Towards an Intelligent and Adapted Small Scale Landslides Monitoring System in East Africa: Shyira Landslide Monitoring Using Sentinel – 1 SAR Data on Google Earth Engine Cloud Computing

Authors- Bernard Hakizimana1, Kingsley Chika Chukwu2

Abstract- -Rainfall-induced landslides pose significant threats in Rwanda’s North-Western provinces, contributing to major disasters. This paper addresses technological challenges in disaster response, specifically focusing on soil displacement quantification. The study centers around the Mukungwa River at a local scale, utilizing remote sensing techniques and community science. The methodology employs In SAR polarization and phase measurements, with a specific focus on Shyira Landslide Monitoring using Google Earth Engine Cloud Computing. A citizen science approach is seamlessly integrated into the study’s framework. The landslide detection methodology involves carefully selecting an Area of Interest (AOI) and distinct time periods Before Event (B Event) and After Event (A Event), corresponding to the landslide occurrence. To comprehensively represent ground surface properties pre- and post-landslide, SAR image stacks are generated. These stacks, calculated as temporal medians of SAR data, are constructed for ascending data, descending data, and a combination of both. Landslide detection entails assessing changes in the backscatter coefficient using the standard SAR intensity log ratio approach.
The classification process categorizes changes into three classes: stable, subsidence/decrease, and increase/uplift. To deepen insights, a CSV file is generated for statistical analysis, providing a quantitative examination of landslide event dynamics. The study conducts comprehensive statistical analysis and derives meaningful recommendations. This research significantly contributes to understanding landslide monitoring through a robust methodology that combines remote sensing technologies, community engagement, and statistical analysis. Findings include the impact and damages of the landslide; out of the 5,000 surveyed buildings, 96 were completely destroyed, 231 suffered extensive damage, and 1,150 were moderately affected. The derived recommendations have implications for disaster response strategies and underscore the importance of technological advancements in addressing the challenges posed by landslides.

DOI: /10.61463/ijset.vol.11.issue6.105