Miura, T; Nagai, S (2020). Landslide Detection with Himawari-8 Geostationary Satellite Data: A Case Study of a Torrential Rain Event in Kyushu, Japan. REMOTE SENSING, 12(11), 1734.

In this study, we investigated the utility of Himawari-8 Advanced Himawari Imager (AHI), one of third-generation geostationary satellite sensors, for mapping landslides caused by torrential rain that hit the northern Kyushu area in Japan in the summer of 2017. AHI normalized difference vegetation index (NDVI) time series data had distinctive temporal signatures over landslide areas where the NDVI abruptly decreased after the rain event. The observed changes in the NDVI were linearly correlated with the percent landslide area, the percentage of landslide areas within the AHI pixel footprint, obtained with aerial survey (r = 0.78). AHI 10 min resolution data obtained near cloud-free coverage of the landslide region by the 8th day after the disaster event. This was comparable to the amount of time it took to obtain near cloud-free image coverage with aerial survey, and better than those with the polar-orbiting satellite sensors of Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite, Landsat-8 Operational Land Imager, and Sentinel-2A/B MultiSpectral Instrument. These results suggest that third-generation geostationary satellite data can serve as another useful resource for post-event, region-wide initial assessment of landslide areas after a heavy rain event.