Michael Taylor, Author at STELLA

There Will Be More of Us: Rachel Stagner on STELLA, ARSET & Growing a NASA Mission-Literate Workforce

Michael Taylor — Sat, 21 Mar 2026 23:31:00 +0000

There Will Be More of Us: Rachel Stagner on STELLA, ARSET & Growing a NASA Mission-Literate Workforce

About Rachel Stagner

Rachel Stagner is STEM Coordinator and science educator at Templeton Academy in Washington, D.C., and a NASA Climate Change Research Initiative (CCRI) Associate Researcher/Educator. Over 15 years of teaching — across physics, chemistry, biology, ecology, and a dedicated NASA Earth Science Research course — she’s developed a thoughtful, practical approach to bringing NASA science into the classroom.

STELLA in the Classroom

STELLA (Science and Technology Education for Land & Life Assessment) is a suite of low-cost, open-source instruments developed under the NASA Landsat mission, with components Commercial of the Shelf (COTS) parts. Rachel uses STELLA to give students genuine hands-on experience, circuit assembly, embedded programming, data collection, and spectral analysis in an approachable, buildable format.

One of the things she finds most valuable is the connection STELLA creates between what students can measure in their own neighborhood and what Landsat is capturing from orbit. That link between a small handheld instrument and a NASA satellite mission helps students start to see where they might fit in the larger picture of Earth science.

ARSET as a Starting Point

Rachel introduced ARSET, NASA’s free Applied Remote Sensing Training Program, at the very beginning of her NASA Earth Science class, spreading the introductory module across five or six class periods before students moved into hands-on work.

Students who came in with little or no remote sensing background began asking questions about how satellites collect data and how observations get turned into imagery.

A particular highlight was an ARSET unit using Jupyter Notebooks to map cyclone data — it generated more student excitement than anything else she’d seen that semester.

Her takeaway: ARSET and STELLA work well together precisely because they serve different purposes. ARSET helps build the conceptual foundation. STELLA gives students something concrete to do with it. Used together, they offer a natural progression from learning about remote sensing to actually doing it.

"There Will Be More of Us"

When Rachel talks about where she hopes this work goes, the throughline is community. She’d like to see professional development treated as an ongoing cycle where teachers who attend a workshop come back a few months later to share what they’ve tried, and eventually help facilitate for the next group.

She also likes the idea of a STELLA Share-A-Thon: a low-key, celebratory space where students can show what they’ve done with their instruments and hear what other students across the country are exploring. Something like comparing plant health data between cities nothing overly formal, just students and teachers learning from each other.

The hope is that each workshop, each teacher, each student who engages with these tools makes it a little easier for the next person to find their way in.

Resources

- STELLA: https://landsat.gsfc.nasa.gov/stella/
- ARSET: https://appliedsciences.nasa.gov/what-we-do/capacity-building/arset
- STELLA Community Forum: https://github.com/STELLA-Landsat/STELLA/discussions

STELLA / ARSET Interview Transcript

Interviewer: Mike Taylor (NASA GSFC, Landsat Outreach Scientist) Guest: Rachel Stagner (STEM Coordinator & Teacher, Templeton Academy, DC)

SEGMENT 1 — Introduction & Background

(00:00:08 – 00:02:14)

MIKE TAYLOR: First off, thank you for joining us. Can you introduce yourself and tell us a bit about your background as an educator? How did you end up teaching at Templeton Academy and what subjects do you cover?

RACHEL STAGNER: Sure. My name is Rachel Stagner. I’ve been teaching for about 15 years. I started in 2009. I started teaching in Portland, Oregon, and that’s where I got my master’s degree in education, as well as a master’s of science in teaching. And then I moved to DC — it was summer of 2018 — for the Einstein Fellowship, which I did at NASA, and then I ended up staying in DC. The next year, 2019–2020, I got a position here at Templeton Academy. So I’m the STEM coordinator. I also teach basically everything because we’re a very small school. So I’ve taught physics, chemistry, biology, various variations of biology, ecology, human ecological history, and I’m teaching a NASA Earth science research class. Right now I’m teaching marine biology, so I teach basically everything. The only things I don’t feel comfortable teaching at this point are an advanced physics class or a really advanced chemistry class. Other than that, I can teach it all.

MIKE TAYLOR: That’s great. It’s a little bit — yeah, it’s kind of overwhelming when I think about it.

RACHEL STAGNER: I’m like, oh my goodness. Yeah.

MIKE TAYLOR: So I mean, I respect you — you wear a lot of hats.

RACHEL STAGNER: That is correct.

MIKE TAYLOR: PAEMST — do you call it “pamst” award?

RACHEL STAGNER: I don’t know.

MIKE TAYLOR: Oh yeah. Yeah, yeah. The Presidential Award for Excellence in Math and Science Teaching, which was actually discontinued last year, but —

RACHEL STAGNER: In 2023, I applied and I was named a finalist. And then in January of 2024, they released the list of winners.

SEGMENT 2 — CCRI Program, STELLA & Curriculum

(00:03:09 – 00:05:17)

RACHEL STAGNER: With the Einstein Fellowship and the Aeronautics Mission Directorate, I learned a lot there that I was able to apply. Like, I did an engineering course when I first started teaching at Templeton, and we were able to use some of those things. But last summer when I did the CCRI program, we developed a curriculum module focused on the five teacher teams and the research projects that we were working on. So we created a unit plan. And I think my goal all along was to try to use that unit plan in a new class and kind of focus it around NASA Earth science research. So I learned a lot during that experience about satellites and remote sensing, and this whole class is based on that curriculum — but also helping students navigate things like how to collect data, how to pull data from NASA resources, as well as ARSET, which I always forget the acronym, but they are ARSET training programs. So they’ve been using that to help them understand remote sensing, NASA Worldview, and NASA Eyes on Earth. So hopefully all these resources are going to help them.

We are finishing up our last unit on urban heat islands right now. And then starting after spring break in April, they’re going to start to choose their own adventure and pick a topic that we’ve covered — or something maybe tangentially related to it — that they can either use NASA Earth data for, or go out and collect data on their own, maybe a little combination of both based on their interests. So that is hopefully the plan. So far it’s going well, and I hope to incorporate STELLAs maybe even as soon as next week — to try to introduce them to the students and have them do some basic experiments so they can kind of understand the purpose and the value of them. And yeah, we’ll see what happens.

SEGMENT 3 — STELLA Workshops & Growing the Community

(00:06:11 – 00:10:32)

RACHEL STAGNER: And we keep offering more this year, which is really great. So the goal there is to offer free PD to teachers. We’ve partnered with American University and the DC Space Grant to help post us and to do the hard work of finding us a place to be on a regular basis. So it’s been really great.

MIKE TAYLOR: And then, what drew you to the NASA STEM Education Ambassadors program? And what has the experience been like so far as a practicing teacher?

RACHEL STAGNER: I mean, Matt is the one who told me about it. And as CCRI fellows last year, we were invited to be a part of it. So I’m continuing it. But this year, I think the value of it, from my perspective, is the networking. I’m lucky enough because I’ve had a chance to be with NASA a couple of different occasions wearing different hats, so I know a lot about the resources that are shared — but that doesn’t mean I can’t learn more stuff. So every time we have one of the meetings, I’m hopefully learning more about the ways that people are using it. But also I think the networking is very important. For example, Nick and I met during one of the meetings — the office hours. So he and I are now hopefully going to collaborate a little bit to do something with STELLA. And he has a student who —

MIKE TAYLOR: Yes.

RACHEL STAGNER: So Matt Pearce and Nick — Nick Barbi. That’s it. Yeah. So like Nick Barbi, another teacher, is really interested in incorporating STELLA in his classroom. He’s done some work with that. So I think that’s the power. I think what I’d like to use the STEM Ambassador program for is to find other teachers who want to collaborate on projects that don’t just take place where we are, but maybe comparing data across different classrooms, different states, all of that.

And then — Ryan Miller and I and other CCRI fellows basically put on that professional development, which STELLA was part of. So that was really great. I think I learned a lot more about STELLA and also started to think about how other people could use it in their classroom. And the one that we did here in January, same thing. Like every time I’m having a chance to build a STELLA or help other people build a STELLA, I learn a little bit more about how to use it myself. And so I am continuing that knowledge.

Hopefully now I have a colleague here in DC — Brooke — who I’m working with on that project. And so there’s more of us now. Hopefully there’s more of us. It’s like that Hamilton song — like there’ll be more of us, right? Like, so we’re going to just keep hopefully doing things with STELLA so that we can all bring it to our kids, because STELLA is a great program and needs more support, and it doesn’t have the kind of built-out support that you would expect for, like, a commercial product.

MIKE TAYLOR: Right.

RACHEL STAGNER: And so I’m happy to help with some of that. And I think that’s the power of keeping up with these kinds of professional developments — it just gets more people who are interested in doing that.

SEGMENT 4 — Introducing STELLA to Students

(00:10:35 – 00:12:53)

MIKE TAYLOR: So you haven’t introduced STELLA formally to your classes, as you said, but you’re hoping to bring NASA Earth science to students soon.

RACHEL STAGNER: The students soon, likely after spring break in early April. Yeah, that was the main factor in the timing.

MIKE TAYLOR: And what does the runway to introducing that look like for you? What did you intend to do with your students?

RACHEL STAGNER: We’ve got — I think the runway to it was I wanted to have the first part of the class be the introduction to different tools. That’s where the curriculum came in, because now they’ve been learning about all the different ways that NASA Earth science research can help inform us about the Earth and how scientists do that. So the point of bringing STELLA in was to give them another tool. So as they start to think about their own questions — here’s another tool that you can use. You can potentially build it themselves. We’ll see if anyone’s interested in doing that, and then also use it to collect data. So I think that’s kind of the rationale about why and when.

In terms of the on-ramp for it, I think I’m going to model what I do with them using some of the basic stuff that the teachers and I were doing at some of the workshops — like obviously showing them how to use it, how it works, why it works. And just having them go collect data. I think that’s probably going to be the easiest thing. I’ll probably have them come up with a basic question, and then just go collect some data, and then hopefully give them some structure of how to analyze it, because I think that will also be very cool for them. Which is another reason why taking the R class is helpful, because as I get better with manipulating the data and figure out what you can do with it, I’ll be able to help the kids with that too. So that’s the goal. That’s the timing part of it.

SEGMENT 5 — How ARSET Prepares Students for STELLA

(00:12:57 – 00:15:43)

MIKE TAYLOR: Well, and in that respect, you had mentioned ARSET. So how are you using it to prepare your students, or have them use it with STELLA, so they can get a better understanding?

RACHEL STAGNER: We used ARSET the first couple weeks of the class. I had assigned them the introductory module. Like, there’s five parts of it, I think. So we broke it up over like five or six class periods where they were doing one module. And then we talked about it and they had a little check-for-understanding quiz — which, spoiler alert, was just questions from the ARSET modules that I just used for in-class understanding, which was great.

I think it was a really good way for them to be introduced to what satellites do and how remote sensing works. And I think a lot of them — they told me they really enjoyed it. And when I did it last summer as part of the CCRI experience, I found it very useful and it taught me a lot. And so I just figured that instead of me trying to fumble my way through trying to teach them a lot of that stuff, ARSET actually did a better job with all the visuals and the connections to satellites already built in. So that prepares them because it will actually give them some kind of background with which to understand what the STELLA is doing. And also whatever they choose to do for their research, if they want to —

Like, I just give an example: since we’re doing urban heat island stuff right now, if they wanted to do data collection on the ground with infrared thermometers or pollution sensors or whatever, they could actually go back and compare that data to NASA satellite data. And I think they will have a better idea of how that data is collected and how it’s used.

And at the end, I know the last module in the ARSET training is looking at a couple of examples of how to use it. So while it’s not exhaustive, I think if any kids want to challenge themselves with something that ARSET has a training for, I can also point them towards that module and hopefully help them figure out what to do with huge NASA data sets.

That’s why I like the STELLAs too, because these data sets are not massively huge — and while complicated to deal with as all data sets are, they’re not as overwhelming as a satellite download.

MIKE TAYLOR: So would you say it’s sort of a nice bridge to understanding some NASA data and making it more — don’t put words in your mouth —

RACHEL STAGNER: Oh yeah, for sure. Yeah. I think it’s definitely a bridge to help them figure out how to go from small-scale data collection to massive data collection.

SEGMENT 6 — Student Responses & STELLA Engagement

(00:15:59 – 00:19:27)

MIKE TAYLOR: And so how have the students responded to ARSET content so far? Have you seen the light bulb moments you were hoping for?

RACHEL STAGNER: Yeah, I think so. I think — I always think — it’s a small class, there’s only nine of them. So I talk to them often about what are you enjoying. Like after every mini unit I’m like, hey, what did you like? What did you not like? — which I’m going to share with Matt Pearce. But also after the ARSET modules, like after we did a kind of check for understanding quiz, like they were doing really well with that.

MIKE TAYLOR: Yes. Yeah. For sure. So I think that they’re going to be very fascinated by this, which is fun. So and then I mean, along with the data science and all that — STELLA supports a wide range of engineering skills, from circuit design and 3D printing to optical engineering and data analysis. Which of those dimensions do you think will most resonate with your students, and why?

RACHEL STAGNER: I think the analysis part, because I’m not sure if we will actually build any for the students. So while I think the engineering part is really interesting and fascinating, and eventually I’d like to have that happen — because this class is so broad and kind of focused on just Earth science in general — I don’t know if any students will choose to go that route. If they did, that’d be great. I do have a couple of kids who are really interested in engineering that I think we can build around, and I’ll push that for those kids.

SEGMENT 7 — Kenneth Leslie’s Summer STELLA Boot Camp

(00:19:29 – 00:22:00)

RACHEL STAGNER: I think the data analysis part is going to be the most useful. And probably the investigation design — like the thinking of how we can use this tool. So understanding its capabilities and then trying to come up with some kind of investigation, and then take that data and do something with it. I think that will be the most useful part for these kids.

I do know that this is kind of related-unrelated to that — another teacher, Kenneth Leslie, he came in at the end of our STELLA PD on the 24th of January. He’s actually doing a summer engineering workshop. Did you know about this?

MIKE TAYLOR: Oh, wow. I haven’t told you about this yet.

RACHEL STAGNER: Okay, so DC Public Schools has programs. One is CRI — I can’t remember what that stands for. The other one is like a summer work program. And again, I’ll get you the acronyms if you want them. But he does — because there’s not a lot of internship availability with engineering and STEM in DC proper — and he teaches at McKinley Technical High School. He basically every summer creates opportunities for the students. Some of those things are like the rover programs that NASA used to have. But this year he’s created a six-week like boot camp on STELLA. So I’m maybe helping with him. The goal was to have like five of my students and 20 of his students in this, and we’re going to start at American University where the kids are going to learn and build and 3D print everything, and then go from that to the data collection to the eventual presentation of something that they’ve created — some sciencey data and analysis.

MIKE TAYLOR: He’s a busy man.

RACHEL STAGNER: He’s a busy man. So I haven’t really been able to pin him down. He’s got this whole plan. He’s talked to Chelsea and American University and the DC Space Grant. And this is hopefully moving forward. I may or may not be able to help with that. But that’s the plan. So there’s even more in the works. And I think that Kenneth is such a great advocate for everything STEM in DC that if he gets his claws into STELLA — which he has — he will probably use it pretty regularly, which is great.

MIKE TAYLOR: And now would you recommend, like, say, him using ARSET — you know, so maybe they build their STELLA and then they need examples of how to use it and all that. So would you recommend using ARSET to start understanding some of these investigations that they might be able to make and actually do some comparisons with NASA data too, or anything like that?

RACHEL STAGNER: Yeah, absolutely. I think — oh, would you implement it? Yeah. I would basically — I mean, I think that could be part of the “how does remote sensing work” — right, and how do you take remote sensing data —

SEGMENT 8 — STELLA and ARSET as Complementary Tools

(00:22:36 – 00:25:04)

RACHEL STAGNER: And they’re not parallel tools. I think, depending on a student’s interests — especially if they’re coming in with not a lot of background information on remote sensing in general — I think it provides a good foundation for understanding that. And then if you kind of make that natural connection — like there’s just like a mini satellite in a lot of ways — then they kind of understand how it works and then even start to maybe think about what kinds of data they could collect with it and how it connects to the bigger missions at NASA or science. And again, the idea of — you know, this is what the satellites do, you’re able to do this with a small instrument and in a smaller scale around your school, around your neighborhood, around your community. It might even lead them to think about how they could compare the data that they’ve collected with the satellite data.

But also I think some of the other ARSET modules are specifically about how to use certain data sets and what to do with them. And I think that based on a kid’s interest, it could be a natural fit to help point them towards some of those resources to help them learn about what they might be able to do with the data after they’ve collected it.

SEGMENT 9 — What Teachers Need to Feel Confident

(00:25:08 – 00:27:37)

MIKE TAYLOR: As a nationally recognized STEM educator and someone who has worked at NASA — so you’ve seen both sides — what do you think teachers most need to feel confident to bring real NASA science tools into their classrooms?

RACHEL STAGNER: I think a lot of it is knowledge. One of the things that I experienced when I was at headquarters was it was like a fire hose. There’s so much stuff that NASA does and also so much educational material — that I think just the knowledge of what NASA has in terms of educational programming and lesson plans and then like these different things like the Aerokat and the STELLA and all of the different kinds of side things that people are able to do with NASA tools and data — I think that’s the most important thing, and that is the limiting factor. It’s just not well known. You know, you get these specialists that have maybe heard of a program and they’ve done that, right. But the sharing of that is somewhat limited, I think, or just there’s so much of it that it’s just overwhelming. So I think exposure is a big one.

And then I think professional development is also a big thing. Like if you can help teachers understand how to use some of these tools, that is always a great way to get them to do it. I think when you’re introduced to a lot of things — like I said, the firehose effect — you’re like, wow, there’s so many things. But then there’s often not enough time to digest all of it and to figure out what you might do with it. So good professional development helps you not only learn about stuff but also do it so that you can help your students do it later. I think that’s the key. So targeted stuff like what we’ve been doing with the STELLA workshops is great.

I think following up on that — I would like to do a follow-up session because the motivation always starts out high. You know, these teachers who come to these are self-selecting — they want to come and learn about the stuff. But then the realities of the school day and the school year and life, and not having potentially people to collaborate with, can kind of slow progress.

SEGMENT 10 — Follow-Up PD & Cycling Teachers Back

(00:27:38 – 00:28:24)

RACHEL STAGNER: So I think just following up on stuff is important too. Like if you do a STELLA workshop, let’s do another one in like three months and have these people back and then, hey, what have you done? What are you thinking? You know, that kind of stuff. So it’s like a cycle of professional development — with a lot of NASA tools, that’s important.

MIKE TAYLOR: Yeah.

RACHEL STAGNER: And I think ideally, if I were to do that, I’d like the folks who already did that workshop to possibly help proctor the next workshop. So they get the other side of the experience as well.

MIKE TAYLOR: Right. I think that would also really help as well — building those skills.

SEGMENT 11 — Advice for Teachers New to STELLA or ARSET

(00:28:31 – 00:30:11)

MIKE TAYLOR: So, for a teacher watching this interview who’s curious about STELLA or ARSET but doesn’t know where to start — what would you tell them? I know you’ve given some hints, but — I mean, ARSET’s free?

RACHEL STAGNER: I mean, ARSET’s free. So I would log in and take the first module yourself. And I think that would be a good place for a person coming into this whole field of wanting to do this in their classroom with not a lot of background information — that’s a great place to start. I didn’t have a lot of background information. That’s why it was such a good place for me to start.

And then in terms of the STELLA stuff, I think if you are someone who teaches engineering, or any kind of circuit design, or mostly computer science, I think they could probably look at a lot of that material and figure it out and maybe use it. I think going to professional development, if you have one in your area, is great. Or just — reach out. I think just finding out where you can go and build one, if you can’t build it yourself, or talking to other people who have used it — I think is really valuable. So even like the STEM Ambassadors, or any other resources that they can find, because it’s a little intimidating — you know, it’s just a really cool instrument. But if your background is not strong, then it might be intimidating. So I think reaching out to people who have used it — and I think the GitHub is a good idea to help spur discussions. I’d like to see more of that. I think that’s where you start.

SEGMENT 12 — Vision for the Future of STELLA & ARSET

(00:30:16 – 00:32:18)

MIKE TAYLOR: Finally, what’s your vision for where STELLA, ARSET, and the community of educators can go over the next few years? And what would success look like to you? And then of course, if there’s anything else you’d like to add that I’ve neglected, please feel free to do so.

RACHEL STAGNER: I think that this is going to have to kind of be a grassroots effort — teachers who want to learn more about it and who want to collaborate to kind of do those things. Right, like that. Would that be successful? To me, it’s like — I think Nick Barbi mentioned — like if we had some kind of a STELLA competition where students were able to share the research that they’d done in their classrooms. And maybe it’s not a big formal competition, but even just a share-a-thon where students are like, “Hey, I did this really cool thing.” I think that would be a success. I would like to see that.

I would like to be able to collaborate with either people here in the district — like on a small scale — or teachers in other places, to have their students do a project with STELLA and then compare that to something that I’m doing in my classroom. Like I’m just giving an example — maybe we wanted to look at, I don’t know, plant health in another city and compare it to plant health here. That’s not the perfect example, but like something that could be measured in multiple locations, right? And then the kids could be like, hey, we found this here. And what did you guys find? I think that builds not only buy-in from the kids, but also gives them the sense that it’s not just what’s happening in our classroom that’s important. Like we actually can collaborate with other classrooms and other teachers to see even more about the world than what we can measure here in our area.

So that’s what I think would be successful to me — creating these communities of practice with STELLA where teachers are talking to each other, and then maybe even having some kind of a place where students who are using STELLAs can share with each other. That would be very successful, I think.

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STELLA-1.2 Official Launch: Earth Science Workforce Development

Michael Taylor — Tue, 24 Feb 2026 02:53:00 +0000

STELLA-1.2 Official Launch:
Earth Science Workforce Development

NASA scientists and engineers at Goddard Space Flight Center, led by Paul Mirel and Mike Taylor, have officially launched STELLA-1.2 (Science and Technology Education for Land/Life Assessment), a modular remote sensing platform that makes Earth observation science more approachable while building the next generation of mission-literate professionals. STELLA is a force multiplier for NASA missions and programs—it amplifies their impact by breaking down barriers that make satellite remote sensing seem inaccessible, transforming mission data from abstract numbers into tangible participatory science that develops the technical workforce Earth observation systems depend upon while creating thousands of mission-literate professionals who understand why NASA investments matter.

The STELLA-1.2 base platform represents a breakthrough in accessible Earth science instrumentation. This modular foundation features GPS positioning for precise location tracking, onboard SD card data logging, a real-time display, and a versatile computing core that accepts interchangeable sensor module plugins. Users can configure instruments for different applications by simply swapping sensor packages in and out, enabling measurements across multiple Earth system spheres—biosphere, hydrosphere, and atmosphere. The platform’s lightweight, field-portable design weighs between 33 and 450 grams depending on configuration, and all files and instructions for instrument construction, data acquisition, processing, and initial analyses are freely available online at https://science.gsfc.nasa.gov/stella/. Following extensive beta testing and user feedback, the official STELLA-1.2 features redesigned 3D-printed housing with improved manufacturing tolerances, enhanced structural integrity, and superior environmental protection for field deployments.

The flagship Remote Sensing Plugin is now available, featuring 18-channel spectral sensing from 410 to 940 nanometers with sensor bands that overlap with Landsat 8 and Landsat 9 Operational Land Imager instruments. This spectral alignment allows for comparison of measurements across different accuracy and precision levels, spatial scales, and temporal scales. The module includes thermal infrared temperature measurement plus temperature, humidity, and pressure sensors for comprehensive atmospheric monitoring. While STELLA cannot match the high-precision, high-accuracy instruments in NASA’s Earth Observing fleet which cannot be duplicated with inexpensive, off-the-shelf components, this spectral overlap enables users to understand what satellites observe from space through direct ground-based measurements. The enhanced official RS module features soldered connections instead of connector-only assembly, significantly reducing field failures and improving long-term measurement stability. Additional sensor modules in development include the Expansion Module for extended sensor connectivity and the Lab_Spec Module for advanced spectroscopy applications, each maintaining the same plug-and-play architecture for multiple sensor combinations.

Multispectral and thermal measurements taken with the STELLA‐1.1, demonstrating the instrument's capability to simultaneously derive a vegetation index (e.g., normalized difference vegetation index) and measure temperatures, to compare vegetation parameters and surface characteristics across heterogeneous landscapes. STELLA-1.2 has the same capability. This image from the journal AGU Perspectives of Earth and Space Scientists: Science and Technology Education for Land / Life Assessment (STELLA): Democratizing Remote Sensing Science With Low-Cost Open-Source Instruments for Research and Education

STELLA directly addresses critical workforce development needs by making hands-on remote sensing accessible to those who lack advanced training or expensive equipment. Users build career-ready skills in engineering, remote sensing, environmental monitoring, and geospatial technology through authentic data collection experiences across multiple Earth system spheres. By constructing their own instruments using through-hole electronics assembly, learners gain practical experience with sensor systems, embedded programming, mechanical design, and statistical analysis—all while developing familiarity with NASA data products and Earth observation workflows. STELLA allows users to collect their own data, which creates a deeper understanding of the meaning of the resulting data and the emotional attachment and technical knowledge needed to defend or refute that data, impossible to achieve with pre-existing datasets. Through direct experience with measurement limitations and capabilities, users develop deep appreciation for the precision instrumentation and rigorous calibration required for NASA’s Earth observation missions.

The modular platform transforms training across multiple sectors: workforce development programs teaching geospatial technology, agricultural training in precision farming, technical colleges building remote sensing labs, NASA partnerships creating mission-literate professionals, and environmental organizations building community-based monitoring capacity. Due to low cost and modular design, STELLA instruments can be deployed in large groups to make multipoint surveys at times and spatial scales chosen to meet specific needs—acting as a force multiplier that extends observation capabilities beyond what high-precision instruments alone can achieve. The ability to collect data over many locations in short intervals is especially important for ecosystems where land cover changes occur rapidly. STELLA’s spectral sensing capabilities enable quantification of plant productivity using NDVI (Normalized Difference Vegetation Index) and near-infrared reflectance, monitoring of leaf reflectance and temperature to assess water stress, and estimation of both energy and carbon fluxes across plant surfaces—providing critical data for agricultural optimization and ecological research across the biosphere.

Join the STELLA Community Forum! Let's Build, Share, and Innovate Together!

As a crowdsourced, community-driven project, STELLA provides free access to complete build documentation, video tutorials, programming guides, 3D printable files, and CircuitPython libraries. The accessible drag-and-drop programming makes instruments approachable for users without extensive technical backgrounds while offering sophisticated capabilities for advanced applications. This open approach creates opportunities for new directions in workforce development and scientific research by enabling educators, researchers, and training programs worldwide to adopt and adapt STELLA for measurements across atmosphere, hydrosphere, and biosphere. Due to modern capabilities, low cost, and design simplicity, STELLA brings once futuristic instrumentation into the hands of both amateur and career scientists, creating new pathways to Earth science careers and building a workforce that understands NASA’s Earth observation capabilities from the ground up.

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NASA Acres Supports STELLA Workshop at American University

Michael Taylor — Sun, 22 Feb 2026 02:58:10 +0000

NASA Acres Supports STELLA Workshop at American University

Story By NASA Acres

Last month, NASA’s Science and Technology Education for Land/Life Assessment (STELLA) initiative organized a hands-on workshop for middle and high school teachers at American University focused on advancing remote sensing skills and STEM workforce development. STELLA is a low-cost, open-source, handheld spectrometer platform that participants build and use to measure light reflectance and environmental parameters, helping connect field-based observations with NASA satellite remote sensing.

STELLA Team Lead Mike Taylor led the workshop, with NASA Acres’ Drs. Mike Humber and Allison Bredder serving as contributors alongside Paul Mirel, creator and lead engineer of STELLA, who delivered a talk and Q&A, and Natalia Quinteros Casaverde, who shared a presentation on her use of STELLA to support home garden monitoring in Jamaica. The workshop was organized and planned by Chelsey Brown, Program Manager for the NASA District of Columbia Space Grant Consortium and the Integrated Space Science and Technology Institute (ISSTI). Funding was provided by a grant Chelsey received from the American Physical Society. It included contributions from Rachel Stagner, a nationally recognized STEM educator, 2023 PAEMST Awardee, 2018–19 Albert Einstein Distinguished Educator Fellow at NASA, and founder of STEMTeachersDMV, which also organized and sponsored the workshop.

During the workshop, teachers progressed from understanding how sunlight interacts with Earth’s surfaces to applying Landsat imagery, measuring spectral reflectance with STELLA-Q2 spectrometers, and analyzing vegetation health using NDVI, gaining skills they will now bring directly to their classrooms and students. The presenters highlighted techniques that support agricultural applications, demonstrating how NASA satellite data and field spectroscopy inform crop monitoring, resource management, and decision-making. Teachers assembled and programmed their own instruments, collected and analyzed field data, and gained practical experience aligned with real NASA mission applications. Participants left the event with functioning instruments, hands-on remote sensing experience, and positive feedback highlighting the value of the workshop’s practical, real-world focus.

Through initiatives like this, NASA Acres advances workforce development by equipping educators and students with applied remote sensing skills and helping bridge the gap between NASA Earth observation data and on-the-ground agricultural and environmental applications.

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Building Tomorrow’s Earth Science Workforce, One Spectrum at a Time

Michael Taylor — Fri, 20 Feb 2026 01:46:55 +0000

Building Tomorrow's Earth Science Workforce, One Spectrum at a Time

How NASA's STELLA Instrument is Multiplying Mission Impact Through Student Engagement

In a sun-drenched corner of Southwest Florida, high school students are learning to see the world the way NASA does—by measuring light invisible to the human eye. It’s August 2025, and at the Suncoast Faulhaber Fab Lab in Sarasota, twenty students are building spectrometers, collecting data from wetland plants, and discovering a career landscape they never knew existed.

This is COASTWISE (Community Observations and Analysis using Spectroscopic Techniques and Wetlands Imaging to foster Stewardship of the Environment) -making Earth observation science accessible, understandable, and inspiring to the next generation.

The Participants

Nick Barbi, founder and president of the Science and Technology Society and a NASA STEM Ambassador, sat down with Michael Taylor, NASA STELLA’s team lead to discuss the program. They were joined by Tara Bergstrom Merino, a technology professional at Bank of America and coach of the state championship Ultronic robotics team, and her son Michael Merino, one of the student participants.

Their conversation reveals how NASA’s STELLA (Science and Technology Education for Land/Life Assessment) instrument is doing more than teaching science—it’s building pathways to careers students didn’t even know existed while multiplying the impact of NASA’s Earth observation missions.

More Than Rocket Ships

“The common answer back was, doesn’t NASA just do like rocket ships?” Tara recalled. “Learning that there’s so much more to what NASA does and that they actually work on instruments and they’re doing observational things and they engage with students and they’re doing research, I think was eye opening for the students.”

For Michael Merino, who participated in COASTWISE, the revelation was profound. When asked if he knew NASA monitored Earth from space, he admitted: “I was not aware to the extent that they do.” But working hands-on with STELLA changed that understanding completely.

“The concepts, yes, as well as the type of technology that they’re using,” Michael explained. “And as well as the extent to which NASA does, you know, take notes and record data on the environment, given how direct STELLA is.”

A Mission Multiplier: Connecting Space and Ground

Nick Barbi sees STELLA as a powerful complement to NASA’s satellite missions, particularly Landsat. “It seems so out of reach with the Landsat data, other satellite data and the imagery,” Nick explained. “If you can say this is basically how it’s done. It’s just more sophisticated and a tad more expensive than what we’re trying to do. So the concept is very similar—that exactly is the point.”

This connection is crucial: STELLA uses the same spectroscopic principles as Landsat and other NASA Earth observation satellites, teaching the future workforce ground-based methods that complement and help them understand satellite observations. Students learn why ground truth matters, how spectral signatures identify vegetation, and how local measurements relate to global monitoring efforts.

“It elevated the importance of what we’re doing to say that NASA on a much larger scale is doing this, doing it at a much more scientific level, a worldwide level,” Nick noted. “It gave it a substantially stronger rationale and credibility in terms of what we’re trying to do.”

The program also introduced students to NASA’s NDVI (Normalized Difference Vegetation Index) the same metric NASA uses from satellites to assess plant health worldwide. By calculating NDVI from their own spectral measurements, students directly connect their work to NASA’s operational missions.

Nick pointed out the synergy: “We pointed out the similarity between what NASA’s doing with Landsat and what we’re trying to do.” The goal is to eventually integrate drone-based spectroscopy with ground measurements, creating a multi-scale approach that mirrors how NASA combines satellite data with field observations.

This makes STELLA a true mission multiplier, it doesn’t replace NASA’s capabilities but extends their reach into communities, classrooms, and the next generation of scientists who will use and advance those capabilities.

Workforce Development for a Earth Observation

But COASTWISE isn’t just about understanding NASA missions, it’s about preparing students for careers they might never have considered.

“I think STELLA Instruments are the greatest thing to happen—the most significant innovation to happen in STEM education since robotics,” Nick declared.

Nick pointed to a growing workforce need in the analytical instrumentation sector. “There are hundreds of thousands of instruments out there,” he explained. “Somebody’s got to run them with the technical and scientific bent and understanding.”

The answer, he explained, is “a different group of people than the engineers who build robots. This is many of the kids interested in geology and environmental chemistry, data processing. You know, math students—they may not be skilled in building robotics and electromechanical devices and so forth. Maybe scared of them.”

Tara Bergstrom Merino, who brings both a technology career background and robotics coaching experience to the conversation, emphasized the career exploration aspect: “How are you supposed to know that you want to be an architect? How are you supposed to know that you wanna do scientific data analysis if you’ve never actually been able to work alongside someone that does that with a real data set, normalize the data, put a model against it, understand the impact of that and have to do the hard work right? Not just the fun work.”

She continued: ” COASTWISE and STELLA provides them an opportunity to utilize a tool in a way that gives them information and experiences they wouldn’t have. I think then being able to work alongside real scientists and folks that built the instrument or people that use the instrument and hearing how they use it connects them to real world experiences and gives them an understanding of like how they could use what their careers could be like someday.”

Skills That Transfer Across NASA's Mission Spheres

The workforce development goes beyond just career awareness. Students gained concrete technical skills that transfer directly to careers across NASA’s Earth science, data science, and applied research spheres.

“COASTWISE allowed them to connect with a technology and a terminology that they never would have had,” Tara explained. “They got to program in a way that’s very different… They don’t do any programming over a data set to analyze data—that was something that they had never done before. A lot of them had never looked at data set that needed to be normalized before.”

She pointed out that even coming from robotics, “the amount of variables they were looking at was also much more complex than something that we would look at in robotics. I think the data component was something that is a new skill for them. I think just working with a spectrometer was definitely a new skill for them.”

These aren’t abstract educational objectives—these are the exact skills needed in environmental monitoring, agricultural technology, climate science, and countless other fields where Earth observation data drives decisions. Students who understand both satellite data and ground-based measurements become the professionals who can effectively use NASA’s Earth observation assets.

Learning from Failure, Contributing to Progress

One of the most powerful workforce development moments came when things went wrong. The new 3D-printed STELLA housings proved difficult to assemble. Rather than just finding a workaround, Nick turned it into a learning opportunity.

Two students, both freshmen at the time—prepared an engineering failure report and presented it via Zoom to Paul Mirel, STELLA’s creator and chief design engineer at NASA.

For Michael Merino, watching his classmates present technical problems to NASA engineers was transformative. “It was a very positive experience,” he recalled. “Paul was very accepting and obviously took notes of all of our feedback. And made sure to feel like our input was going to be used to better the product… We felt like we were now part of the progress that we were seeing in STELLA as well as getting a little bit of insight into what was going on behind the scenes.”

This wasn’t just a classroom exercise—it was real professional experience contributing to NASA’s outreach mission. As Tara noted: “That can be hard for a student, and even as an adult. So I think, you know, no matter what, those sort of opportunities are really educational and valuable to students. And then I think as engineers and as adults to hear from students is also allowing us to help them better their skill set.”

Multiplying NASA's Earth Science Impact

COASTWISE demonstrates how STELLA multiplies the impact of NASA’s Earth science missions across multiple dimensions:

Earth Observation Education: Students learn the same spectroscopic principles NASA uses to monitor vegetation health, wetland conditions, and ecosystem changes from space. They understand Landsat not as an abstract concept but as a more sophisticated, high-quality version of what they’re doing themselves.
Ground Truth and Validation Concepts: While COASTWISE measurements are educational rather than operational, students learn why ground truth matters and how it complements satellite observations. This understanding is crucial for the next generation who will use NASA data professionally.
Community Engagement Multiplier: NASA’s Applied Sciences program emphasizes making Earth observation data useful to communities. STELLA-equipped students become ambassadors who can help their communities understand and use NASA’s Earth observation resources.
STEM Workforce Pipeline: NASA faces workforce challenges across its Earth science portfolio. STELLA creates entry points for diverse talent in environmental monitoring, data analysis, and applied science—careers that directly support NASA’s mission.
Mission Understanding and Advocacy: Students who understand how NASA monitors Earth become advocates for continued Earth observation. They can explain to their communities why missions like Landsat, PACE, and future systems matter.
Complementary Data Networks: As STELLA use expands, networks of community-based observations complement satellite data by providing fine-scale, frequent measurements that satellites might miss—a true mission multiplier effect.

A Model for the Future

Nick Barbi envisions COASTWISE as the flagship of a larger program called IDEAS—Instruments for Discovery, Exploration and Assessments in Science. The model would use various STELLA instruments across different scientific domains, always focused on workforce development and complementing NASA’s missions.

“Robotics is aimed at future engineers and coders, while IDEAS is aimed at would-be geologists, biologists, environmentalists, chemists, astronomers,” Nick explained. It’s a different pipeline into STEM careers, one desperately needed as Earth observation becomes increasingly critical.

Tara sees the broader potential: “I think any large company should work on a model like this, right, where you’re engaging something that’s kind of cheap and accessible to as many people as possible. You can get students engaged. I have found that students, especially younger students, have such creative minds and they think so outside the box that you really want them to be engaged in projects like this.”

She added: “Students just kind of look at it however they want with their mind wide open. So I think engaging students in this and making it accessible to them with kind of a less expensive tool set can help maybe guide your overarching real modeling.”

The Bottom Line

STELLA isn’t separate from NASA’s Earth observation missions—it’s complementary to them. It’s a mission multiplier that extends Landsat’s impact from orbit to classroom, from data product to workforce development, from satellite observation to community understanding.

It teaches the scientific methods and technical skills that employers across the Earth science sector need. It helps communities connect local environmental concerns to the global perspective NASA provides from space. And it builds understanding of why NASA’s Earth observing missions matter.

As Michael Merino put it simply: “We felt like we were now part of the progress.”

That sense of connection—to NASA’s mission, to real science, to meaningful careers—is exactly what Earth observation needs as it faces the challenges of the coming decades. STELLA multiplies NASA’s mission impact by building the workforce that will carry that work forward, the communities that will use that data, and the next generation that will advance those capabilities.

Transcript

COASTWISE Interview Transcript

Participants:

Michael P. Taylor – NASA GSFC, STELLA Team Lead
Nick Barbi (Dr. Barbi) – Science and Technology Society, Program Director
Tara Merino (Tara Bergstrom Merino) – Program Coordinator, Bank of America Technology
Michael Melvin Merino – Student Participant (Senior)

00:00:08:13 – 00:00:16:12 Michael P. Taylor: Welcome. Nick. Can you introduce yourself and tell us about the Science and Technology Society and how CoastWise got started?

00:00:16:13 – 00:04:49:02 Nick Barbi: Okay, Mike, thank you very much for giving us the opportunity to talk about what we’re doing. My name is Nick Barbi. I was, at one time, a material science scientist. Then I got into making instruments because the first instrument I worked on was a scanning electron microscope and EDS x-ray detector, and we were one of the first to do that. So the story of my life was I became an instrument maker. So that’s one connection with STELLA that we have right off the bat.

I’m still involved in selling hyperspectral imaging cameras to museums. And it’s more or less a part time job, but we sell VNIR cameras, VSWIR cameras and SWIR cameras and extended SWIR cameras. So there’s a whole range, and they typically cost from 40,000 to 140,000. And which is another reason STELLA is so attractive at $200 a unit.

And so I’m still involved in that, but predominantly retired and started the Science and Technology Society about three years ago now, two and a half years and we’re initially it was to hold technology meetings and socializing with people that were in science for their careers or just interested in science, and then we just got organically interested in STEM education and actually is where we’ve been focusing most of our time these days.

And we, the first course, because of my experience, we chose to use the STELLA Q2 which is 18 channel VNIR spectrometer and you know, since I made spectrometers most of my life, various types and sold them, if I wasn’t making them and teaching people how to use them, it was a natural for me to want to do that.

One of the most important spectroscopy, one of the most important features of Sarasota and Manatee counties in southwest Florida, where we’re based is are the wetlands. And it’s an interface between the ocean and the land and a lot of neat environmental and ecosystem things happen in wetlands. So we thought we would use a spectrometer to see if we could differentiate one type of plant from another. And in so doing, learn about the importance of wetlands.

So there was an ulterior motive. Whenever you have an instrument, you need an application. And so we were sneaking in the interest and the exposure to the application, along with talking about spectroscopy, electromagnetic radiation, how to use a spectrometer, data collection, data processing, all that kind of thing. But at the same time, getting speakers to talk about our environment, the ecological system, the importance of wetlands, the damaging of wetlands that due to hurricanes and also development, hurricanes they seem to survive, you know, development they don’t, which is you know, somehow hurricanes because they’re natural do somehow work themselves out. Maybe later I’ll tell you a story about that. But so, we’re, we’re now focusing very much on STEM education for students and trying to do something exciting and different. And NASA with the family of STELLA Instruments has provided us that opportunity.

00:04:49:03 – 00:05:00:01 Michael P. Taylor: Awesome. Thank you very much. That was a heck of an introduction. So, and you answered actually answered probably like, 3 or 4 of the questions doing it.

00:05:00:02 – 00:05:12:02 Michael P. Taylor: So, short interview. Okay. All right. Exactly. So, Tara, again, thanks for joining us. And what is what’s your background and how did you get involved with this program?

00:05:12:03 – 00:09:02:08 Tara Merino: Sure. Thanks for having me. So, my name is Tara Bergstrom Merino. I officially work for Bank of America in Technology. I started in computer engineering, but I spent most of my career overseeing a suite of applications and change across those applications. About eight years ago, nine years ago, I became heavily involved in STEM with the youth in our community, mostly resulting, you know, as a result of my kids. They were very, especially Michael was very interested in STEM, and there was really not a lot in our community for him to kind of develop that interest.

We by chance kind of came into a program called FIRST, for Inspiration and Recognition of Science and Technology. We do not have any sort of presence of that organization in our community. But it was at that time the age group that my kids were in was Lego based. And so they really wanted to kind of pursue a team in there. So, Michael will share, but he, you know, I told him if you wanted to do that, you know, I would help. But, you know, I wanted him to kind of find a team. It could be about ten members. And so he aggressively went and sought out a bunch of students and came with 60 students. So we ended up having six teams because we didn’t want to turn anybody away.

And we did that for quite some time. But when we published that, it caught the interest of Lakewood Ranch proper. And so they’re the number one selling master plan community in the nation. And there’s, you know, a lot of organization that goes behind making sure that it continues to be the number one master plan community. And so they do a lot of activities and events there. So they were like, oh, what is your vision to bring STEM to the community for our youth? I was like, I don’t have a vision. But the whole we really want to bring STEM. There’s like this very significant demand in our community and we think, you know, it’s obviously an up and coming area.

So that ended up I started, you know, kind of like what Dr. Barbi’s doing, but more for youth. I started running meetings and presentations and connecting them with the experts. And I started running math 24 leagues. And we were running all sorts of like we were running the STEM tent at the farmer’s market, and we were doing all sorts of things, when Covid happened, a lot of that went away, just because everything was locked down and we weren’t able to go anywhere. But I remained very engaged in FIRST with Michael and Natalie’s team. We continued that, they continued even running activities over the Lakewood Ranch Facebook page. So like STEM activities, we’d get like every week, we give a STEM challenge out to the students to kind of keep them engaged and connected because that was, you know, an isolating time, I think, for our young folks.

So we did that. But when we came out of Covid, I knew I was going to be moving away from Lakewood Ranch, just because my kids were going to be going to a school that was about 45 minutes south of it. So I didn’t want to re-rigor all of that. When I moved down here though, I got connected with the Suncoast Science Center, the Fab Lab, which is about 15 minutes from my house. And that’s where I met Doctor Barbi. And I was like, oh, well, Doctor Barbi has a vision that was kind of like what Lakewood Ranch wanted to do. And so I said, you know, I’d love to support you in your vision instead of, you know, trying to restart that again. And that’s how we became connected. And then he’s, you know, brought a lot of great programs to the students and fully supportive and COASTWISE is definitely been a staple of that. And I think it’s taught the kids a lot. You know, I don’t think any of those kids even knew what spectrometers were before that. So I think, you know, it’s been an amazing opportunity. The kids have been involved in it for two years now. And I’m just, you know, I’m really just connecting Doctor Barbi with the students, and we have a great relationship doing that.

00:09:24:12 – 00:09:34:04 Michael P. Taylor: Excellent. Yeah. Michael, we’re glad to have you in the student perspective. What grade are you in and what made you want to do coastwise this summer?

00:09:34:05 – 00:09:59:05 Nick Barbi: And don’t say your mother made you do it.

00:09:34:05 – 00:09:59:05 Tara Merino: No.

00:09:34:05 – 00:11:17:06 Michael Melvin Merino: Yeah. So I’m in 12th grade right now, so I’m a senior. And two years ago when it was my mom that brought up the opportunity to do CoastWise, I was actually very intrigued in that. And I shared that with a bunch of other people that I knew. We were all in the same robotics team, so we share that common interest in trying to learn new things. So I originally approached it with like, the, oh, this is just going to be something new to learn, like something I can just add to my skill set. And then going to the meetings when we realized that this was actually something that was very important to the, I want to say the area like the environment, I guess, and helping the wetlands and, you know, understanding how they, their health, how they thrive, how to preserve them. And I got very invested in that. The more that I started going to these meetings. So, yeah, I mean, it’s, I think it was a great opportunity. I think it was definitely a very great chance to learn some new skills and learn a lot about the environment, how it works, how to measure certain things, how to predict the future of those environments, and to help preserve the Everglades for the future.

00:11:17:07 – 00:12:02:14 Nick Barbi: I do want to thank Tara and Michael. Our first group. You know, I contacted Tara, and I said, Tara, I don’t know how to get kids into this. And she said, don’t worry. The robotics team will be there for you. So our first group was almost completely the robotics team. So, I think not only Tara and Michael and Natalie and all the people, but just the spirit, the community spirit they have and the STEM, the love of STEM courses and efforts and experiences and so forth. So it was really critical to us. So I want to thank them for that.

00:12:03:01 – 00:12:11:10 Michael P. Taylor: Before the summer, have you ever heard of, you know, spectroscopy or worked with these particular types of scientific instruments?

00:12:11:11 – 00:12:55:02 Michael Melvin Merino: No. And that was our look at the camera. No. So before before I ever got involved in STELLA, I never heard of any of that terminology before in my entire life. And that’s, I think, part of the reason that me and all my other teammates were so intrigued, was because even though we are so invested in commonly used STEM instruments and, you know, looking at these innovative solutions quite often, that this was a brand new branch that we had never even seen before. So becoming involved in it was, you know, branching into new territory. And I think that’s what originally caught us all and got us engaged into STELLA.

00:12:55:03 – 00:13:02:07 Michael P. Taylor: What made this program appealing for your kids to participate in? So, you know, what excited you about the program?

00:13:02:09 – 00:14:36:12 Tara Merino: Oh, sorry. When the students were younger and they’re part of the Lego branch, that program included an innovation project. So every year they were asked to look at a challenge and find a real world solution for that challenge. And that was always like one of their favorite parts beyond just the robot part, really. The innovation project was one of their favorite parts. But for the league they’re at right now when they’re doing this level of robotics, there is no innovation project. There’s no real world kind of presentation or innovation kind of component. So when Doctor Barbi brought this to the community, it was like, hey, you know what? I have this CoastWise plan. We’re going to be using spectrometry. We’re going to be looking at the Everglades and the wetlands. And we want to understand if we can utilize this tool to actually do something in the real world. I knew that the kids would be interested in that. Right. It’s something that has an impact in the real world, right? That they get to work alongside experts, you know, getting to work alongside you and Dr. Barbi and people that have, you know, real knowledge I think is invaluable to students to get to kind of work alongside real engineers and real scientists, to kind of see their thought process, just learn from them, like how they grow, how they work through problems, I think is invaluable. And then, you know, also the impact of being able to have the potential of doing something that truly has an effect on the wetlands, I think is an incredible experience. Right. Like, who wouldn’t want a student to be part of it?

00:14:36:13 – 00:14:44:04 Michael P. Taylor: Did working with STELLA lead you and the students to discover various NASA data sources and stuff you didn’t know about before? And what did you find?

00:14:44:05 – 00:17:24:05 Tara Merino: Yes. Like, I think, mostly, you know, I’ll have to give credit to Craig Phillips, who really dove in to the NASA applications and pointed out to me and to others who were interested in this, that there’s some phenomenal data sources. We went up and visited a professor at USF, who has access to all the, you know, the direct satellite data and some high resolution satellite data. And Craig pointed out the benefits of space. You know, he, Craig was the type of scientist who, you know, who kept getting ahead of everybody. And instead of keeping pace, he was out at the next level already. Unfortunately, Craig and his wife moved back to Colorado. They’re not much. It’s hard to get them involved. Hopefully we’ll get them involved remotely as time goes on.

So one of the things that we tried to do was show how you could use Google Earth and get the aerial images and look at the changes to the vegetation over time, and pointed out the similarity with Landsat and the PACE which is the ocean satellite, essentially, is extremely interesting to us. The reason we couldn’t use more of the data itself is that it’s pretty complicated, very large to deal with and so forth. So for our first course, which was just four days long, we pointed out the similarity between what NASA’s done with Landsat and what we’re trying to do.

And this year, I think we’re actually going to achieve a drone flying possibly of STELLA itself, but certainly the nature that Bianca Cilento has done where in her case, I believe Mike, she had a spectroscopic drone and then sort of matched up the STELLA 18 channel information with the three channel spectroscopic drone so that they could say, this spectrum from the drone gives us this spectrum from STELLA. So now we can look in more detail and do false color imaging. And I think false color imaging is an interesting concept for young students as well.

00:17:24:08 – 00:18:24:03 Nick Barbi: So this year, we’re fortunate enough, if all goes well, to have a student who, for his science project, designed the control system for drone hardware and software. Have a student that might be able to, you know, help be a not only a student, but be an instructor in some sense. And then if we had our own control system, we have more options to modify it and link the flight of the drone with the collection of the spectrum and so forth. And the goal is to get more involved in and directly relating our work to NASA’s database and you guys. It just needs more than four days to really delve into that.

00:18:24:04 – 00:21:31:02 Michael P. Taylor: Yeah, yeah. So my question was did working with STELLA introduce you and the students to NASA’s broader work in Earth science beyond just rockets? And did it change how students viewed NASA’s work?

00:21:31:03 – 00:22:22:02 Tara Merino: Yeah. I think, you know, when I first brought this to the students that I spoke to, you know, the first year we predominantly did the robotics team, and then the second year we went to some school students as well that I know were engaged in STEM because we had a bit more time. The common answer back was, doesn’t NASA just do like rocket ships? Like what is this? And like, what do they do? And I think, you know, just learning that there’s so much more to what NASA does and that they actually work on instruments and that they’re doing educational things and they engage with the students and they’re doing research. I think was eye opening for the students. Right. But I agree with Dr. Barbi then that like then saying you’re going to get to work with a NASA instrument immediately was exciting to the students are like, oh, we’re going to work with something that NASA made, like, we’re working with something that’s, you know, really, really must be like forward looking.

00:22:22:03 – 00:23:10:12 Nick Barbi: And now they’re engaged like, oh, what else does NASA do, right? That kind of like created a spark to like is there other things that NASA works on and like what other kind of research programs do they do? You know, so I think that was kind of like a lynch pin for them to kind of start looking at that NASA does more than just rocket ships.

00:23:10:13 – 00:24:28:13 Tara Merino: You can get students engaged. I have found that students, especially younger students, have such creative minds. And they think so outside the box that you really want them to be engaged in projects like this, that they can really look at problems in ways that we haven’t been taught yet. Like this is the process you follow to look at a problem. Students just kind of look at it however they want with their mind wide open. So I think engaging students in this and making it accessible to them with kind of a less expensive toolset then can help, maybe guide, you know, your overarching real modeling and things because you really do never know what can come out of a student’s mindset.

I know for us, several years ago, we were looking at space travel and, you know, the challenges that exist in space travel. And our students came up with this whole suit that had like resistant bands to kind of keep muscles engaged so that they wouldn’t lose bone density and all of that. And I think maybe like five years later, that was like a real product. Like now people actually use that for physical therapy and things. So but it’s just you know, it was incredible that ten year olds came up with that concept, like right off the bat within a couple hours or like, oh, this is, you know, these are the challenges and like, this is what we could do. So I think, you know, having youth and students engaged in real world challenges like this, they can look at it in a different way. And they might come up with ideas that, you know, some of us that have been doing this for many years wouldn’t come up with.

00:24:44:09 – 00:26:14:12 Nick Barbi: I was going to say something, Mike, if I’m still allowed a minute. Now, we don’t want to hear from you. Yeah. So. No, your comment was about linking it to the NASA data inspired me a little bit because we are talking about doing a freshman in college level course that would actually be, you know, a semester, trimester, whatever works out to be. And in that course, that’s where we could really spend a lot more time on that kind of association. It makes it a much higher level course. And be it, you know, we got the time to do it. So I think that that’s a perfect sort of vertical addition. You know, we want to do things laterally in this course across the different instrumentation that you’re doing or different applications of the same instrument, but also vertically above the, you know, the science behind it and the use of the data further beyond it. So hopefully that’s something we’re working on now and may come to fruition in a year or two, not sure. But thank you.

00:26:14:13 – 00:27:27:03 Michael P. Taylor: Yeah, so Michael, can you talk about the experience of assembling the STELLA and what challenges you ran into?

00:27:27:04 – 00:30:12:09 Nick Barbi: So we, initially we ordered the parts to do a build class, meaning we bring in, you know, 15 kids and 15 instruments, and we go through building it all at once. But when you do that, you’ve got, you know, you’ve got to be somewhat of a control freak, right? Because everybody’s got to be on the same page, doing the same thing at the same time, and the parts have to be laid out. And in this case, it was me and one other instructor, and we just didn’t get the job done. Kind of a classic mistake and not fully doing the build prior to the teaching exercise. So you know it has the trappings of looking very easy and yet there’s some experience level things that you need to gain. The other thing that caused us a problem was just ordering parts and finding out that they weren’t available and the notice that we had given ourselves. And because of that, we had to modify a part. We essentially had to build a part that came as an integrated unit into from two pieces. And that piece ended up not being of the proper dimension for the slot and the housing. So that caused the case not to close properly. And we didn’t realize it until we spent hours on it. And so it was not, I think the conclusion was it would be nice to have a little more room in there for those wires and also some suggestions about the placement of the buttons and that kind of thing. But by and large, the problem that we experienced while building was mostly of our own doing. And now we have, you know, we have a couple of. I will show you right here. I just got delivered new Q2 units. But, yeah. So, you know, we even though we understand it was needed to be, you know, the design goal was to be small. We didn’t think it had to be quite as small as it was and that we could have used a little more leeway with the wires.

00:31:48:12 – 00:33:29:12 Nick Barbi: Although the problem was not itself the wires. The problem was in the oversized component that we had a rig up from because the part wasn’t available directly. So on time later, they all came in, but they didn’t come in on time. We then had the students do failure analysis and the whole thing. And a couple of students, including Tara’s daughter, Natalie, and Colton, who was the exceptional young man, the two of them together, really led the failure analysis and came up with some great suggestions, some of which were solving a problem that didn’t exist, as I said. But nevertheless, we didn’t know that at the time. But the exercise of going through that and then listening to Paul explain why things were done a certain way, why he didn’t think, you know, recommendations were necessary in some cases, but also why he thought they were very good recommendations in other cases. That was a great moment for us.

00:33:29:13 – 00:33:41:03 Michael P. Taylor: Yeah. In fact, he sent you all a failure analysis report. Yes. He did. Right. And so it was there for that.

00:33:41:04 – 00:35:47:03 Tara Merino: And I do recall him, like, you know, stopping the students and really having them explain what they meant and why and all that, that it was, yeah. Not only the students, but the instructors as well. And I think that’s also a very good experience for students, right? To be questioned and have to kind of give their logic and reasoning for what they thought or what they presented and areas of improvement that they see. And then how do you defend why they think a certain thing, or why they felt a certain way about something. So I think, you know, that can be hard for a student and even as an adult. So I think, you know, that no matter what those sort of opportunities are really educational and valuable to students. And then I think, you know, as engineers and as mentors to hear from students is also allowing us to help them better their skill set. So I think the students learned a lot. I hope, you know, I think Paul also hopefully took some takeaways from it. You know, I don’t think, you know, I know there were some things that were necessarily actually wrong or complicated with it or a challenge. And it was something else, like the chip we bought or something. But I think, you know, hopefully there was some other value in what they presented. But I think any time you’re having a student engage with a real professional and you’re connecting them, I think there’s a lot of growth. I think being able to struggle, and I agree with Doctor Barbi, sometimes the challenges or the problems or the struggles are much bigger learning opportunities than successes. So I think, you know, for them, you know, CoastWise and STELLA provides them an opportunity to utilize a tool in a way that gives them information and experiences they wouldn’t have.

00:36:11:10 – 00:36:51:07 Tara Merino: I think then being able to work alongside real scientists and folks that built the instrument, or people that use the instrument, and hearing how they use it, connects them to real world experiences and gives them an understanding of like how they could use, you know, what their careers could be like someday, and if that would be interesting to them. And I think overall, it gives them a breadth of exposure to things that they may never have known to consider in their careers. I feel like a lot of times students are like, okay, I want to be a lawyer or I want to be a doctor, or I want to be an engineer, because those are things that they see all the time in movies or they hear about.

00:36:51:08 – 00:39:29:07 Michael P. Taylor: What surprised you about the connections between this local project and NASA’s broader Earth science work?

00:39:29:08 – 00:42:30:14 Nick Barbi: I think that, you know, it elevated the importance of what we’re doing to say that NASA on a much larger scale is doing this, doing it at a much more scientific level, a worldwide level. And zillions of applications of it, depending upon which area of the world people are interested in. And so it gave it a substantially stronger rationale and credibility in terms of what we’re trying to do. I think one of the really interesting things was the NDVI, the normalized difference vegetative index. And this is a way to compare the vegetation from year to year or month to month or season to season. And the concept that this is done on NASA satellites, that this is common practice, I think is extremely interesting. And the fact that the waterkeeper is very interested in the changes of sea grass density, especially in the aftermath of all the, you know, the red tide and all the other things that have polluted the, the sea grass area. And so we can do a relatively small version, mini version of the same kind of thing. So yeah, I think all of this lent credibility from what we’re doing on a small scale to what the waterkeeper’s doing on a much larger regional scale and what NASA’s doing on a worldwide scale.

00:42:30:15 – 00:44:08:04 Michael P. Taylor: For Michael, could you walk us through what it was like collecting data from plants, from actual plants? And could you tell different plants apart from their light signatures? Did anything surprise you? And what were your takeaways from that?

00:44:08:05 – 00:46:29:03 Michael Melvin Merino: The data collection portion was actually very simple and very straightforward. We set up multiple plants outside, and we did a series of measurements on each plant. So it wasn’t just one measurement per plant. It was a couple. And then we imported that data into, I think it might have been Excel. And then we, you know, graphed it, organized it, looked at it, looked through trends. It definitely gave me a lot more insight into how data collection is actually done. Before then, I had really only collected data like with like single variable like experiments, not with something that had this many components to it that we had to account for, like the sunlight, which is one that I didn’t remember until you mentioned it. Like the position of the sunlight changes obviously over time. And like that, that’s not something that I’m used to accounting for. Like working with that many variables was definitely something that was new to me. And although it didn’t, like STELLA itself didn’t change the direction of mechanical engineering that I wanted to go into, it definitely gave me a lot more insight into like how the collection of data might actually happen in my field, rather than just like, you know, oh, we’re going to run this tiny little experiment. It might be like, okay, we’re going to run this experiment. Here’s all the variables we have to take into consideration. And I think using, you know, having gone through the STELLA program, although it was short, gave me a little more insight into how that process and data collection, collection and analysis might actually work.

00:46:29:04 – 00:48:53:00 Tara Merino: Yeah. I mean, I think that COASTWISE allowed them to connect with technology and terminology that they never would have had. Right, terms they never would have had. They got to program in a way that’s very different. Right? So, right now they only program for hardware, so they only do hardware programming. They don’t do any programming over a data set to like kind of analyze data that was something that they had never done before. A lot of them had never looked at a data set that needed to be normalized before. I think understanding kind of how they would have to present information and how they could utilize information and also like how data can be manipulated to kind of not maybe necessarily always give the truth was also something that was unique to them through CoastWise. So I think those were all very unique skills that they didn’t have exposure to before and without going through the CoastWise program with STELLA, they wouldn’t have had access to. Just to show, again, I wanted to mention the Fab Lab that was so generous and crucial to our pulling the first couple of years off. And then here is Natalie, Michael’s sister, and there’s Michael.

00:48:53:01 – 00:55:32:02 Nick Barbi: So I wanted to show some results of our spectra from the black mangrove, the red mangrove and the white mangrove. Now, these were all obviously saplings, but we knew exactly what they were, and we could get, you know, color wise, they’re all very similar. Here we can see the spectra that we were getting from these. And here’s the wavelength axis from 400 to 1000 nanometers, reflectance. And then these were the areas of some differentiation that I pointed out on the spectra that clearly allowed us to differentiate, you know, one spectrum from another. And there are plenty of regions that give us differentiation. And then here’s the color bar where the black is infrared and the rest is as shown here. So I think this seemed to be consistent. Consistency is always an issue. But I think it’s very interesting that the green color was very common.

And these were done one, two, three. So that was not a lot of there was no time difference. The sun was at the same angle. Essentially throughout the whole thing we used the white card and so there’s clearly differences between this, especially when you look at the infrared here, but also just in the colors. I mean, the spectrometer pointed out some very different levels of color amounts of blue and green and orange and so forth that it was hard to see by the eye. And then here we have seven plants that we looked at. And I’m going to jump to just looking at the five green plants. I took out, if you see here, I threw in a couple of ringers because I knew they were going to be quite different in the visible light spectrum because their color is different. And so these were the five green plants, and then these were the two that I threw in to make sure we got some differences.

And so the, if you go to the five plants, you can see that there’s, these are all normalized at an orange color. And so all these plants, all these spectra were made to be equal at 580 nanometers. And then you can see there’s ratio differences that can be, if consistent, can be used to distinguish one plant from another. Now, here’s a situation between two groups where we looked at the group called Viper and the group called Crocs. And we saw the green box here, which is below. And these spectra between the two groups were very similar. Remarkably so. Maybe, this one, they’re all three very, very good. So this is the bougainvillea, the jasmine and the Persian shield and so two different groups, two different spectrometers being used. And then the blue box up here was pretty good, pretty good match from one group to another. And then finally the Heliconia was really not so good of a match where we would have to do a lot more data collection. So, but of the group we looked at, we had some pretty good consistency. And this will end up being the true test as to how consistent we’ll be able to get. So is the deviation from time to time, group to group, in the system greater than the inherent deviation of the spectrum? If it is, then we’re in trouble. If not, then we’re in good shape. So this is part of the research aspect of what we’re trying to do.

00:55:32:03 – 00:56:29:10 Tara Merino: Yeah. I mean, I think if we’re going to expand it to more areas, there needs to be sort of like a curriculum guide. And I don’t know if that exists, but something that allows someone maybe that doesn’t have a Doctor Barbi, that’s utilized this sort of technology before that’s going to be able to explain it. Right. So if you’re going to want somebody else like a me to be able to run a course like this or like a fab lab to be able to run and utilize STELLA, there needs to be some sort of instruction set that says like, okay, you know, day one, this is what you want to do. Day two, this is what you want to do. Day three and maybe there’s multiple variations of that. And depending on the duration that you’re going to work with the technology with, so that would be like what I would suggest if we want to expand. Right. There just needs to be some sort of high level explanation and instruction so that you can make it accessible to people that don’t have a Dr. Barbi that has experience with instruments like this.

00:56:29:11 – 01:04:16:02 Michael P. Taylor: What do you want to tell parents or educators about programs like this?

01:04:16:03 – 01:10:35:05 Nick Barbi: And the way to do that is to make sure there are opportunities. And so we want to build the technical community, the technical strength of the community, make it a place where technical families and their companies can feel comfortable locating. Start ups can locate. One of the best things we can do in my position is to have opportunities for their kids and opportunities that can be modeled nationwide and worldwide. So if we can say that a program that is now worldwide began in Sarasota and Manatee counties in Florida, that would make people aware of the things that we’re doing. So that’s what it does for the area. It would do that, you know, we can’t, we’re not going to change much of the political spectrum or the funding spectrum or we’re not going to do much of that. But if we can make it a known place for starting really advanced STEM education programs for kids that get national and international recognition. To me, that is a phenomenal contribution.

01:05:47:15 – 01:05:53:15 Michael P. Taylor: Finally, any closing thoughts about where do you want to take this program and why people should support it?

01:05:54:03 – 01:08:46:15 Nick Barbi: You know, one of the things we’re doing next month is we’re having some kids that, you know, one of the, besides CoastWise, a very big program we do is send kids to Italy for three weeks at an AI session at, you know, Fondazione Bruno Kessler, which is in Trento, Italy. And they pay 100% of the fees once kids get to Italy. So what we do and what the parents do now is the parents have to have the money to send a kid. The airfare. And so we would like to open this up more for other kids that may not be able to buy the airfare, whose family may not be able to send them over, even though it doesn’t cost them anything when they get over there. Airfare is not cheap. So we are trying to say that we give a technical experience that kids can’t get anywhere else. It helps the career opportunities decision by opening up, you know, if kids have a bent toward science but never heard of instruments, never heard of spectroscopy, don’t know anything about data analysis. At grades, you know, at say rising freshman level where they’re just going from eighth grade to freshman. This is the time really to hit those kids with look at these opportunities.

So it will help the standard of living, as I say, draw more people into the community that have, that are tech aware people and are worried about their kids education. And then we have this international tie which is an experience that opens up all new kinds of opportunities for kids. They meet friends from not only Italy, but from, you know, there’s many countries represented in this program. So next year we’re going to be able to send 6 or 7 kids to this program. We’ve been upgraded because of the level of kids that we’ve been able to send. But we want to expand that international collaboration. And we want Italian kids to come here, and we want more of our kids to go to Italy and all of this, you know, builds the community, builds opportunities for kids, brings in families that are concerned about that. And so we can make kids aware of the environmental issues of the affected development.

01:08:46:16 – 01:10:35:05 Nick Barbi: So they can make their own decisions. And this is our CoastWise program about whether development is a good thing or whether it’s nonsense. They can look at images, they can compare images before and after. They can see mangroves decreasing in volume or changing in normalized difference vegetative index. And then we could expand this to water quality, agricultural analysis, sustainable farming, air quality to a lesser extent. We’re fortunate enough not to have severe air quality issues here because of the ocean and the breezes and all that kind of thing. So, but the things that care about the community, it teaches the kids not only science, but more about the environment in which they live and how what the real difference between an organically grown product and an organic soil versus non organic and help them understand the choices that they make throughout life. So, you know, the the launches are done and so forth can be, Jacksonville is pretty industrial area, but, you know, we’re noted for our beauty. And so environment becomes a big issue. But we want to also have tech companies, new companies, start ups or relocations of companies here. And we have to show them that there’s some amazing informal STEM education programs and maybe other education programs, not so necessarily STEM oriented, entrepreneurial things, which we’re looking into, an entrepreneurial fair, for example. And so this is to make the area a more prime location for the tech families and tech companies to locate.

01:10:35:06 – 01:12:15:00 Michael P. Taylor: Yeah. Thank you so much. You’ve been great. I’m really pleased and happy you guys were able to join us today. Thank you. Well, again you know any time we’re going to get to interact with, you know, real experts and hear feedback I’m going to sign my kids up for that. Yeah. Even after surgery. Yeah I didn’t get up there. Well, they’ll see it. And that was that was an emergency like we did. I didn’t know that that was going to happen until Monday, so I didn’t actually sign him up like knowing that that was going to be the case.

01:12:15:00 – 01:13:19:01 Tara Merino: Thank you so much, Mike, for all that you do and engaging with students in your time. I mean, it really has been an amazing opportunity. I look forward to seeing what comes out of it this summer. But, I know, you know, not just Michael, but all the students, they really, really enjoyed the summer. They really enjoyed being able to speak to you and to Paul. I know that as Doctor Barbi said, he didn’t really just say that. Like it really was the highlight. They all talked about it for weeks about how they got to talk to NASA. They thought it was the coolest thing. So, you know, I definitely, you know, I appreciate you guys taking the time, making it a memorable experience for them. You know, listening to them and taking their feedback, making them feel part of, you know, a process, making them feel part of a solution and part of, you know, impacting something that’s beyond themselves. I think that was a really inspiring moment for them. So, so thank you for that. And Dr. Barbi, you know, always, you know, thank you for making all the opportunities for our students and the community. You know, it’s awesome to work with you.

Nick Barbi: Yeah. Well thank you. And, great. Back at you, Tara. Thank you very much.

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University of Toledo Students to Launch NASA-Inspired Satellite to Monitor Lake Erie Algal Blooms

Michael Taylor — Sun, 01 Feb 2026 15:03:08 +0000

University of Toledo Students to Launch NASA-Inspired Satellite to Monitor Lake Erie Algal Blooms

TOLEDO, OH — University of Toledo graduate and undergraduate students who are part of the Mission EARTH NASA Science Activation funded project, in collaboration with three high schools, are preparing to launch a satellite into space as part of the Dream Big Project, an initiative funded through Near Space Launch and the Don Wood Foundation. The project represents a significant workforce development effort, bridging classroom learning with hands-on space technology experience while preparing the next generation of Earth science and engineering professionals.

The project, led by Dr. Kevin Czajkowski and project manager Dr. Olawale Oluwafemi, brings together students from the University of Toledo’s Department of Geography and Planning with students and educators from Toledo Technology Academy, Crestwood High School, and Stockbridge High School. The team designed and built satellite instrumentation inspired by NASA’s Science and Technology Education for Land/Life Assessment (STELLA) platform to collect environmental data on harmful algal blooms in Lake Erie and map urban heat islands in the Toledo area.

From Classroom to Space: Workforce Development in Action

The project originated when Near Space Launch invited the University of Toledo to participate as one of six universities in phase one of the Dream Big Project. Dr. Czajkowski, who first encountered Near Space Education through Stockbridge High School students at the American Geophysical Union (AGU) conference, had previously worked with the organization in 2023, when his Digital Image Analysis class built and launched a cubesat on a high-altitude balloon.

UToledo students (left to right) Yusuf Tayo, Olawale Oluwafemi, Md. Faisal Karim, Hossain Idrish, Stephen Yankyera preparing to launch a high-altitude balloon in front of 300 K-6 students from Defiance Elementary School, Defiance, OH, to test their ThinSat - April 2, 2025.

Md. Faisal Karim and Olawale Oluwafemi working on the UToledo payload while Dillon Embry and Alex Reno or Near Space Launch check the signal from the sensors.

The UToledo payload, without the sensors attached, being checked for size to fit into the ThinSat.

Dillon Embry and Alex Reno of Near Space Launch, Upland, IN

Utoledo students Elizabeth Blakely-White and Yusuf Tayo holding the high altitude balloon during setup.

“When Near Space Launch got a grant to do the Dream Big project, they reached out to me to see if UToledo would want to participate,” Dr. Czajkowski explained. “I said yes.”

The year-long project exemplifies modern workforce development by engaging students at multiple educational levels in authentic scientific research and engineering design. University students worked alongside high school teams, with educators serving as team leads and Dr. Czajkowski providing overall supervision.

The University of Toledo team includes: Kali Whitaker, Olawale Oluwafemi (project manager), Md. Faisal Karim (PCB and instrumentation design lead), Elizabeth White, Bethany Boehler, Kazi Kabir, Stephen Yankera, Yusuf Tayo, Cody Graves, Hossain Idrish, Derek Chambers, Pramila Paudyal, Dhananji Karunarathna, Hema Nimmagadda, and Eve Corlett.

High school participation included students from Toledo Technology Academy (teacher Laura Kubiak with students Kei Frey, Alex Marino, Jackson Huise, and Logan Oster), Crestwood High School (teacher Diana Johns with students Hala Komaiha, Noor El Fadl, Maryan Farhat, and Mohammed Ali AlSabeh), and Stockbridge High School (teacher Robert Richards with students Brock Rochow, Jack Hammerberg, and Timothy Handshoe).

“The students did the majority of the coding and designing,” noted the project team, emphasizing the hands-on learning that builds workforce skills in science, technology, engineering, and mathematics (STEM) fields.

Why STELLA?

The team selected STELLA as the foundation for their satellite design due to its straightforward approach and comprehensive documentation—qualities that make it ideal for workforce development and educational applications. “The students were coming up with designs that required a spectrometer and thermal sensor. They wanted to observe the impact of the Normalized Difference Vegetation Index (NDVI) on temperature,” Dr. Czajkowski said. “It was straightforward for me to suggest that they pattern their design after STELLA. There’s no sense in reinventing the wheel.”

STELLA instruments, developed by NASA scientists and engineers in collaboration with university researchers, combine inexpensive sensors with user-friendly software and 3D-printable housings to produce lightweight, handheld instruments. The STELLA components for a given instrument retail for approximately $200, and instrument weight ranges from 33 to 450 grams depending on configuration.‎᠎‎‌᠎‎᠎‎‌ All files and instructions for instrument construction and for data acquisition, and programmings are freely available online at https://science.gsfc.nasa.gov/stella/

Elizabeth Blakely-White noted that the step-by-step procedures and graphical explanations on the STELLA website, particularly the schematic diagrams of pin connections, made the platform accessible for students without extensive engineering backgrounds—a crucial factor for workforce development initiatives that seek to broaden participation in STEM fields.

“It was briefly mentioned in a support meeting and our team did more research following,” Blakely-White explained. Dr. Czajkowski added, “I’ve known of STELLA for a long time. I have one in my office that I use with my classes. I first saw it at AGU.”
STELLA instruments measure light spectra over 18 channels in the visible and near-infrared range from 410 to 940 nanometers.‎᠎‎‌᠎‎᠎‎‌ The instruments’ small size, affordability, and ease of assembly make them ideal for scientific and educational applications where deployment across many users is important. Some STELLA instruments can be built without any tools at all, by connecting components with inexpensive, commercially available cables.‎᠎‎‌᠎‎᠎‎‌

The team modified the original STELLA design by creating a custom printed circuit board (PCB) and connecting sensors to an Adafruit Feather microcontroller. Engineering student Md. Faisal Karim led the PCB and instrumentation design work, demonstrating the type of specialized technical skills that are increasingly valued in the aerospace workforce.

Scientific Goals and NASA Mission Connections

The primary scientific objectives focus on environmental monitoring around Lake Erie and the Toledo region. “We are hoping to get information on the harmful algal blooms on Lake Erie,” Oluwafemi stated. “We are also interested in mapping the Urban Heat Island around the Toledo area, and other climatic parameters that our spectrometer was able to capture.”

Spectral Alignment with Landsat

STELLA’s spectroscopic sensor wavelength bands overlap with the spectral coverage provided by sensors on Landsat. Specifically, the sensor bands in STELLA spectrometers at 535, 560, and 585 nanometers fall within the Landsat Operational Land Imager (OLI) instrument’s band 3 (Green, 525–600 nm), while the STELLA sensor bands at 645 and 680 nanometers correspond to Landsat OLI band 4 (Red, 630–680 nm). Similarly, STELLA’s 860 nanometer sensor band aligns with Landsat OLI band 5 (Near-Infrared, 845–885 nm).‎᠎‎‌᠎‎᠎‎‌ The spectral alignment between the Landsat and STELLA instruments allows for comparison of measurements within overlapping wavelength bands across different spatial and temporal scales.‎᠎‎‌᠎‎᠎‎‌

While STELLA instruments provide valuable educational and research opportunities, the high-precision, high-accuracy instruments in the NASA Earth Observing fleet cannot be duplicated with inexpensive, off-the-shelf components.‎᠎‎‌᠎‎᠎‎‌ The spectral overlap between STELLA and Landsat instruments allows for comparison of measurements of different accuracy and precision across spatial and temporal scales.‎᠎‎‌᠎‎᠎‎‌ Validation tests for STELLA instruments are currently under way.

Validation with NASA Earth Observation Data

The team plans to validate their satellite measurements using data from NASA’s Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission. ECOSTRESS acquires high-resolution temperature images of Earth’s surface and has now acquired over 600,000 scenes since completing its In Orbit Checkout phase. The mission measures plant water stress by detecting temperature changes and supports applications including agricultural water management, wildfire mapping, and urban heat monitoring—making it particularly relevant for the team’s goals of studying algal blooms and urban heat islands around Lake Erie and Toledo.

The team may also cross-reference their observations with Landsat satellite imagery. The Landsat program, a joint effort between NASA and the U.S. Geological Survey (USGS), provides continuous measurements of Earth’s land surface with data spanning more than 50 years at 30-meter pixel resolution. Landsat data serves diverse communities including agriculture, fire management, forestry, and water quality management—including algal bloom detection in lakes like Erie.

Additionally, Sentinel-2 imagery from the European Space Agency‘s Copernicus program provides high-resolution multispectral data with frequent revisit times, valuable for monitoring rapidly changing environmental conditions like algal blooms.

Challenges and Lessons Learned: Building Problem-Solving Skills

The year-long project presented several technical challenges that provided valuable workforce development experiences in troubleshooting and adaptive problem-solving. “We had some trouble getting the instruments to work with the emulator. But, we learned that artificial intelligence (AI) could figure out what was wrong,” Oluwafemi noted, highlighting how students gained experience with emerging technologies that are transforming the engineering workforce.
One significant obstacle emerged late in the development process when communication gaps created design challenges. “Near Space was not able to share a physical version of the satellite bus while the teams were designing their payloads,” Oluwafemi explained.

“Therefore, we were going off of schematics on how to make our payload. However, we made a mistake in reading it so we had to hurry and redesign our payload and then pay quite a bit to get it fixed.” This experience taught students valuable lessons about the importance of clear technical communication and documentation in collaborative engineering projects—skills essential for professional success. Near Space has acknowledged that providing the physical bus earlier would have been beneficial to the teams.

Despite these challenges, the team successfully completed their satellite, which has been delivered and awaits launch no earlier than the end of March.

Preparing the Next Generation

Dr. Czajkowski reflected on the educational and workforce development value of the project: “I was hoping to have my Geography students design and build a satellite that was launched into space. The students really have to work hard to figure out how to do this.”
The Dream Big Project represents a collaboration between NASA Science Activation, Near Space Launch, and educational institutions, providing hands-on space technology experience to both university and high school students. By exposing students to authentic research challenges, advanced instrumentation based on NASA missions, and professional collaboration structures, the project builds a pipeline of skilled workers prepared for careers in Earth science, aerospace engineering, environmental monitoring, and related fields.

This workforce development approach—connecting classroom learning with real-world applications, engaging students across educational levels, and providing mentorship from experienced researchers—exemplifies best practices for building the diverse, technically skilled workforce that NASA and the broader aerospace industry need for future missions and Earth science applications. Low-cost, low-complexity instruments make hands-on science and engineering available to researchers, educators, and students with limited budgets, expanding the pool of potential scientists to include a wider range of demographics than possible with limited numbers of expensive instruments.

As the University of Toledo team awaits their launch and prepares to collect data on Lake Erie’s environmental conditions, they are not only contributing to scientific knowledge—they are building the skills, confidence, and professional networks that will define their future careers in STEM fields.

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Students Build AI-Powered Drone for Earth Observation | NASA SEES Internship Journey

Michael Taylor — Fri, 30 Jan 2026 04:32:29 +0000

Students Build AI-Powered Drone for Earth Observation | NASA SEES Internship

Video Summary

In this interview, four high school students from the 2025 NASA SEES (STEM Enhancement in Earth Science) internship program discuss EarthLens, an innovative drone-based system they developed to complement satellite Earth observations with high-resolution ground data. Samuel Bawden, Nandini Khaneja, Neev Tamboli, and Jordan Rodriguez share their journey from classroom learners to hands-on innovators, demonstrating the power of experiential STEM education in workforce development.

Project Origins and Technical Design

EarthLens emerged from the students’ experience using GLOBE Observer to compare ground-truth land cover data with satellite datasets from Landsat and Sentinel. Recognizing the challenges of manual data collection and the vast difference in spatial scales between ground and satellite observations, the team designed a drone platform that bridges this gap. Their system integrates STELLA-Q2 and Helio-STELLA spectrometers for measuring surface and atmospheric properties, RGB cameras, a Raspberry Pi-based data system, and a preliminary AI classification tool for real-time land cover analysis. The goal is to make Earth science data collection more accessible for citizen scientists, educators, researchers, and agricultural applications.

Learning Through Hands-On Experience

The students candidly discuss their learning journey, emphasizing that none of them began with significant remote sensing or drone-building experience. Through hands-on problem-solving, mentorship from University of Toledo graduate students, and self-directed learning, they assembled the drone from accessible components, integrated unfamiliar technologies like Raspberry Pi systems and flight controllers, and developed software solutions. Their discussion of comparing satellite and ground observations provides authentic insight into how students build conceptual understanding of remote sensing principles through real-world experience. The team emphasizes that their work complements satellite missions, filling an important niche in spatial resolution and data validation.

Future Directions and Impact

Looking forward, the students plan to create build guides for others to replicate their system, integrate additional environmental sensors, and refine both hardware and software components. They envision applications in agricultural monitoring, environmental research, and education, where the system could provide detailed observations at scales between satellites and ground measurements. Each team member reflects on how the project influenced their career goals in engineering and Earth science, demonstrating that high school students can develop meaningful tools for real-world environmental challenges. Presented at the American Geophysical Union conference, EarthLens exemplifies how project-based learning and mentorship cultivate the next generation of Earth science professionals while students continue building their foundational knowledge in remote sensing and related fields.

Transcript

Introduction & Team Members

I’m here with the, NASA SEES group that I met at AGU. Working on the EarthLens project.

And I’ll save that for you to tell us all about what EarthLens, is and what you did and all that.

But, with, that being said, I’m going to ask you to, introduce yourself.

Where you’re from again, just the city is fine. And your role in the EarthLens project.

Okay. And I’m just going to go in order from how I see it in my screen over here, from right to left.

Okay. And so first up, I have Sam. Yeah. Hi.

I’m Sam Bodman from Washington, DC area.

I’m, going to Dartmouth next year. I’m going to be a freshman there. And my main responsibilities

with the Within the EarthLens team was, essentially doing,

a lot of the background research for essentially identifying the problem we were seeking to solve, which was improving,

citizen science tools for land cover. So we were interns, in a program this past summer,

which I’m sure we’ll talk about. And a lot of the tools we used were challenging and give great data.

And so kind of assessing what those challenges were and then how to solve them with EarthLens was kind of

where I came in then next up I have Neeve. Yeah. So I’m Neeve, from the Bay Area in California,

about like 20 minutes out of San Francisco. And, my main role within the EarthLens project was

sort of, helping design and plan out the drone as well as designing

how our entire system would kind of be integrated with the computational part. next up, I have Nandini.

Hi, I’m Nandini, I’m from Long Island, New York. My role on the EarthLens team was, was, hardware lead.

So I did the physical construction of the drone and the STELLA integration. And we’ll be continuing to work on various iterations of the drone.

And last but not least, Jordan. Hi. My name is Jordan Rodriguez, and I’m from Westlake, Texas.

And, on the EarthLens project, I focused on software and data architecture. My role involves designing how observation data,

is captured, from the drone and transmitted to the actual app.

NASA SEES Program & Project Origins

first off, I want to understand what NASA SEES is and how, you know, folks from all across the country,

you got to get together and work on the project. So can you tell me just a little bit more about NASA’s SEES

and, and how that happened? Sure. I love to take that question. So NASA SEES

is, really was a gift of a program. I think for a lot of us, they do,

all kinds of programing for high school, students interested in engineering and earth and space sciences

and physics and, so students from all over the country, every corner.

You know, this group is representative of that, but not in the least, limited to how many places people came from,

including, you know, territories like Puerto Rico and things like that. People from all over the country,

got together and worked on a lot of really cool projects. Or specifically was about,

essentially assessing the agreement between ground truth land cover data and satellite derived land cover data.

But there were groups who worked on designing future missions to moons of Jupiter

and Saturn or other really, you know, just crazy cool things like that. And so I think it was a really awesome way to get introduced,

to, you know, kind of what careers in Stem look like. And I think I speak for everybody when I say

it really encouraged us to pursue this kind of work in the future.

What is Earth Lens?

Awesome. Awesome. That’s fantastic. And, so we’ve touched on a bit of what EarthLens is, but,

could I bother, one of you to, tell me exactly what EarthLens is? What did you do for the project?

You know, sort of just, the in broad, definition, a broad scope of what the project is.

Yeah, I could take this one. So, I think from a very basic quick perspective, EarthLens,

we came across the idea once we realized how, a lot of times, inaccurate

and inefficient data collection of land cover was with the existing technology

because it relied mostly on, like, manual or just simply very far off inaccurate satellite satellite data.

And we wanted to change this by making it a more accurate and be more reliable, because one of our friends, Jordan, over here, I think he lost

over 200 images that he took over like ten plus hours. And we also had the data that a lot of the pictures

that we had taken, as part of our internship, they were I believe, less than one megapixel in resolution.

So we wanted to see how we could improve that. And we came up with the idea that a drone could address

both of these problems, because a, a drone is kind of like a happy medium between the very inaccurate high up satellites

and the having to go on your feet with your phone manual like, NASA GLOBE.

And with our computational parts, we can also make sure that the data can be stored very safely, and we’re not going to be losing it.

Okay. And so you said inaccurate, satellites. What do you mean by that?

So I think very briefly, one of as Sam mentioned, our internships goals

was to see the difference between, the land cover

that we can see on the ground and what satellites are, showing them to be on the main NASA data sets.

And I think we can probably pull this up later sometime, but we had these large charts that we made that compared these different, strips of data.

And we were able to see that the, the data that the satellite gave about the land,

specifically stuff like spectral resolutions and what was exactly being covered by that land was often inaccurate.

And it would be inaccurate in the way that, let’s say, it would classify something that’s grass as trees that were nearby wouldn’t be accurate

enough to see that, hey, this is a patch of grass over here in the midst of a forest.

Sometimes even, like, you know, shadows that would be picked up, it just wouldn’t give any information.

Or maybe it might even say was like water because of the darkness. It compared with other, water bodies to those, shadows.

Yeah.

Coming Together

tell me how this whole process, sort of came together and how you all started working and collaborating together.

Sure. So the NASA SEES internship program as a whole is open to high school juniors and seniors from across the country.

So we had had the ability to select teams we were interested in, and we ended up getting sorted into those as we got accepted into the program.

So we were part of a 50 person team called Earth System Explorers that met virtually over two months. June to July 2025.

We had a variety of mentors, including rusty, Peter and all the scientists who, you know, and since our main goal was to compare land cover data that we recorded

using the GLOBE, the GLOBE Observer application in our own community, and comparing that to data existing in ArcGIS

and manual, data that we’ve classified in Collect Earth Online.

We, a lot of groups were deciding what to do with that data that we had generated throughout the internship,

since we had like 37 different points within a three kilometer grid in our own communities. So a lot of people wanted to analyze the data that they had generated.

But we took a closer look at our, data quality itself. And then once we saw what a big issue that data quality was and how Jordan lost

such a significant number of the photos that he had taken, we realized that GLOBE Observer had been a very valuable, tool for the time that we were using it.

But it had, you know, there were challenges that were beginning to surface, especially since it hadn’t been

updated as frequently. And we thought we wanted to combine the benefit of the bird’s eye view that a satellite gives with the increased granularity

you would get just going by, manually taking the photos. So we wanted to, take a more unconventional hardware

based approach to doing this. And it was definitely a challenge because we’re all across the country.

So, it was a group decision to go all in on this one leading up to AGU.

Combining Hardware & Citizen Science

what interested you all about combining drones, remote sensing and citizen science all together into one package?

the technologies that have become accessible to, you know, the average person have, improved greatly.

I think, you know, these STELLA sensors and the ability to build a drone in your garage and access to AI tools is something that’s new.

And so why not take a new approach to, land observation, Earth observation.

Yeah, that hits the nail on the head. So for me, I just, we remember how initially we,

I think when we were working with our working group to see what we could take the project further with.

We definitely wanted to keep citizen science in mind, because that was kind of the core value that was ingrained with NASA GLOBE

and, you know, working after the NASA SEES project where we were so deeply engrained with land cover

and wanting to revolutionize that sort of sector, we decided that we had like a few different options.

And I remember Jordan had this great computational idea. And Nandini brought to, a hardware based idea where we had,

like, instruments like STELLA and then we looked at each other and we were like, wait a minute. We can kind of combine both of these to make like an intelligent hardware

based system that uses this type of instrumentation to solve the problems that we need to.

Building the Drone – Hardware Development

what was your experience with, like, say, drone technology, remote sensing and or the, STELLA instruments themselves?

Sure. I’d like to talk about that from from, like, a hardware perspective. I had never built a, never built a drone before.

I actually, my, mechanical engineering related experience, even before the internship program, I had done a research project,

working on a martian simulation chamber in my basement with a friend of mine. And that, you know, made me very familiar with that low cost optimizing,

being responsible for basically every type of engineering in one project kind of experience.

So from there, I, we were able to, I researched how, I guess these kinds of drones have been built in the past.

I visited my local hobby store to learn how to mount the motors. Right. And, you know, try to use online resources and my own community

to try to make this hardware as accurate as possible. And for example, we were we ourselves were not familiar with STELLA tools beforehand.

And I personally also had never used a spectrometer board. Actually, we started using STELLA because it gave us a place to start

exploring this. The first step, the very first step we took hardware wise, was ordering every part

that is required for the Helio-STELLA and the STELLA-Q2 designs. Attaching the circuitry, making sure it worked

on the SparkFun boards that it’s designed for. And then once I realized we needed to integrate that

into a Raspberry Pi system to record that microSD card and be part of the transferring to Jordan’s app system,

we were able to slowly strip away components like the real time clock didn’t need to be needed anymore.

The, of course it’s slipping my mind right now, but there’s displays, there’s much, many components we were able to eliminate

to make it to a more barebones style model that hopefully any, lab worker or hobbyist could build in their basement for a,

reasonable sum of money. Yeah, I think the cool part of it is none of us came in

with any significant experience directly related to this. And I think in, in a, in a cool way,

that’s an advantage on the citizen science end of things. Because if we can make something that is intuitive,

then it can be widely used. Yeah. And just focusing on like even though we were so inexperienced

with hardware like this, I think one of the beauties of science and in specific here with STELLA was that there’s like this community

around people that know what they’re doing. And for example, we were able to reach out to grad students all the way out in Ohio, and they were able to help us

because they were like STELLA experts, and we were able to use their help. And that kind of brought us forward to a stage where we wouldn’t

have been able to without them. Oh yeah. And of course, of course. It all ties back to you know, the, the SEES program giving us

this opportunity to explore what we probably wouldn’t have otherwise known,

if it wasn’t actually for the SEES program.

Graduate Student Mentorship & Support

Rusty connected us, with two graduate students at the University of Toledo, who go by Femi and Feisal,

who, they work under a professor that she knew very closely. And they were both very helpful in two different ways.

So for example, Faisal was able to help verify, our technical planning,

while Femi was very helpful in making sure that we knew the, just generally how to plan a project like this, because it’s

such a big undertaking and especially considering we’re for high schoolers, trying to figure it out because, I mean, in a way,

we are the citizen scientists trying to put together this kind of a system. So I think having so much support on that side from,

not just the scientists that we directly worked with in the SEES program, but scientists, we were able to be connected to, during the design process and even after.

Technical Challenges – Raspberry Pi & Flight Systems

were there any other, like, major components of the EarthLens systems that you developed, that you didn’t previously mentioned?

I think, you know, the we did a lot of work,

specifically with how to fly the drone. With Nandini, you can talk more about it, but essentially,

you know, you want it to be, clean user interface, and you don’t want it to be, you know, clunky controls

where you have to type an input for the for the drone drone to go up or down. And so there was a lot of tinkering we had to do on that.

And Nandini you want to talk about that, that’s cool. And it one that feeds right into the next question, which would be like and I figured to go right into there,

what was the sort of, most challenging technical problem you had to solve? And how did you approach it?

So I got to say, it’s like, I think it’s the combination of all the little problems that came in along the way.

Like, for example, we’re using this Raspberry Pi based system. We haven’t used Raspberry Pi’s in the past, past all my experiences

with Arduinos. So I think understanding the Raspberry Pi itself was going to be like a mini computer and required its own monitor

and keyboard, and that kind of stuff was not something I expected. So we ended up working around that so I could run it from

my own computer connected to a hotspot on my phone. So that it can be done literally anywhere, because this was because

we had to do early stages before it gets fully connected to just an app. So like that’s one of the challenges that came in the way our flight controller,

for example, they come in with preloaded software sometimes. And, you know, these things are usually designed

for like the first person view racing drones. And it was definitely hard to see how big of a how big a propeller,

what kind of flight navigation hardware, what kind of, GPS system is required for an actual observation drone.

So we had to take risks like deleting the software already on that, on that flight controller,

like $140 flight controller, and hoping that I downloaded the, the GPS navigation appropriate software.

INAV correctly instead. So I think it was just the combination of, you know, we can very clearly plan

this out and go, okay, step A, step B you know, these are going to be all the steps that we’re going to take.

But there are so many little not necessarily detours but little bumps in the way that I guess

you become more familiar with once you or a small group is responsible for the entirety of a project like that at this scale.

So I think that was definitely the biggest thing to get used to.

Dual Spectrometer System

So yeah. And you were integrating the STELLA-Q2 and the Helio-STELLA spectrometers into your platform.

And you also hinted of this, but, what did you learn from that process and why did you do it?

So the reason I think we chose those two in particular was that we we noticed that the GLOBE Observer app was not just land cover.

It also had a cloud cover function too, even though we ourselves had used it. So by we already planned to have a camera facing down and a camera facing up,

which that’s kind of being worked on still, with the multiplexer,

but so we wanted something that was going to measure the upward and downward, both because you wanted to have something, you know, comparing it to.

So it’s not just one data source. So like for example, like I have the actual thing here too.

We designed it using the same cables in the STELLA system. I don’t know if the blur will let you see it. So that we have the triad spectrometer used in the Q2 going down

and giving us more channels and more and more information or data like we would need for that land cover observation.

While we would have, I believe, 8 or 9 channels something, something a smaller number of channels

in the Helio-STELLA one and those two combined. Well, because we were able to do that,

like the daisy chaining of storage with the quick cables. So I through the STELLA system, I learned how to even do that,

because if I just looked at the spectrometer board alone before that, I would be asking myself, where’s the ground?

You know, where’s the ground? Where’s the power? Just working and very like, simple. Like the normal DuPont wire setup.

So I think, especially that STELLA the the guides for STELA online

help me see how intuitive the connection, especially between these two specific ones, would be and how valuable they’d be for implementation.

Yeah, and it’s not just how intuitive the actual hardware is, but also just the data that it spits out.

So like for our initial tests, like using the spectrometers and photos,

we were literally able to create charts of our of our first data collections by just copy and pasting values

from the output into a Google spreadsheet, Google, Google Sheets spreadsheet. So it’s not so, so STELLA.

The STELLA devices, you know, they served our purpose really well of wanting to get, you know, all of the data about light and air

and not just the ground and not just the sky, but how the lighting, essentially mixes with the irradiance between those,

two sources, interact with each other. But also just how easy it is to get the data from the STELLA hardware

to, a format where we can interpret it.

Uncertainty, Data Processing & AI Classification

so you used basically the Helio-STELLA to help normalize the data you were getting from the surface reflectance and all that.

Okay. So sort of instantaneous reflectance. So you just bypassed, the whole irradiance problem itself.

I’m sure you have quite a bit of uncertainty with those, because those are not the most sophisticated sensors ever.

Are you taking a look into those, into the uncertainties as well? So, yeah, there there was a certain amount

of normalization we had to do, for example, the, the, the, the wavelengths that each, of light

that each of the two spectrometers collect are not exactly the same.

They’re only off by a little bit, which means in a graph, you know, we can we can, pretty accurately compare them.

But there is that small contingency you have to deal with. And then, you know, like you said, it’s we’re not working with,

you know, massive, you know, super accurate spectrometers. So it really is the other thing that we’re working on with

the drone is how we can collect the maximum amount of metadata, how high we are, how fast or moving

temperature, time date and all of those things

combined to kind of account for anything that might not make sense. And so you get a much better picture by using the other aspect,

the other pieces of data that the drone itself collects to get a better picture of what the STELLA spectrometers are seeing as well.

Yeah. And one of our like, further works that we’ve planned out as well is kind of integrating an AI model into our Sis system.

And what this could do is make use of all of that metadata, as well as the raw spectral data

that we have to kind of eliminate as much as possible those uncertainties.

The Software Application – Real-Time Insights

can you tell me what was involved in developing the AI classification system?

Yeah. So I can go ahead and, take a lead on that. So when it comes to the AI classification,

we’re kind of talking more about the software side, right? So, we’re going through the route of making the app.

So EarthLens, is going to be an app, that works with the sensors and cameras to look at land in real time.

Basically, it’ll take the information like the vegetation, soil and water, and then it will use AI to give you, like, the insights right away.

So, when we were using the GLOBE Observer, we had to, use like these little scales and we had to kind of like guesstimate.

What percentage of the photo was, let’s say water tree or shadow or grass and whatnot.

So instead of waiting to process all that data later, you can see it right when happens.

Right. So, I really wanted it to be easy to use, so you don’t have to, like, be a scientist or an engineer to understand what’s going on.

Of course, that’s kind of the main point of citizen science. Yeah. So it’s meant to work in different places, too, whenever it’s,

farmland or wetlands or even urban areas so that the app can adapt, to different environments.

The coolest part is seeing the data, like, actually turn into something useful, right? So I’ve learned a lot about how the softwares and the sensors

and the AI can work together. Of course, it’s still in the development. Preliminary stages, right. Because it’s not super easy to do that.

But, also figuring out, what’s realistic for a tool like this and what it can actually do.

And what’s better to simplify it, right. So it’s been a fun challenge to make something that’s powerful, but, also very useful for citizen science.

Yeah. And, you know, developing an AI tool is, you know, it’s more doable than ever,

but it really is, kind of a space that AI hasn’t,

fully impacted, I think, in the way that it could. And so, you know, all all of the challenges that come along

with training a model, validating data to train it on, is is, you know, one of the probably one of the biggest challenges,

one that having to face, throughout the course of this project. But we think it’s very much worth it for the end goal.

So that’s one of the things that we’re excited to work on in the future. Yeah. And while we’re on the topic of both challenges and AI, I think

which is really important to note that one of our main goals was to also keep the whole thing really affordable.

And that means making sure that all the computational power that it would take is kept to as little as possible.

So we have to sort of balance how heavy of an AI model we can use without having to make sure that,

oh, there has to be like a big fat computer onboard the drone or something.

NASA Mission Data Comparisons

what particular say NASA missions would you be comparing the data to? If you’re or are you comparing the data to, if any?

I believe right now, in our adopt a pixel, in the adopt a pixel methodology

like chart that we’ve been using so far in this internship. I think we compare Landsat and Sentinel data

specifically to, what we’ve observed in GLOBE. And I remember in our poster, we proposed adding an additional column

with the, with the photos from down, another one for the up photo, and then like a bunch for those graphs individually.

So it could be seen as like an expansion to the currently existing, like comparisons that are being done to Landsat and Sentinel data.

So, so far I was going to say I completely agree that we we had a few conversations

with people at the AGU conference that brought up, similar topics about,

kind of thinking about how EarthLens itself could expand to slightly more than just land cover, observations.

And I think that integrates nicely, comparing a lot of different,

sources of satellite data. And also it sounds like STELLA has a few,

a few more really cool tools that we could work with.

Division of Labor & Team Roles

can you tell me directly, how did you divide responsibilities among your team members, and what was your specific contribution?

So you can go, one at a time, if you don’t mind. And, Sam, sincerity like on screen. Or at least you’re in my widest view here.

I can go ahead and start with yourself, if you don’t mind. Yeah. So, before CES, before this project,

I, really can’t say I’ve had that. I had that much technical experience.

Experience? I’ve learned a lot throughout this project. I do have, some pretty significant experience

working with the Smithsonian and the communication of science.

And so, a lot of what I contributed to this on, on this project was,

kind of a how to, talk about how we are kind

of converting from GLOBE to what we think could be a better system. And then also

kind of trying to optimize for citizen science is sometimes, you know, when you have these grand ideas for projects, it’s easy to let them,

slip away from you or become much bigger or more expensive than you really have the capacity for, than what’s even intended.

And so I have found a lot of joy and, helping to kind of

stay on track towards a citizen science goal. I think in terms of division of labor,

like we were talking about earlier, I definitely had, limited technical experience.

Nandini has had, a good amount, but none of us have had an exorbitant amount of technical experience.

And so we kind of just fell where our interest lied. And, you know, we’re,

you know, it’s a small team, so everybody gets a bit of a little bit of everything anyway, but,

you know, we we all have our unique passions and I’ve worked hard to integrate those into the project overall.

Fantastic. Neeve. Yeah. So, as Sam mentioned, like, I was kind of,

going into that little bit of everything type of flavor. So I personally have experience with both

the hardware and mechanical engineering as well as software and specifically and how like both of them can be integrated.

So I helped sort of design and plan how and what the drone could do,

as well as how we would integrate that with some specific systems

that our AI and software models could use to make sure that the entire system

solves the problems that we want to, while making sure that everything’s reliable and affordable.

Fantastic. Nandini Yeah. So,

I definitely agree with Sam, and you’ve talked about how we kind of did go where our interests, lay in the very beginning.

We started our working group is actually about ten person group. And, the very first thing that I had to do

so that we could get some progress in deciding what projects we would do was, you know, introduce ourselves and introduce what we like to do in a technical standpoint.

So we had a little Google document with a list of all that and all the ideas. And that’s kind of how we split which people went to do our friends,

which people went to do a different AI based project and that kind of stuff. I would say in terms of vision and division of labor,

I always liked the hands on building component the most. I, I mean, I was I’m grateful my parents have allowed me

to take over my half my basement and, build, I guess whatever I need.

I used to do a lot more art down there, but I end up switching it into more of a little basement lab setup. So,

and, you know, I want to go into mechanical engineering. The physical hands on stuff is, what, my favorite part of it.

So that’s why I decided to build the drone itself. And, also, like, I have familiarity with being up at

like 2 or 3 in the morning and saying, guys, this thing’s finally work. So I’m sure Sam, Jordan and Neev remember the, every so often, like a 1

or 2 minute video of like, demonstrating something, working in that kind of stuff. So I mean, I feel like it, I felt what would be the highlights of my day,

I’m very happy to hear that it’s it’s so. Yeah. Fantastic.

And then Jordan. Yeah. So, so before EarthLens. Right. And I also have to say Nandini. Yes.

I did love watching those videos. But, before working on EarthLens, you know, I also didn’t have much

hands on experience with a project at this caliber. So I know I had done some programing and,

but of course, again, it wasnever at the extent that we did it with this project with EarthLens.

Right. So, specifically my role in EarthLens was really focused on the application itself.

So, I worked in designing how the app processes data from the sensors in the cameras and, you know, turns it into real time insights.

About land cover, of course, going back to things like vegetation and, soil and water, we also tested a lot of troubleshooting

to make sure the system was reliable and, accurate. So, yeah, I have to say,

I think the thing we’re most proud of was how we all grew in the process. So, from almost no experience to a project

that caught a lot of attention at that, conference. Right. And it taught us, you know, how to build

from nothing to making such, we took a big stride, I have to say.

Building on a Mature Program

What do you think GLOBE added to the project? I’d honestly say without GLOBE there is no project because that’s what really gave us

the foundation of what already exists and what we want to improve upon. And from that introductory sense, I think GLOBE is phenomenal.

And what it does, it’s a very accessible technology, and what it means to do is to get that scientists,

if like they get citizen scientists activated and mobilized in a way to give our actual professional scientists the data that they need.

And what we just saw was the opportunity to make that whole system better and more optimized.

And that is in no way is they saying that GLOBE is not doing what it was meant to do.

Yeah. And I also have to say, you know, science is in science without problems, right? So of course, using the GLOBE, it was a really strong introduction

to remote sensing. I personally had no idea what remote sensing was.

And then we, of course, we got into the SEES program. We got accepted into the Earth systems explorers.

And they taught us about, you know, the GLOBE app. And working working with the GLOBE app taught us, you know, to collect consistent and accurate data.

And of course, speaking from my experience, doing all that data aggregation and all that, it took close to eight hours in total.

And then I took all my photos and I was praying that they all, you know, saved to the database.

It was 216 photos I took. I lost 202 with the GLOBE Observer app.

But of course, it again, it is phenomenal at what it does. But it was just a little bit of a misstep.

Gotcha. Yeah, yeah. And it it showed, you know, it got your hands dirty.

You had to go out and do the field work and you had to do the ground truthing. And it was a, it was a

messy process of how to, you know, compare what you’re seeing versus what sensors orbiting the Earth are telling you.

And it’s great. You know, highlighting that friction.

We just think, you know, there the there’s a system that could improve upon what GLOBE has already been able

to do for citizen scientists that we can pursue.

Skills Development & Teamwork

are there any other skills that you would like to mention that you developed through the project that you haven’t already mentioned?

I’d say personally, for me, one of the main soft skills that we were able to build was definitely like working with a team.

I think this was a big emphasis that our mentors at the SEES internship had given us, and they given us resources

like their one team building module and how to do research in teams. And I feel like

it was definitely really important for us being spread out all across the country. But the fact that we were still able to be so productive and have that sort of bond

in that connection between us to make sure that we were all on the same page. You know, those videos that I was sending, like, that’s the type of stuff

that makes us all know what’s going on and be, like, happy with what’s going on and make sure that we’re all communicating perfectly.

Yeah. And I’d say also the skills to take what’s happening internally

in our team and be able to communicate that externally. So from, you know,

Nandini building the drone and Jordan building the app. And so collaborating on,

you know, how to quantify, results from the, the research we did with GLOBE and comparing what the drone gives us.

Like that’s all the technical stuff that that goes on inside. And then being able to

put that all down on a poster in an abstract or in a paper and put that out into the world for people to get an idea of what we’re working on

is it’s it’s a lot of abstraction. And that is a skill that we’ve definitely developed through this project.

Agricultural Applications

how do you see EarthLens being used, say, for agricultural monitoring or environmental research?

How would you like to see it use as well? I mean, I would say the way I envision EarthLens,

especially in these earlier stages right now, is, we plan to put together, I’ve started drafting this, a guide similar to the inspired by the STELLA

Guide of components of how to build each, one of these drone systems and all that kind of stuff.

I mean, now, since each year we’ve started communicating more with researchers across the country who have expressed interest in it,

and we hope by getting it into a larger audience like that, continuing that integration with STELLA, we could have it be something

that a hobbyist or classroom, or that kind of stuff. People could actually start building these and using them in their own

communities, kind of like, kind of like how we use GLOBE. But I think the benefit of it being a drone is that as we adapt it,

to be able to fly higher and have a bigger field of view, it’ll be useful for maybe if there needs to be a weekly observation

of certain fields or agricultural areas, like you were saying with the coasts earlier and that kind of stuff.

I think it could be useful. Starting from this research perspective and continuing

from seeing like environmental stability and things like that. So, yeah, yeah, just

just to add to that, you know, you hit on the agricultural piece a bit, but the the sheer advances in technology that have,

occurred in agriculture over the last few decades are amazing. And it’s what allows us to feed, you know, the,

the modern population of the Earth and a growing population of the Earth.

That’s really important. And technology is one of the main ways we’re going to be able to continue to do that.

The way I envision EarthLens kind of being able to do that is right now you have, you know, you can survey your land to to an extent

and you can use the satellite data that’s made available to farmers to, you know, inform

the parts of land that tractors go over to fertilize or the different seeds that are planted on different portions of land.

And those are all based on satellite data as it is now. And, you know, in the research we did in the seed

program, comparing ground data to satellite derived data, we saw that there are inaccuracies in that seasonal inaccuracies,

spatial inaccuracy, inaccuracies, temporal inaccuracies. And if you have if you have something like EarthLens that’s small,

that’s modular, that’s easily deployable, that’s personalized and easy to use. But that still turns out quality data.

More immediately, you can, you know, imagine a farmer launching a few EarthLens drones and having them fly over their field

like Nandini said once or twice a week and get maybe even a more detailed image of their land than they would for modern satellite, data.

And so there’s a I really like this question about how to use EarthLens or similar technologies in agriculture.

building off of that, have you, played around with any vegetation indices since you’ve been, doing, or at least thinking about,

like, plants and agriculture and land use and all that? We’re not fully there yet.

Right now for this first iteration. Right now. I mean, right now we’re working on more mechanical challenges. Like, for example, a big thing is that the light bulb battery

for example, to power this is pretty heavy. It’s pretty heavy. And it’s time. And, right now, our maximum estimated flight time,

I’ve been working towards is probably about 20 to 30 minutes a piece right now. Now, we ought to work towards extending that or making

that battery system more interchangeable. And then in that next level we would integrate, though still, like the air quality systems and things like that.

Thankfully, our flight controller gives us things like accelerometer and, you know, other specific motion and gyroscopic related data.

But I think as we keep adding on different layers, we’re going to start, you know, maybe seeing if we can train it like, as Jordan,

you were saying earlier in the AI standpoint towards data sets with healthier or non healthier vegetation,

knowing what to flag in an image and that kind of stuff. Yeah. And I have to say, I also I really like the question

when you touch based on the, agricultural side. So I am from the Rio Grande Valley and, Texas, and it’s a region

where agriculture plays a very important role, of course, not just to the economy, but to the community as a whole.

So I’ve seen firsthand how much farmers rely on knowledge of the land, you know, the weather, the crop cycle to make, these decisions every day.

And that’s, of course, where we see EarthLens making that difference, because it can collect data from sensors

and, you know, cameras and processes, as, Sam had explained. So you know, coming from the region so connected to agriculture,

EarthLens has been exciting, of course, because it can, really improve this, agri agriculture that we have here in the Valley.

Comparing with NASA Satellite Data

Are you inspired by any of the, different, NASA missions and Earth science that you’ve, you know, sort of, probed at?

And then which ones have you really taken a look at? Is it just Landsat or are there others out there as well?

And if you are doing Landsat, you know what? What might have inspired you with Landsat as well. So go ahead.

Yeah. So we’ve we’ve worked with quite a few different earth science projects, I think from the original data sets

we were comparing our ground truth data to, we were pulling from Landsat. We were pulling from,

a few different data sets, with Dynamic World and, yes, array and world cover and,

a few different tree canopy data sets.

And then we also, you know, again, worked with Landsat time series data, which was cool to interact with.

I for me personally, I wouldn’t say there’s one specific, Earth science project, that I’ve been,

you know, singularly inspired, but inspired by the we did hear from one of the main engineers who’s working on the NISAR mission,

which is a very newly launched telescope that uses some really cool technologies to get information you never seen before.

But I think in, in when you take them all together and you get, you know,

a more complete image of Earth systems and science on Earth, that’s kind of the part that truly, has inspired me.

You know, the goal of NASA to continue that kind of research, I personally feel is, is very valuable.

And so that’s kind of what’s inspired me throughout all of this. for it. Now the only thing right now least existing, the only thing we’re

comparing our global observer data to is that kind of Landsat and Sentinel data. And as things continue to change, I mean, having satellites that are is in the hand

of, labs on their own or hobbyists and that kind of stuff. Still being able to contribute some to some sort of shared thing,

maybe like an ArcGIS layer or something like that gives us, you know, another thing to verify against.

And I think that’s, definitely a motivating factor to keep using that

in conjunction with the satellites while we, you know, while we can and, allowing that to be a technology that continues to evolve

alongside it. what would you like to develop further if you could continue this project?

Future Developments

And do you have plans to. Yeah. So I’d say, on top of, like, that whole AI and automatic classification goals

that we have where we wouldn’t have to manually classify each pixel of the data that our drone takes, the AI would take care of that.

On top of that, we also have an idea of perhaps adding intelligence to the flight patterns of the drone So in a way,

making it an automated flight, which would make the entire, system a lot more efficient and make it easier for people like average

Joe’s to be able to use the entire system. And I’d say as as EarthLens as a whole, like, scales up,

there’s a lot of potential for it to integrate with external platforms that already provide data sets and have this sort of connected

infrastructure, which would just make the data that EarthLens gets. And people using EarthLens have been taking and putting it out there

for a lot more people to use, and having a lot more eyes on that same data.

Yeah, I definitely think that’s a very great way to keep progressing it. And I think from the hardware perspective, I think, like I was saying before,

integrating that carbon dioxide centered, sensor and integrating some of the things that are being added in some of the new STELLA, variations

would be something that we plan on implementing back into drone and automating flight patterns is actually, the reason why we switched to that idea

of, flight software. So that’s the easiest way to go about that in the future. So I think it’s definitely, good that we’re starting to explore

these possibilities of what we’re going to do in the future now, so we can kind of make those steps as easy as possible, like starting

from where we are today. But we definitely all have plans to keep continuing this project, at least for the next couple of years and that kind of stuff, because now

we see how valuable a continually updating or continually improving, application or system like this can be. So

yeah. And then any, any kind of tapped on it but earlier.

But the end goal is the citizen science access and the whole point of making tools

available for average people to collect scientific data is to make that

data available to researchers who, you know, we’ll know what to do with it, know how to draw conclusions.

And so we hope so. Also continue work with EarthLens in terms of,

how to get that data out to researchers and how to allow users of EarthLens to make their data accessible.

The app is the main way we want to do that, but also we hope to maybe one day have enough data to make a meaningful,

geographic data layer on some other software like ArcGIS or something like that.

Experience Influencing Future Pathways

how does this experience influenced your career interests or academic plans? So, like I said

earlier, the, the SEES program, you know, it was my first real kind of technical and scientific experience.

And I definitely want to continue that,

I want to study engineering in college, and I think I’m going to try and continue with that. I’m planning on going to a school

that allows you to do a lot of interdisciplinary study. And, you know, being involved in EarthLens is also,

generating a lot more curiosity for me about Earth science and, kind of the associated

technologies and space that, help us conduct our science. So I’m really excited to,

continue in that sort of direction. Yeah. For me, I’d say the process of developing EarthLens

and the SEES internship as a whole, it’s kind of me, made me firm that I want to keep being like this sort of inventor.

I’d say the fact that we were able to design and create something that didn’t exist before and this like, completely our brainchild, is so cool.

And that kind of motivates me to keep on doing that sort of tinkering, that sort of problem solving.

And especially in this, like using this interdisciplinary nature, but making sure that we’re grounded in solving real world environmental issues.

Really beautiful. Yeah, I would say for me, it’s made me more solid in my decision to pursue mechanical engineering for my undergraduate degree.

But I because, you know, I’ve I’ve had such a wonderful time, integrating this building with so many different other aspects of it.

And, like Sam, I mean, I think it’s made me a much more interdisciplinary builder, considering my prior experience is more aerospace connected.

I think that exploring Earth science and more applications here, it’s made me more willing to explore,

all different things under NASA and scientific purview. And, I mean, I plan to continue studying, hopefully

in grad school, neither aerospace or nuclear engineering. And I feel that EarthLens and this experience in Earth science

has given me, the willingness to keep exploring in that regard,

you know, and keep seeing which type of engineering is close to me at that point. Yeah. So, I totally agree with what everyone else has said.

I am a junior, so I still have, you know, a year to think about, at least a year to think about it, but not a lot of time.

Right. But working on EarthLens, you know, through NASA SEES you know, really shaped my interest in what I do want to become and that is, aerospace engineer.

So before this, I hadn’t, of course, I have already said, I hadn’t had much experience with projects at this scale.

And, you know, SEES exposed me to that. You know, the real world engineering challenges such as, you know,

collecting aggregation and analyzing, complex environmental data, you know, designing systems to process that data efficiently, too.

And, making decisions based on the real insights. Right. So I think the experience also taught me how to approach problems method.

With the method. Right. So to adapt things that didn’t go as planned and to think critically about, you know, how technology,

can be applied to solve, big real world problems. Right? So, participating in SEES influenced my goal of going to UT as well.

UT Austin. It made me realize what, I want to be in an environment where I can work,

you know, with great ambitions, you know, impactful projects, and continuing to grow as a thinker and, of course, a problem

solver. what was the most rewarding aspect of working on this project?

Most Rewarding Aspects & Takeaways

You know, like, what do you hope people take away, from learning about EarthLens? And is there basically anything else about the project that you’d like to know?

So, some sort of combination of those three?

I think, you know, these have been pretty comprehensive questions. You talked a lot about what EarthLens is for and how we hope it gets used.

If, you know, if you if if, you know, God forbid, the projectnever gets finished

or if younever get your hands on an EarthLens drone.

The thing I would hope that people learning about it take away is just that, these things

don’t have to be, stagnant. The way we study Earth can evolve with technology.

And I think it should, because, you know, we have better ways to collect data,

better ways to interpret that data, better pipelines for that data and more data

and all of that in in together just means we get a better picture of our Earth.

How it’s changing. There’s a lot of ways that influences policy economics.

And, you know, just in general, we hope EarthLens gets people excited

about studying the Earth for change. Yeah, I’m 100% agree with that.

And I would say, I think a big thing that I guess anyone, especially maybe high schoolers or college students or people newer to these kinds of things, can,

I guess, learn, is that, I mean, we all came with relatively small amounts of experience in here and kind of used whatever we learned through this.

Internship program to formulate this kind of mission. And it felt it felt nice to kind of, I guess, like,

as you said, to be a group of, you know, inventors in this regard. And something we weren’t as familiar with.

So I think it hopefully should encourage to keep learning and I guess keep tinkering about this kind of stuff, considering, you know,

I mean, you can you can build a drone that can do these kinds of things in your own basement. You know, there’s there is more capability to do these kinds of things

outside of the traditional laboratory or, environment.

That’s typically seen for more professionals or more for adults. Yeah, I’d say personally for me, touching on like that

most rewarding part, I’d say some of the most rewarding, like emotions that I felt were when we were all on call

and we’d have like, we’d be throwing out different ideas and then as soon as we’d hear one, then we think of one that stuck.

It’d be so rewarding just to feel like, hey, you know, I can see this. I can envision this actually coming into existence.

And I’d say one of the beauties of like, the whole process of EarthLens in general

is that in a way, it has like endless possibilities, right? Like so far, how we’ve thought about it.

We have like a few different ideas that you can go into use here. You can go to use there.

But at the end of the day, we’re still high schoolers. And that’s one of the goals we have with reaching out to experts in the area

like Michael Taylor, like people at NASA, at like for over at different universities,

because they’re going to give us so many new insights about where we could take this, what we could add and how we could keep building.

And for me personally, right, I think the most rewarding experience of working on this project was,

seeing how we could develop, what we could develop can actually make a difference. And again, reiterating we’re all just high school students, right?

I mean, we made this project from scraps, right? So one thing that really excited me,

of course, was also the power of citizen science and how a tool like this project can let anyone contribute to,

you know, collecting data and understanding environmental data. So it’s amazing, I think, that this project could really connect

communities, you know, students and researchers across the country. In terms of goals for EarthLens, I really hope it continues to expand.

You know, I think we all really think we’re just gonna, you know, keep driving, right? Of course, we’re from all literally all four corners of the United States.

Right. So, sometimes there’s a little bit of a challenge in getting, communications,

but we work it out with our, with our, time zones and stuff like that. Right. But, I also wanted to take a moment to, thank NASA SEES right.

And of course, you, Michael Taylor, for allowing us to, present this project.

Yeah, it’s it’s been an amazing opportunity. You know, being part of that program was a huge learning experience.

And, it inspired all of us to keep exploring, right? Building and contributing to projects that, you know, have meaningful real

world applications.

From Orbit to Earth: Agricultural Workforce Development using Real-Time Spectrometry

Michael Taylor — Sat, 17 Jan 2026 14:51:21 +0000

From Orbit to Earth: Agricultural Workforce Development using Real-Time Spectrometry

Video Summary

At Garden City Community College in Kansas, Assistant Professor Elisa Mai integrated STELLA spectrometers into her Technology in Agriculture course during fall 2025. The partnership came together when Kansas State University recognized that the college’s newly developed Crop Production Technology program aligned well with NASA ACRES‘ goals. Mai’s program trains students who want to return to family farms or become agronomists, and the STELLA instruments provided a hands-on way to teach remote sensing and precision agriculture concepts. Students used STELLA-1.2 spectrometers alongside Landsat 8-9 satellite data, supplemented with soil data from web surveys and elevation data, to measure spectral differences between surfaces like concrete and grass, and healthy versus stressed vegetation. “Having the STELLAs there was cool because we were able to see at the moment what those wavelengths actually looked like,” Mai explained. The real-time visual display helped students understand wavelength changes that were previously abstract concepts when viewing satellite imagery alone. Students collected field data that the NASA ACRES team—including Jacob Orser, Mike Humber, and Allison Bredder—helped analyze, then completed projects visiting multiple field sites and presenting their findings.

“It made it easy to explain and I think it was cool for the students to see just from walking around and pointing the STELLA at the ground what was happening. I think it really made that part make more sense because when we were looking at satellite data, they’re like, oh, yeah, of course. These points that we’re looking at and we mapped are different. But being able to actually see the jump in those wavelengths was pretty useful.”

– Elisa Mai

Mai extended the technology’s reach by showcasing STELLA at a campus STEM fair, where she demonstrated spectral differences between bare dirt and plants for students and faculty from across the college. She kept explanations accessible, comparing the instrument’s readings to printed NDVI (Normalized Difference Vegetation Index) satellite imagery without overwhelming visitors with complex equations, recognizing that many attendees didn’t know satellites could monitor plant health. This approach helped introduce precision agriculture technology to potential students in a way that felt approachable rather than intimidating. The course introduced basic concepts like different types of light, how satellites are used in farming, and wavelength analysis, with students going out to fields to gather data and bring it back to the classroom for analysis.

For the next course iteration scheduled for spring 2027, Mai plans several improvements based on the first implementation. She wants to provide deeper technical instruction on how STELLA instruments actually function, as students used them successfully but didn’t fully understand the underlying technology. Mai also plans to expand field campaigns beyond measuring around campus—taking students to actual agricultural fields to compare good and bad crop sections so they can see real-world agricultural applications. While the first cohort kept instruction “very, very broad” due to time constraints and the novelty of the material, future students will get more sophisticated training in both the technical aspects of the instruments and their practical applications in diagnosing plant health and field conditions.

Transcript

So my name is Elisa mei.

I’m the assistant professor of crop production

technology at Garden City Community College.

And so, basically this last fall semester.

So this would have been fall of 2025.

We started a new class called technology in Agriculture.

And that class, basically

went over a lot of different types of technology and AG.

Everything from seed genetics to satellites and autosteer,

automatic road shut off on farming implements and all things like that.

And then when, K-State kind of brought

NASA Acres and Garden City Community College together,

they thought that we’d be able

to make a really good partnership, especially with my program being new

and being, the program, the crop production technology program.

Was recently developed, and it’s mostly just to train,

people who want to go back to the farm and also people who

maybe want to be an agronomist and basically diagnose plant health.

And so that was kind of the purpose of that program.

So K-State noticed that, what we were doing

would probably fit pretty well with what NASA Acres is trying to do also.

Using STELLA in the Field and at the STEM Fair

So over

last summer, so summer of 2025, we were able to talk about ways

we could include NASA Acres into that course.

And it fit very, very well.

So we were able to just bring it over directly into that.

And that’s where eventually the STELLAs got involved with that also.

So in the class, we talked about a lot of different things,

the different, types of light, how we see things.

Went over like the technology side, or the technical side, I guess.

I guess I should say of that.

Talked a lot about satellites, how we utilize those and farming,

how we could utilize those and went out

to fields, gathered data and everything like that.

And then the STELLAs we were able to kind of get a more hands

on, down to Earth approach looking at that light.

Previously, we had only looked at infrared light

and, all the different wavelengths using satellite data.

So having the STELLAs there, it was cool because we were able to see

at the moment what those wavelengths actually looked like.

And then we recorded some data, and then we’re able to take that back

to the classroom.

And look at the data we gathered from that.

I also

was able to take the Stella’s to a little,

stem fair that we had at the college.

It was just for, well, primarily for Garden City Community College students.

The community was open to the community, but we only had students attend,

and other faculty.

So other students and faculty came.

Saw how the STELLAs worked.

I compared bare dirt to actual plants so they were able to see the wavelengths.

And then I also printed off a, image of basically what we see

when we look at satellite data and those differences in NDVI.

So it was just super, super broad.

I, of course, didn’t go into like the equation and all of that,

because that gets a little much for someone who doesn’t even know

that we can use a satellite to look at a plant.

So, anyways, that’s pretty much what we did at the very end of the class.

The students did a project where they went to a bunch of different

sites, gathered data, looked at a field, and compared it all.

And so they then put that all into a presentation

showing what they found, anything that surprised them.

And that was pretty much the conclusion of that class.

That’s awesome.

And what version of so did you use again?

I think it was the 1.2 to

NASA Satellite Comparison

was there a particular satellite that you compared the data to?

We mostly use Landsat, mostly use Landsat and the others.

I’m trying to remember now.

I don’t think so.

NASA Acres helped a lot with gathering all that up.

But primarily when we did our projects, when it came to the data,

we were using Landsat, I think it was eight, nine

or however you look at that when you’re looking at the data.

It was kind of new to me.

I’ll admit.

So I’m still learning.

And that process of it all.

But then we took other data, like some soil data from soil web survey.

Elevation data.

And I’m not sure where the elevation data, what satellite that was coming from,

because it was already kind of old and gathered.

But that’s pretty much what we used.

The STELLA Experience

what was your experience with the staff?

I really liked the screen

that you could actually see the wavelengths,

because that way when we were, you know, moving from concrete to grass,

I mean, there was just a huge jump all of a sudden.

So it made it easy to explain.

And I think it was cool for the students to see just from walking around

and pointing the STELLA at the ground what was happening.

I think it really made that part make more sense,

because when we were looking at satellite data, they’re like,

oh yeah, of course, these points that we’re looking at and we mapped

are different, but being able to actually see

the jump in those wavelengths was pretty useful.

That was I didn’t explore much with them.

That was primarily what we did is just look at those differences.

And then NASA Acres pulled that data for us

and then analyzed it all so we didn’t have to go through

the whole entire spreadsheet.

So that was very nice.

Trying to think the only issue that we had was

sometimes it was a little it took a while to record the GPS point

and the point that we were looking at and get all that data to load

and record.

So we had a hang up sometimes there.

I’m not sure if that was user error, or what was going on.

So I also had

students trying to do it as well, so that definitely could have been a factor.

But that was our only hang up point.

And we got through it and we still got the points recorded.

So we just knew that we had to just stay in there for a minute,

let it fully do whatever it’s doing in there.

And before we moved on to a different location.

So the were there any, like, cosmetic,

things or issues you had with the stoves or anything like that?

And are there any improvements you would suggest

or things that you would like to see it do?

No, I don’t think so.

Everything seemed to work pretty well.

Once you figured out how to use the dial, it was pretty easy.

I did like that there wasn’t a ton of buttons.

Because then I didn’t have to worry about people pressing things they shouldn’t.

It was just very.

Turn the knob till you’re at the thing, press it in, don’t touch anything else.

So that was really, really good.

They were easy to point at stuff

once I explained, you know, exactly where everything was.

It was easy to work with.

They looked really cool.

And I took them to the Stem fair.

People were stopping in asking me, what is that?

Because, I mean, they they look pretty different.

So, I think that was helpful to.

I know it’s kind of a small detail in the grand scheme of things,

but it definitely helps with the interest in the equipment.

So, I really liked that.

Technical Challenges and Learning Curve

And then how was working with NASA Acres did they?

Were they good.

And who was, who was on the the team that was working with you from NASA Acres

too it was Jacob Orser.

Mike can’t remember Mike’s…

Humber? Yes.

And, yeah, I can never remember his last name.

And then.

Allison. Bredder. Yes.

So, okay, those three awesome people from Acres.

Yeah, yeah, they were great.

Cool.

And so they did, they

when they were there, when you were setting up, you know,

doing all these measurements and all that, did

they go through like some of the process and all that sort of stuff.

Like what was their steps that you all had to take,

before you all started like really taking the measurements and all.

So in the beginning, we looked at, you know,

what wavelengths are, what we can see, what we can’t see,

all of that when it came to the STELLAs we kept it very, very broad.

We didn’t have a ton of time to go into details,

in the future.

I mean, this was our first time running the class,

so I think there’s some areas that we can tweak.

I would like to talk a little bit more about what the STELLAs really are,

what they’re doing, help apply that more on the technical side

because they saw, you know, physically they use them,

but I don’t think they fully understood

exactly what they were doing when they were using them.

And I would say, I don’t really either entirely.

So, that’s definitely an improvement I want to make.

And I want to I think going forward,

all we did was we took them outside of our classroom.

So there was still some green grass out there.

So we were able to just compare, like the pavement to the green

grass, different areas of the grass.

In the future.

I want to do that, but then I also want to travel to a field

and compare good parts of the field to bad parts of the field,

so that way they can see the real comparison there.

So kind of an introduction.

Get used to it, use it once and then actually go out there and

do something with it.

Plans for the Future

Are there any questions that I didn’t ask that you would like me to ask

or anything like that?

That you can think of something you know, that you would like to,

you know, finish off with, you know, thoughts, whatever.

Yeah.

Overall, I’d say just all the support from NASA Acres

and with the STELLA it was really, really great.

The students really enjoyed having a much more hands

on approach to the, remote sensing,

because remote sensing is not much fun to look at from a PowerPoint perspective.

So getting to see a little bit of what’s actually happening was really great.

And I’m excited to improve improve the course for the future also.

NASA SEES Students Showcase EarthLens-STELLA Integration at AGU 2025

Michael Taylor — Sun, 04 Jan 2026 01:25:19 +0000

NASA SEES Students Showcase EarthLens
-STELLA Integration at AGU 2025

Advanced Drone Platform Combines Dual STELLA Insruments (Q2 Spectrometer & Helio) and AI Analysis for Enhanced Land Cover Monitoring

NASA STEM Enhancement in Earth Sciences (SEES) interns Nandini Khaneja, Neev Tamboli, Samuel Bawden, and Jordan Rodriguez, part of the SEES Earth System Explorers Team sponsored by NESEC and the Institute for Global Environmental Strategies presented their innovative EarthLens project at the American Geophysical Union (AGU) Fall Meeting 2025, demonstrating exceptional technical achievement in developing a drone-and-app system that addresses limitations in existing citizen science tools.

Student Innovation and Workforce Development

The EarthLens team exemplifies the caliber of innovation emerging from NASA’s SEES program, successfully integrating complex systems across drone engineering, spectral sensing, mobile app development, and AI analysis. Their ability to identify real-world problems in platforms like NASA’s GLOBE Observer app and develop sophisticated solutions showcases the high-level technical skills being developed through NASA’s workforce development initiatives.

Understanding Why NASA Maintains the Cutting Edge

Working with EarthLens provides firsthand experience with sensor limitations that highlight why NASA must stay at the very cutting edge of science, engineering, and technology. The system uses two STELLA spectrometers – an AS7341 8-channel (415-680 nm) and AS7265x 18-channel (410-940 nm) – that reveal measurement variability, calibration challenges, and atmospheric interference effects.

By confronting these uncertainties with accessible instruments, users develop appreciation for why NASA missions require years of development, extensive calibration protocols, and sophisticated technology. This hands-on experience demonstrates why precision satellite sensors like Landsat and PACE represent the pinnacle of remote sensing engineering and why NASA must continue pushing technological boundaries to maintain scientific leadership.

Technical Innovation and Problem Solving

EarthLens addresses significant challenges identified in current citizen science platforms. Research revealed that 63.2% of users took more than 9 hours to complete land cover observations using traditional GLOBE tools, often losing data or struggling with poor image quality. The team’s solution combines:

Drone platform with dual STELLA spectrometers for comprehensive spectral monitoring
High-resolution Raspberry Pi cameras (3280 x 2464 pixels)
Mobile app with real-time drone feeds, AI-powered land cover analysis, and social features
GPS-accurate data collection that prevents the data loss plaguing existing platforms

Building on Research Foundation

The project extends work by Russanne Low, Peder Nelson, Cassie Soeffing, Andrew Clark, and the SEES 2020 Mosquito Mappers Research Team, whose 2021 study demonstrated connecting ground observations with satellite imagery. EarthLens advances this framework through drone-based data collection that bridges the gap between citizen science and professional Earth observation.

Advancing Science and Technology Leadership

The system incorporates AI for automated land cover classification while enabling users to learn remote sensing principles used in NASA missions. Though STELLA and EarthLens aren’t peer-reviewed research instruments, they provide valuable experience with measurement challenges that drive NASA’s commitment to advancing calibration methods and developing more sophisticated technology.

EarthLens demonstrates how understanding sensor limitations motivates continuous advancement in Earth observation capabilities. NASA’s investment in precision-calibrated missions and cutting-edge engineering ensures American leadership in space-based science and technology, maintaining the nation’s competitive advantage in understanding our planet through the most advanced remote sensing systems ever developed.

References

Nandini Khaneja, Neev Tamboli, Jordan Rodriguez, et al. EarthLens: A Novel Drone-based Citizen Science Tool for Land Cover Observation and Analysis. ESS Open Archive . December 26, 2025.
DOI: 10.22541/essoar.176677108.80716415/v1

Low RD, Nelson PV, Soeffing C, Clark A and SEES 2020 Mosquito Mappers Research Team (2021) Adopt a Pixel 3 km: A Multiscale Data Set Linking Remotely Sensed Land Cover Imagery With Field Based Citizen Science Observation. Front. Clim. 3:658063. doi: 10.3389/fclim.2021.658063

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STELLA Paper Published on STELLA Technology’s Impact on Remote Sensing Access and Workforce Development

Michael Taylor — Wed, 17 Dec 2025 18:15:48 +0000

Paper Published on STELLA Technology’s Impact on Remote Sensing Access and Workforce Development

A new paper published in the American Geophysical Union (AGU) journal Perspectives of Earth and Space Scientists examining how low-cost, open-source instruments are expanding access to remote sensing science while supporting NASA’s Earth observation missions.

The paper, titled “Science and Technology Education for Land/Life Assessment (STELLA): Democratizing Remote Sensing Science With Low‐Cost Open‐Source Instruments for Research and Education,” documents how STELLA instruments are creating new opportunities for scientific engagement and workforce development.

Authors: Paul Mirel, Michael Taylor, William Jesse Barber, Petya Campbell, Bianca Cilento, Lynn M. Nichols, and Manuel Lerdau

Paul Mirel, the creator and lead engineer of STELLA at NASA Goddard Space Flight Center, developed these instruments to make remote sensing science accessible through commercially available components. The instruments cost under $200 and measure light spectra across visible and near-infrared wavelengths, demonstrating the same principles used by NASA satellite missions.

The paper documents implementations across multiple settings, showing how STELLA technology creates pathways for understanding NASA Earth science missions. Dr. Craig Kohn at Waterford Union High School has integrated STELLA into agricultural science curricula, where students analyze vegetation health using NDVI measurements to compare different farming practices. This work connects classroom learning to the same spectral analysis methods used by NASA’s Landsat program.

Michael Taylor from NASA Goddard Space Flight Center has led workshops demonstrating how STELLA instruments help people understand NASA’s Earth observation capabilities. The technology provides hands-on experience with remote sensing principles while developing technical skills applicable to Earth science careers.

The research shows that STELLA instruments enable scientific measurements at scales not practical with expensive professional equipment. By making remote sensing accessible to broader communities, the technology expands participation in scientific research while building understanding of NASA mission applications.

Karen Karker at SUNY Environmental Science and Forestry has used STELLA in outreach programs, engaging participants from elementary through high school ages in spectral analysis activities that demonstrate how sensors can detect light invisible to human eyes. Her work shows how STELLA creates early exposure to NASA Earth science concepts.

The paper documents how university students gain comprehensive research experience through STELLA projects, developing skills in electronics assembly, programming, data analysis, and scientific methodology. These experiences prepare students for careers supporting NASA missions and Earth science applications.

The study demonstrates that STELLA’s open-source design supports global implementation while building technical workforce capabilities aligned with NASA’s Earth observation objectives. The research shows how the technology creates pathways between community engagement and the technical skills needed for NASA mission support.

The publication provides evidence of how accessible instrumentation can simultaneously advance scientific capabilities and develop workforce expertise essential for NASA’s Earth science and space exploration programs. The research establishes STELLA as a model for community-based technology development that supports NASA’s strategic objectives while expanding access to remote sensing science.

The post STELLA Paper Published on STELLA Technology’s Impact on Remote Sensing Access and Workforce Development appeared first on STELLA.

STELLA at AGU 2025 MacGyver Session

Michael Taylor — Wed, 17 Dec 2025 12:59:50 +0000

STELLA at AGU 2025 MacGyver Session

Poster PDF (18 MB)

NASA’s Low-Cost, Open-Source Instruments Empowering Workforce Development and Community Science

Mike Taylor presented STELLA (Science and Technology Education for Land/Life Assessment) at the American Geophysical Union Fall Meeting 2025, showcasing NASA’s innovative approach to democratizing remote sensing technology. The poster demonstrated how NASA Goddard Space Flight Center scientists have created affordable (~$200) instruments that teach the same fundamental remote sensing principles used in advanced remote sensing satellites. Taylor’s presentation highlighted STELLA’s critical role in building America’s technical workforce while explicitly showing why continued investment in cutting-edge space technology remains essential for maintaining leadership in Earth observation and space exploration. Featured in the MacGyver Session, which celebrates novel, self-made, and improved sensor solutions that contribute to citizen and community science, the presentation illustrated how accessible instruments can inspire the next generation of space scientists and engineers while creating clear pathways to NASA’s future workforce.

Presentation Details:

Presenter: Mike Taylor
Session: SY31D – The MacGyver Session
Date & Time: Wednesday, December 17, 2025 | 8:30 AM – 12:00 PM CST
Location: New Orleans Ernest N. Morial Convention Center
Format: In-person poster presentation
Abstract ID: 1858474

The post STELLA at AGU 2025 MacGyver Session appeared first on STELLA.

Michael Taylor, Author at STELLA

There Will Be More of Us: Rachel Stagner on STELLA, ARSET & Growing a NASA Mission-Literate Workforce

There Will Be More of Us: Rachel Stagner on STELLA, ARSET & Growing a NASA Mission-Literate Workforce

About Rachel Stagner

STELLA in the Classroom

ARSET as a Starting Point

"There Will Be More of Us"

Resources

STELLA / ARSET Interview Transcript

SEGMENT 1 — Introduction & Background

SEGMENT 2 — CCRI Program, STELLA & Curriculum

SEGMENT 3 — STELLA Workshops & Growing the Community

SEGMENT 4 — Introducing STELLA to Students

SEGMENT 5 — How ARSET Prepares Students for STELLA

SEGMENT 6 — Student Responses & STELLA Engagement

SEGMENT 7 — Kenneth Leslie’s Summer STELLA Boot Camp

SEGMENT 8 — STELLA and ARSET as Complementary Tools

SEGMENT 9 — What Teachers Need to Feel Confident

SEGMENT 10 — Follow-Up PD & Cycling Teachers Back

SEGMENT 11 — Advice for Teachers New to STELLA or ARSET

SEGMENT 12 — Vision for the Future of STELLA & ARSET

STELLA-1.2 Official Launch: Earth Science Workforce Development

STELLA-1.2 Official Launch: Earth Science Workforce Development

Join the STELLA Community Forum! Let's Build, Share, and Innovate Together!

NASA Acres Supports STELLA Workshop at American University

NASA Acres Supports STELLA Workshop at American University

Related Resources:

Building Tomorrow’s Earth Science Workforce, One Spectrum at a Time

Building Tomorrow's Earth Science Workforce, One Spectrum at a Time

How NASA's STELLA Instrument is Multiplying Mission Impact Through Student Engagement​

The Participants

More Than Rocket Ships

A Mission Multiplier: Connecting Space and Ground

Workforce Development for a Earth Observation

Skills That Transfer Across NASA's Mission Spheres

Learning from Failure, Contributing to Progress

Multiplying NASA's Earth Science Impact

A Model for the Future

The Bottom Line

Transcript

COASTWISE Interview Transcript

Related Resources:

University of Toledo Students to Launch NASA-Inspired Satellite to Monitor Lake Erie Algal Blooms

University of Toledo Students to Launch NASA-Inspired Satellite to Monitor Lake Erie Algal Blooms

From Classroom to Space: Workforce Development in Action

Why STELLA?

Scientific Goals and NASA Mission Connections

Spectral Alignment with Landsat

Validation with NASA Earth Observation Data

Challenges and Lessons Learned: Building Problem-Solving Skills

Preparing the Next Generation

Related Resources:

Students Build AI-Powered Drone for Earth Observation | NASA SEES Internship Journey

Students Build AI-Powered Drone for Earth Observation | NASA SEES Internship

Video Summary

Project Origins and Technical Design

Learning Through Hands-On Experience

Future Directions and Impact

Transcript

Introduction & Team Members

NASA SEES Program & Project Origins

What is Earth Lens?

Coming Together

Combining Hardware & Citizen Science

Building the Drone – Hardware Development

Graduate Student Mentorship & Support

Technical Challenges – Raspberry Pi & Flight Systems

Dual Spectrometer System

Uncertainty, Data Processing & AI Classification

The Software Application – Real-Time Insights

NASA Mission Data Comparisons

Division of Labor & Team Roles

Building on a Mature Program

Skills Development & Teamwork

Agricultural Applications

Comparing with NASA Satellite Data

Future Developments

Experience Influencing Future Pathways

Most Rewarding Aspects & Takeaways

Related Links

STELLA-1.2 Official Launch:
Earth Science Workforce Development

How NASA's STELLA Instrument is Multiplying Mission Impact Through Student Engagement

NASA SEES Students Showcase EarthLens
-STELLA Integration at AGU 2025