Mapping Wildfires with AVIRIS Data

This project focuses on identifying and mapping burned areas from wildfires using hyperspectral data from NASA's AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) and thermal anomaly data from VIIRS (Visible Infrared Imaging Radiometer Suite). The analysis is performed using Python tools and open-source geospatial libraries.

📁 Project Structure

• mapping_wildfires.ipynb: Main analysis notebook for loading, processing, and visualizing wildfire-related remote sensing data.
• data/: Folder containing AVIRIS and VIIRS GeoTIFF files and shapefiles (not included in repo for size reasons).
• figures/: Folder where output plots and maps are saved.
• README.md: Project overview and instructions (this file).

🔍 Objectives

• Merge AVIRIS granules to create a continuous mosaic of the affected area.
• Georeference hyperspectral images using associated latitude and longitude bands.
• Overlay VIIRS thermal anomaly data to correlate with AVIRIS observations.
• Visualize the extent of burned areas and assess spectral reflectance differences.

📦 Dependencies

Install the required libraries before running the notebook:

pip install -r requirements.txt

🛰️ Data Sources

• AVIRIS: https://daac.ornl.gov/AVIRIS/guides/AV3_L1B_RDN.html

🗺️ Tools Used

• Python (Jupyter Notebook)
• Rasterio & GDAL (for raster data manipulation)
• GeoPandas (for shapefile processing)
• Matplotlib (for visualization)

👤 Author

David — Applied Remote Sensing | NASA Open Science Participant