(EXERCISE - DaNCE March 2026) Landslide Proxy Heat Map (Copernicus Sentinel-1) for the Brazil Flood, May 2024

Dates of Images: 5/11/2024 Summary: The NASA GSFC landslides team produced this landslide proxy heatmap from Sentinel-1 imagery. Potential landslides were detected by calculating the change in the backscatter coefficient before and after the triggering event using the log ratio approach (Iratio). The Iratio is generated by subtracting median pre- and post-event Radiometrically Terrain Corrected (RTC) gamma0 backscatter in decibel scale at 10 m resolution obtained from the Alaska Sar Facility’s Hybrid Pluggable Processing Pipeline (HyP3). The likely landslide pixels are identified using 99th percentile Iratio threshold considering areas greater than 10-degree in slope and not affected by radar shadow and layover effects. A heatmap is generated using identified landslide pixels for visualization ease. Pre-event imagery = median imagery generated using images from 09/14/2023, 09/26/2023 Post-event imagery = 05/11/2024 This map should be used as a guide to identify areas likely affected by landslides. This is a rapid response product. We have not done any form of manual verification or corrections to remove false positives. Please see the slope and shadow layover mask item for areas not considered in this analysis. Suggested Use: The red and yellow areas indicate potential zones of dense landsliding. False positives related to natural and human-made ground surface change, including but not limited to deformation from mining, construction, deforestation, agriculture, flooding, snow cover, and changes in reservoir water levels can also be within the red and yellow areas. Satellite/Sensor/Resolution: Synthetic Aperture Radar on European Space Agency's (ESA) Copernicus Sentinel-1 satellite, 10 meters Credits: NASA GSFC landslides team, Copernicus Sentinel-1 data Esri REST Endpoint: See URL to the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_sentinel1_landslide_heatmap/ImageServer/WMSServer

Dates of Images: Post-Event: 06/25/2026 Pre-Event: 04/07/2026-06/13/2026 (8 images total) Summary: The NASA GSFC landslides team produced this landslide proxy heatmap from Sentinel-1 imagery. Potential landslides were detected by calculating the change in the backscatter coefficient before and after the triggering event using the log ratio approach (Iratio). The Iratio is generated by subtracting median pre- and post-event Radiometrically Terrain Corrected (RTC) gamma0 backscatter in decibel scale at 10 m resolution obtained from the Alaska Sar Facility’s Hybrid Pluggable Processing Pipeline (HyP3). This map should be used as a guide to identify areas likely affected by landslides. This is a rapid response product. We have not done any form of manual verification or corrections to remove false positives. The likely landslide pixels are identified using 99th percentile Iratio threshold considering areas greater than 10-degree in slope and not affected by radar shadow and layover effects. A heatmap is generated using identified landslide pixels for visualization ease. Pre-event imagery = median imagery generated using images from 04/07/2026-06/13/2026 (8 images total) Post-event imagery = 06/25/2026 Suggested Use: The red and yellow areas indicate potential zones of dense landsliding. False positives related to natural and human-made ground surface change, including but not limited to deformation from mining, construction, deforestation, agriculture, flooding, snow cover, and changes in reservoir water levels can also be within the red and yellow areas. Satellite/Sensor/Resolution: Synthetic Aperture Radar on European Space Agency's (ESA) Copernicus Sentinel-1 satellite, 10 meters Credits: NASA GSFC landslides team, Copernicus Sentinel-1 data Citation: Handwerger AL, Huang M-H, Jones SY, Amatya P, Kerner HR, Kirschbaum DB. 2022. Generating landslide density heatmaps for rapid detection using open-access satellite radar data in Google Earth Engine. Nat. Hazards Earth Syst. Sci. Copernicus Publications, 22(3): 753–773. https://doi.org/10.5194/nhess-22-753-2022. Esri REST Endpoint: See URL to the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202606_EARTHQUAKE_VENEZUELA/202611_sentinel1_landslide_heatmap/ImageServer/WMSServer

Dates of Images: Post-Event: 06/25/2026 Pre-Event: 04/07/2026-06/13/2026 (8 images total) Summary: The NASA GSFC landslides team produced this landslide proxy heatmap from Sentinel-1 imagery. Potential landslides were detected by calculating the change in the backscatter coefficient before and after the triggering event using the log ratio approach (Iratio). The Iratio is generated by subtracting median pre- and post-event Radiometrically Terrain Corrected (RTC) gamma0 backscatter in decibel scale at 10 m resolution obtained from the Alaska Sar Facility’s Hybrid Pluggable Processing Pipeline (HyP3). The likely landslide pixels are identified using 99th percentile Iratio threshold considering areas greater than 10-degree in slope and not affected by radar shadow and layover effects. A heatmap is generated using identified landslide pixels for visualization ease. Pre-event imagery = median imagery generated using images from 04/07/2026-06/13/2026 (8 images total) Post-event imagery = 06/25/2026 This map should be used as a guide to identify areas likely affected by landslides. This is a rapid response product. We have not done any form of manual verification or corrections to remove false positives. Suggested Use: The red and yellow areas indicate potential zones of dense landsliding. False positives related to natural and human-made ground surface change, including but not limited to deformation from mining, construction, deforestation, agriculture, flooding, snow cover, and changes in reservoir water levels can also be within the red and yellow areas. Satellite/Sensor/Resolution: Synthetic Aperture Radar on European Space Agency's (ESA) Copernicus Sentinel-1 satellite, 10 meters Credits: NASA GSFC landslides team, Copernicus Sentinel-1 data Citation: Handwerger AL, Huang M-H, Jones SY, Amatya P, Kerner HR, Kirschbaum DB. 2022. Generating landslide density heatmaps for rapid detection using open-access satellite radar data in Google Earth Engine. Nat. Hazards Earth Syst. Sci. Copernicus Publications, 22(3): 753–773. https://doi.org/10.5194/nhess-22-753-2022. Esri REST Endpoint: See URL to the right. WMS Endpoint: See Sublayers.

Date of Image: 9/28/2024, 10/3/2024, 10/5/2024, 10/10/2024, 10/15/2024, 10/17/2024 Date of Next Image: Unknown Summary: NASA used a Sentinel-1 SAR backscatter change approach developed in GEE (Handwerger et al., 2022) to detect areas with high landslide density. This approach detects potential landslides by calculating the change in the backscatter coefficient before and after the triggering event using the log ratio approach. False positives such as backscatter change due to flooding, agriculture, and more, are removed by using threshold-based masks made from the topographic slope from the 1 arcsec (∼30 m) resolution NASADEM (NASA JPL, 2020). Using stacks of SAR data reduces noise, and furthermore, the pre-event stack provides backscatter data that is more representative of the pre-event ground surface properties. Finally, to detect landslide areas, the backscatter change raster was thresholded using the 99th percentile to highlight strong signals, and the heatmap was calculated. Pre-event time frame: 2024-01-10 to 2024-09-26 Post-event time frame: 2024-09-28 to 2024-10-17 This map should be used as a guidance to identify areas likely affected by landslides. This is a rapid response product. We have not done any form of manual corrections to remove false positives. Suggested Use: The red and yellow areas indicate potential zones of dense landsliding. Disclaimer: not verified in field and optical imagery has clouds preventing verification. Satellite/Sensor: Copernicus Sentinel-1 Synthetic Aperture Radar (SAR) Resolution: 10 meters Credits: NASA GSFC Landslides Team, Copernicus Sentinel-1 data Handwerger Al, Huang M-H, Jones SY, Amatya P, Kerner HR, Kirschbaum DB. 2022. Generating landslide density heatmaps for rapid detection using open-access satellite radar data in Google Earth Engine. Nat. Hazards Earth Syst. Sci. Copernicus Publications, 22(3): 753–773. https://doi.org/10.5194/nhess-22-753-2022. Esri REST Endpoint: See URL section on right side of page

Dates of Images: 4/28/2024, 4/29/2024, 4/30/2024, 5/1/2024, 5/2/2024, 5/5/2024, 5/6/2024 Summary: LHASA was created at Goddard Space Flight Center to identify the potential for rainfall-triggered landslides in real time. LHASA version 2 adopts machine learning to estimate the probability of landslide occurrence at a 30-arcsecond (~1 km) daily resolution. In addition, it estimates the potential exposure of human population and roads to landslide hazard and maps the basins likely to experience post-fire debris flows. Suggested Use: The global landslide nowcast shows where landslide hazard is highest on a given date. Resolution: ~1km Credits: Please cite: Stanley T. A., J. R. Sutton, R. S. Vershel, P. M. Amatya. 2025. "Better Satellite Precipitation Algorithms Slightly Improved Landslide Hazard Assessment." Journal of Applied Meteorology and Climatology 64 (10): 1379-1394 10.1175/jamc-d-25-0021.1 Esri REST Endpoint: See URL on the right side of the page. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/EX2602_lhasa/ImageServer/WMSServer

Dates of Images: 5/6/2024 Summary: The NASA GSFC landslides team produced this landslide polygon map. The landslide map was produced automatically from Planet imagery using the prototype Global Landslide Detection for Rapid response (GLiDEr) system, currently under development as a joint effort between the NASA GSFC landslides team and Data Science group. Pre-event imagery = mosaic of images from 04/20/2024 and 04/21/2024 Post-event imagery = mosaic of images from 05/05/2024 and 05/06/2024 This map has undergone manual false positive removal, but we have not corrected erroneous landslide areas, added missed landslides and resolved amalgamation. Suggested Use: This map can be used to identify location and size of landslides. For landslide mapping extent, refer to the mapping_AOI layer. Credits: NASA GSFC landslides team, NASA GSFC Data Science group, Planet Labs Esri REST Endpoint: See URL on the right side of the page. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/EX2602_planet_landslide_vector/MapServer/WMSServer