SENTINEL-1 AND SENTINEL-2 TIME SERIES PROCESSING CHAINS FOR CYCLONE IMPACT MONITORING IN SOUTH WEST INDIAN OCEAN
Keywords: automated change detection, time series, Sentinel satellite, natural disaster, cyclones
Abstract. Monitoring the spatial footprint of cyclone impacts by remote sensing offers great potential for assessing the extent of damage and monitoring the resilience of the affected territories. For this purpose, as part of the Renovrisk-Impact project, we have developed two change detection processing chains based on optical (Sentinel-2) and SAR (Sentinel-1) data. These chains have been used to track different events in different regions of the world. In this article we focus on two study sites in Madagascar: the city of Miandrivazo, which was heavily affected by severe rainfall from Cyclone AVA in January 2018, and more recently the town of Marovoay which suffered a major disaster following the passage of tropical storm DIANE in January 2020. The obtained results were evaluated and compared with the Copernicus Emergency Mapping Service product, showing good consistency with this product and between them. These results confirm the potential of these Sentinel data and the developed processing chains for monitoring the impacts of cyclones, but also open up prospects for longer-term monitoring.