AI in Identifying Climate Vulnerabilities in Urban Areas in Zambales

Abstract

This study aims at identifying the potential of using artificial intelligence (AI) in estimating climate risks for the urban areas in Zambales, which are often affected by climate change risks. This study has used machine learning models and data analytics to establish regions and populations most vulnerable to flooding, extreme temperatures, and other climate shocks. Based on the collected data of weather conditions, population, social, and economic characteristics of the region, as well as the availability of necessary infrastructure, the AI framework is designed to make recommendations for further actions and improvements to the local governments and interested parties. The results help address concerns in sustainable urban development, behavioral change, and improvements in Zambales' likelihood of adapting to the emerging uncertainties of climate risks.