Generating satellite SAR-based landslide density heatmaps for rapid landslide detection in Google Earth Engine

Detection of landslides is critical for emergency response and improving our understanding of where landslides occur. Satellite-based synthetic aperture radar (SAR) can be used to identify landslides, often within days after triggering events, because it penetrates clouds, operates day and night, and is regularly acquired worldwide. Here we present a landslide heatmap approach based on SAR backscatter change that uses multi-temporal stacks of open-access data from the C-band Copernicus Sentinel-1 satellites to detect areas with high landslide density on the cloud-based Google Earth Engine (GEE). Importantly, our approach does not require downloading a large volume of data to a local system or specialized processing software. We refine our GEE-based approach by examining the July 2018 rainfall-triggered landslide event in Hiroshima, Japan. We then apply our strategies to simulated rapid response scenarios for the September 2018 earthquake-triggered landslide event in Hokkaido, Japan and for multiple rainfall-triggered landslide events that occurred in October 2020 in Vietnam. In each case, the heatmaps allowed us to detect areas with high landslide density within two weeks of the triggering event. We find that our ability to detect surface change from landslides generally improves with the total number of SAR images acquired before and after a landslide event, by combining data from both ascending and descending satellite acquisition geometries, and applying topographic masks to remove flat areas unlikely to experience landslides. Our work shows that SAR-based landslide detection can be performed quickly and efficiently in GEE. Future open-access SAR missions, like the L-band NASA-ISRO NISAR mission, which is currently expected to launch in 2022, will also provide publicly available data that will be useful for rapid response to landslide events. If GEE ingests the NISAR data, our methodology could be used for Sentinel-1 and NISAR, which will undoubtedly improve the ability to monitor natural hazards.