Quantify large population following climate disasters using satellites remote sensing imagery

ABSTRACT

Climate disasters such as floods, storms, droughts, and heatwaves are increasingly leading to signif- icant population displacements, with social, economic, and environmental impacts. This study aims to quantify these movements using satellite remote sensing imagery, focusing on Africa between 2000 and 2018, where such events are becoming more frequent. By analyzing high-resolution satellite im- ages and integrating additional data sources like Landscan population counts, this research aims to link climate disasters with subsequent population movements. The methodology involves a comprehensive data collection process, merging datasets from the Emergency Events Database (EM-DAT) and the Global Disaster Information System (GDIS) with remote sensing data from sources such as Copernicus Climate Data and Dynamic World This integration, made possible by the use of Earth Engine and its big data catalog, as well as Geemap, enables a detailed analysis of population distribution changes before and after disaster events. The study employs both yearly and monthly analyses to to find both short-term and long-term trends in human displacement. Advanced Geographic Information Systems (GIS) techniques and change detection models are used to evaluate land cover changes and validate observed population shifts. The findings are expected to fill significant gaps in our understanding of climate-induced migration, particularly in Africa. This research not only enhances scientific knowledge but also helps in developing practical tools and strategies for managing climate-induced migration and its impacts.