A document by Karen An. Click on the document to view its contents.

Many communities coexist with wildfires that can lead to loss of lives, property, and ecosystem services. The increasing usage of remote sensing tools to aid disaster response and post-event assessment offers fire agencies an opportunity for additional surveillance. The adaptability of radar instruments in their ability to see through smoke, haze, and clouds during the day or night is especially relevant when cloud cover or lack of solar illumination inhibits traditional visual surveys of damage. The Station (2009) and Bobcat (2020) Fires are the two largest fires in Los Angeles County history, each burning over 100,000 acres. These areas are imaged with NASA’s UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar) L-band synthetic aperture radar. For these neighboring fires, we investigate the usage of polarimetric radar products to detect fire scars, burn severity, and different fuel (vegetation) types. These fire characteristics are observed using individual HV (horizontally emitted, vertically collected) images and in eigenvector decomposition products derived from quad-polarimetric data. Traditionally unintuitive, yet powerful PolSAR (polarimetric SAR) products are moved into GIS-friendly (geographic information system) formats to be analyzed alongside agency data such as fire perimeters, burn progression outlines, and soil burn severity. We demonstrate the advantages of combining PolSAR with GIS datasets and methods to understand the fuel loads which contributed to the fires and to monitor post-fire vegetation recovery.

In 2015 and 2016, the AfriSAR campaign was carried out as a collaborative effort among international space and National Park agencies (ESA, NASA, ONERA, DLR, ANPN and AGEOS) in support of the upcoming ESA BIOMASS, NASA-ISRO Synthetic Aperture Radar (NISAR) and NASA Global Ecosystem Dynamics Initiative (GEDI) missions. The NASA contribution to the campaign was conducted in 2016 with the NASA LVIS (Land Vegetation and Ice Sensor) Lidar, the NASA L-band UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar). A central motivation for the AfriSAR deployment was the common AGBD estimation requirement for the three future spaceborne missions, the lack of sufficient airborne and ground calibration data covering the full range of ABGD in tropical forest systems, and the intercomparison and fusion of the technologies. During the campaign, over 7000 km2 of waveform Lidar data from LVIS and 30000 km2 of UAVSAR data were collected over 10 key sites and transects. In addition, field measurements of forest structure and biomass were collected in sixteen 1 hectare sized plots. The campaign produced gridded Lidar canopy structure products, gridded aboveground biomass and associated uncertainties, Lidar based vegetation canopy cover profile products, Polarimetric Interferometric SAR and Tomographic SAR products and field measurements. Our results showcase the types of data products and scientific results expected from the spaceborne Lidar and SAR missions; we also expect that the AfriSAR campaign data will facilitate further analysis and use of waveform Lidar and multiple baseline polarimetric SAR datasets for carbon cycle, biodiversity, water resources and more applications by the greater scientific community.