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STELLA Data

The story is in the data!

Data Types Collected by STELLA

Spectral Data

STELLA instruments capture spectral measurements across various wavelengths (from visible to near-infrared):

  • Visible and near-infrared irradiance at multiple wavelengths (250-940 nm)
  • Measurements in μW/cm²
  • Raw counts and calibrated values
  • Multiple sensor types (AS7331, AS72651, AS72652, AS72653)

Environmental Data

Depending on the model and sensor package, STELLA can collect:

  • Surface temperature (°C)
  • Air temperature (°C)
  • Relative humidity (%)
  • Barometric pressure (hPa)
  • Altitude data (m)

Air Quality Data (STELLA-AQ)

The STELLA-AQ variant measures:

  • CO₂ concentration (ppm)
  • Particulate matter concentrations (1μm, 2.5μm, 10μm in μg/m³)
  • Particle counts across multiple size ranges (0.3μm to 100μm)
  • Air Quality Index for particulates (AQIp)

Data Format and Storage

  • Data is recorded to a micro SD memory card
  • CSV file format with comprehensive headers
  • Timestamp information in ISO8601 format
  • Metadata includes unique identifiers, batch numbers, and measurement sequences

Data Applications

STELLA data supports:

  • Educational activities in K-12 and university settings
  • Field research for ecosystem monitoring
  • Natural resources inventories
  • Environmental quality surveys
  • Vegetation health assessment (NDVI “greenness”)
  • Custom applications through sensor adaptations

Data Visualization

  • Users can visualize and analyze their data in real-time using the STELLA dataviewer
  • Data can be easily exported for further analysis in other software

STELLA Variants and Their Data

  • STELLA-1.1/1.2: Full spectral and environmental data with touch-screen interface
  • STELLA-2.0: Bluetooth connectivity for data transfer to smartphones
  • STELLA-Q2: Simplified connector-based design (no soldering required)
  • STELLA-AQ: Specialized for air quality measurements
  • Helio-STELLA: Solar radiation focused measurements

The open-source nature of STELLA allows for customization of both hardware and data collection capabilities, making it an adaptable platform for a wide range of scientific and educational applications.

(STELLA-Q2, STELLA-1.1, STELLA-1.2 RS)

Some tips to collect good spectrometer data:

  • Make sure the target area is away from your shadow.  To keep out of the shadow the STELLA 1.0 and 1.1 can have a 1/2″ dowel rod inserted into the tapered hole in the back of the casing so you can hold the instrument away from you.
  • Hold the instrument steady during its data collection.
  • Take good field notes such as the batch number, what the target is your measuring, weather and atmospheric conditions.
  • The angle and distance of the instrument from the target play a role in the measurements you receive. If the angle of the instrument is tilted it will have an effect on the measurements taken. The further away the instrument the larger the swath of area being measured.

The data comes in as irradiance and the way to convert it to reflectance is by performing correct field calibrations.

STELLA spectrometer data is collected as a .csv (comma separated value) file on the micro SD card.

In individual sample (yellow) and continuous (blue) mode the data will be saved in batches on the data.csv file.

In sample and average (blue) mode the STELLA will take 20 measurements and put them into their own individual .csv file.

Data collected by the STELLA spectrometers is separated by Universal Identification (UID), batch number, date and time.

STELLA-Q collects air temperature, relative humidity, barometric pressure, and irradiance (µW/cm2) data between 450nm to 860nm.

STELLA-1.1 collects surface temperature, air temperature, relative humidity, barometric pressure, and irradiance (µW/cm2) data between 450nm to 860nm. As well as optional height measurement data using Lidar.

STELLA-2 collects surface temperature, air temperature, relative humidity, barometric pressure, irradiance (µW/cm2) between 450nm to 860nm, 3-axis acceleration (m/s2), 3-axis angular rotation (°/s), and 3-axis magnetic flux (μT) data.

STELLA Air Quality Data

(STELLA-AQ, STELLA-1.2 AA)

STELLA air quality data is collected as a .csv (comma separated value) file on the micro SD card.

Data collected by the STELLA-AQ is separated by Universal Identification (UID), batch number, date and time. 

Measurement data it collects is air quality index for particulates, carbon dioxide in parts per million (ppm), air temperature, relative humidity, barometric pressure, and particle densities from 2.5µm and 10µm. 

Helio Data

(Helio-STELLA)

STELLA air quality data is collected as a .csv (comma separated value) file on the micro SD card.

Spectral Data

  • Multi-wavelength Solar Measurements: Helio-STELLA measures sunlight across different wavelengths of the electromagnetic spectrum, allowing users to see how solar radiation is distributed across visible and potentially near-infrared bands.
  • Spectral Composition: The instrument can show the relative intensity of different wavelengths in sunlight, revealing its spectral signature.

Light Intensity Data

  • Lux Measurements: As specifically mentioned, Helio-STELLA incorporates a “lux sensor” that can “assess light brightness,” providing quantitative measurements of solar intensity.
  • Brightness Variations: These measurements can capture changes in overall solar radiation intensity throughout the day or under different atmospheric conditions.

Interactive Experiment Data

  • Filter Effects: As described in testimonials, users can collect data showing “how different colors influence the electromagnetic spectrum” by placing various filters in front of the sensor.
  • Comparative Readings: The instrument allows for before/after or with/without measurements to demonstrate how materials interact with solar radiation.

Associated Metadata

  • Time and Date: Like other STELLA instruments, Helio-STELLA likely records timestamps with measurements to track temporal patterns.
  • Batch Information: The STELLA platform generally assigns batch numbers to measurements for organizational purposes.