During the summer 2015 Term of the NASA DEVELOP Program, teams used NASA remote-sensing data to investigate many dynamic environmental issues across the globe to develop effective solutions for affected communities. Each term, these projects demonstrate the diverse applications of remote-sensing data, including data distributed by the Land Processes Distributed Active Archive Center (LP DAAC). Common data products used across projects this term included Normalized Difference Vegetation Index (NDVI) data from the Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS), the Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM), and NASA's Shuttle Radar Topography Mission (SRTM) data. These data were often used along with other data types distributed by the U.S. Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA).
Several teams investigated vegetation regrowth and flooding risk after wildfire events. One team used Terra MODIS NDVI data and ASTER GDEM in conjunction with the NOAA PERSIANN Climate Data Record to create risk maps showing how precipitation anomalies, burn severity, and vegetation response impact flooding in the southwestern United States.
Another team used the MODIS Burned Area product (MCD45A1) along with Landsat to quantify fire distribution in Ericaceous shrublands of the Bale-Arsi massif, Ethiopia, mapping burned areas over a 42 year period (1973-2015). The team’s findings improved the understanding of past fire extent, which will inform future conservation efforts by The Murulle Foundation and its partners in Ethiopia.
Another team created a risk map of potential wildfire areas across Texas. The map delineates areas that contain dry fuels and, more specifically, how dry the fuels are. This team used Terra MODIS NDVI data (MOD13Q1), Aqua MODIS land surface temperature data (MYD11A2), precipitation from the Multi-Sensor Precipitation Estimate (MPE), and soil moisture from the North American Land Data Assimilation System (NLDAS). The team was able to develop a high-resolution drought index that can be easily constructed with little cost to the end-user. Methods and results produced for determining drought conditions were presented to the Texas Forest Service for future use throughout the state.
Featured Project: Minimizing Human-Ocelot Conflicts in Texas and Arizona
A unique project this term was conducted by a team aiming to develop a remote-sensing approach to assist with ocelot conservation. Landsat 8 Operational Land Imager (OLI) and Landsat 5 Thematic Mapper (TM) data were used to create supervised land cover classifications for 1996, 2005, and 2014 during January through March to assess land use and land cover over time.