NH43B-1891
Identifying Severe Weather Impacts and Damage with Google Earth Engine

Thursday, 17 December 2015
Poster Hall (Moscone South)
Andrew Molthan, Jason Eric Burks and Jordan R Bell, NASA Marshall Space Flight Center, Huntsville, AL, United States
Abstract:
Hazards associated with severe convective storms can lead to rapid changes in land surface vegetation. Depending upon the type of vegetation that has been impacted, their impacts can be relatively short lived, such as damage to seasonal crops that are eventually removed by harvest, or longer-lived, such as damage to a stand of trees or expanse of forest that require several years to recover. Since many remote sensing imagers provide their highest spatial resolution bands in the red and near-infrared to support monitoring of vegetation, these impacts can be readily identified as short-term and marked decreases in common vegetation indices such as NDVI, along with increases in land surface temperature that are observed at a reduced spatial resolution.

The ability to identify an area of vegetation change is improved by understanding the conditions that are normal for a given time of year and location, along with a typical range of variability in a given parameter. This analysis requires a period of record well beyond the availability of near real-time data. These activities would typically require an analyst to download large volumes of data from sensors such as NASA’s MODIS (aboard Terra and Aqua) or higher resolution imagers from the Landsat series of satellites. Google’s Earth Engine offers a “big data” solution to these challenges, by providing a streamlined API and option to process the period of record of NASA MODIS and Landsat products through relatively simple Javascript coding. This presentation will highlight efforts to date in using Earth Engine holdings to produce vegetation and land surface temperature anomalies that are associated with damage to agricultural and other vegetation caused by severe thunderstorms across the Central and Southeastern United States. Earth Engine applications will show how large data holdings can be used to map severe weather damage, ascertain longer-term impacts, and share best practices learned and challenges with applying Earth Engine holdings to the analysis of severe weather damage. Other applications are also demonstrated, such as use of Earth Engine to prepare pre-event composites that can be used to subjectively identify other severe weather impacts. Future extension to flooding and wildfires is also proposed.