Global Mapping of Exposure and Physical Vulnerability Dynamics in Least Developed Countries using Remote Sensing and Machine Learning

arXiv:2404.01748v1 Announce Type: new
Abstract: As the world marked the midterm of the Sendai Framework for Disaster Risk Reduction 2015-2030, many countries are still struggling to monitor their climate and disaster risk because of the expensive large-scale survey of the distribution of exposure and physical vulnerability and, hence, are not on track in reducing risks amidst the intensifying effects of climate change. We present an ongoing effort in mapping this vital information using machine learning and time-series remote sensing from …

abstract arxiv climate cs.cv cs.lg disaster distribution dynamics framework global least machine machine learning mapping risk scale sensing survey type vulnerability world