Dr. Akash Ashapure (he/him/his)

Remote Sensing Scientist
Terrestrial Information Systems Laboratory (619)

What inspired you to pursue a career in aquatic remote sensing?

Inspired by the transformative power of data and technology, I embarked on a journey to harness satellite observations for aquatic ecosystem monitoring. Growing up in a small town in India, a scientific career seemed distant. However, my undergraduate studies in computer science ignited a fascination with data and its utility for understanding complex systems. This passion deepened during my master's program in Geoinformatics where I discovered the transformative potential of geospatial data and remote sensing.

My PhD at Purdue University initially focused on precision agriculture, using high-performance computing for high-throughput phenotyping. This experience opened my eyes to the scalability and power of satellite-based observations. I realized that these techniques could be applied to entire ecosystems, offering a broader impact.

Transitioning from land-based monitoring to aquatic ecosystems, I recognized the critical role of aquatic ecosystems in biodiversity and human survival. Water bodies are particularly vulnerable to pollution, climate change, and other human activities. Satellite data, with its vast coverage and ability to provide continuous, reliable observations, became an invaluable tool for monitoring these fragile systems on a global scale.

Satellite observations allow us to track changes in water quality, detect harmful algal blooms, and monitor sediment transport. This near real-time monitoring capability is crucial for preserving ecosystems and safeguarding human health. The vastness of coverage and reliability of data continue to motivate me, as I strive to use advanced tools to protect these vital Earth systems.

What is one research project that you are particularly excited about, and why?

Aquaverse, a machine learning-centered atmospheric correction framework for aquatic remote sensing, is a particularly exciting research project. As part of the Freshwater Sensing Program, we use satellite imagery to monitor freshwater ecosystems and provide actionable geospatial information to decision-makers. Aquaverse represents the cutting edge of this field, addressing the challenge of atmospheric interference in remote sensing.

The machine learning model in Aquaverse corrects for atmospheric distortions, providing clearer, more accurate insights into water bodies. This project has a significant impact on the ground, as water is essential for ecosystems, human health, and biodiversity. Aquaverse enables us to detect harmful algal blooms, monitor sediment levels, and assess water clarity in near-real-time.

Aquaverse is not just about improving data quality; it's about improving quality of life. The insights gained can be used by policymakers, environmentalists, and scientists to take timely actions to protect freshwater resources. Being part of a project with such a tangible, real-world impact on both people and the planet is truly exciting.

Tell us about one project of yours that has been particularly impactful in your field.

A particularly impactful project of mine is the STREAM platform (https://ladsweb.modaps.eosdis.nasa.gov/stream/), a Satellite-based analysis Tool for Rapid Evaluation of Aquatic Environments. STREAM empowers water resource managers with near-real-time water quality monitoring by integrating satellite data from NASA and the European Space Agency. This allows decision-makers to visualize and respond to potential water quality issues.

STREAM leverages Aquaverse, a machine-learning framework for atmospheric correction, and downstream products estimation. Aquaverse not only corrects for atmospheric distortions but also facilitates the estimation of downstream products like chlorophyll-a (Chla), total suspended solids (TSS), and colored dissolved organic matter (CDOM). This enhanced accuracy enables precise detection of algal blooms, identification of contamination areas, and sediment transport monitoring.

STREAM's impact goes beyond remote sensing advancement. It puts cutting-edge science directly in the hands of water resource managers, a crucial step towards protecting and sustainably managing our vital water systems. This exemplifies how scientific research can deliver immediate real-world benefits for society.

What does a typical day at work look like for you?

A significant portion of my work involves developing algorithms and models for satellite data processing. I spend a lot of time coding, analyzing data, and running simulations to refine our research outcomes. I regularly collaborate with my team, brainstorming solutions to technical challenges or discussing new directions to expand our research.

Recently, much of our focus has been on scaling up our cloud-computing efforts to handle large datasets for Aquaverse. I also work on converting our research findings into scientific reports, journal articles, and conference presentations. Additionally, I mentor research-interns and students, which is a particularly rewarding aspect of my job.

Our team works closely with national and international collaborators, and these partnerships help us develop and implement cutting-edge techniques for monitoring aquatic ecosystems on a global scale.

What skills are most useful to you in your work, and where did you develop those skills?

Combining machine learning with geospatial data analytics is crucial for my work. Handling large datasets requires strong programming skills, along with a deep understanding of atmospheric corrections, sensor calibration, and satellite imagery. The limited computing resources necessitate efficient processing, especially when working with massive datasets.

My specialization in high-performance computing (HPC) for large-scale geospatial data processing allows us to expedite processes that would otherwise be time-consuming. A recent collaboration with Microsoft Azure for a pilot project demonstrated the power of cloud computing in scaling up radiative transfer simulations. This partnership accelerated the process, completing simulations in weeks rather than months.

Beyond technical skills, patience and problem-solving are essential. These soft skills have been invaluable in navigating the complexities of processing and interpreting large geospatial datasets while working with limited resources and tight deadlines.

Where do you see yourself in the near future?

In the near future, I see myself continuing to lead innovative projects at NASA, expanding the applications of remote sensing to new areas such as climate change resilience and ecosystem restoration. I'm also interested in working closely with international partners to develop open-access tools that can make satellite data and machine learning more accessible to researchers and decision-makers in developing countries.

What is a fun fact about you?

If I hadn't pursued a scientific career, I would likely be a chef or an Indian classical vocalist! Cooking and music have always been my passions. The creative process of experimenting with recipes and perfecting ragas on the harmonium offers me the same joy as solving scientific problems. These hobbies help me unwind and refresh my mind for the daily scientific challenges I face.