AI Based Urban Resilience Planning: Opportunities and Challenges

Abstract

Urban areas across the globe are confronting escalating flood risks, a crisis exacerbated by the effects of climate change, which necessitates precise hyper-localized risk assessments. This research introduces the application of the AI for resilient cities model for flood risk assessment, focusing specifically on the vulnerable area of Penthakata, located in the coastal city of Puri, Odisha. The hyper-local evaluation of associated flood risks is carried out, particularly at the building level. Leveraging cutting-edge geospatial technology, deep learning methodologies, and multi-parameter analysis, this study offers valuable insights into the flood vulnerabilities in the region. Additionally, the research emphasizes the integration of technology with community volunteers and local knowledge, highlighting the essential role of grassroots-level efforts in effective disaster management. The model is one of its kind combining advanced AI technology with community engagement, the study contributes to a holistic and localized approach to strengthen adaptive capacity in the face of increasing flood risks. The findings offer a compelling case for the adoption of hyperlocal risk assessments for urban and rural areas to be better informed of flood risks, prepared for potential disasters, and implement more effective mitigative measures. Ultimately, it aims to safeguard the lives and livelihoods of vulnerable communities of various regions, offering a model for spatial environmental and community resilience.