Optical remote sensing depends on clear-sky imagery where reflected sunlight is not obstructed by cloud or smoke cover. This can be rare during a fire or in recently burned areas. Satellites with high spatial resolution (Landsat 8 and 9, Sentinel 2a and 2b) have a narrow swath of coverage and may not capture a clear-sky image for days or weeks after a fire ignites due to persistent smoke. Meanwhile, burned areas are vulnerable to post-fire risks like flooding as soon as the ecosystem starts burning. To reduce this data gap, we developed a tool that synthesizes multi-satellite optical imagery to create burn severity maps using the most timely clear-sky data available. The Advanced Baseline Imager (ABI) aboard GOES, and the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard NOAA-20 and Suomi-NPP, provide hypertemporal data suited to this objective. ABI, a geostationary radiometer, delivers imagery of Continental United States every five minutes, while polar-orbiting NOAA-20 and Suomi NPP scan the US once daily. High frequency, spatially-coarse GOES imagery compliments the less frequent but higher resolution VIIRS imagery.
Our burn-mapping tool is designed to support National Weather Service meteorologists and hydrologists. A user-friendly interface allows practitioners to develop burn severity maps, customize their scale and location, and select before/after fire event dates. The resulting maps are available for download in multiple open-standard, GIS-compatible formats. Powered by Google Earth Engine, the processing is entirely automated and runs on-demand using the high-speed parallel processing of Google Cloud. Because GOES data is continuously uploaded to Google Cloud in near real-time, this App reduces latency by co-locating data storage, access, analysis and visualization.

