Geospatial AI for Disaster Risk Assessment and Resilience

Uday Chatterjee is Assistant Professor in the Department of Geography, Bhatter College, India. He has a post graduate degree in Applied Geography from Utkal University and Doctoral Degrees in Applied Geography from Ravenshaw University, Cuttack, Odisha, India. His areas of research include urban planning, applied geomorphology, hazards and disasters, environmental issues, land use, etc. He is the author of many research papers published in various journals and edited book volumes, and a book editor as well.s.Kishor Dandapat is a professor in the Department of Geography at Seva Bharati Mahavidyalaya, Jhargram, under Vidyasagar University. His research expertise lies in human ecology, environmental issues, natural hazards, disaster management, and fluvial geomorphology. He is an author and a reviewer.Gopal Krishna Panda is Emeritus Professor at Kalinga Institute of Social Sciences (KISS) Deemed University, Bhubaneswar, India. His distinguished career spans 35 years, focusing on physical geography, coastal geomorphology, climate change, disaster management, and geospatial technology. He holds prestigious fellowships and has published several books.Sailesh Samanta is an associate professor in the School of Surveying and Land Studies at The Papua New Guinea University of Technology, Papua New Guinea. He has published over 50 peer-reviewed publications and is involved with the Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australian Centre of Agricultural Research (ACAR), and Pacific Islands Universities Research Network (PIURN).Monalisha Misra is an assistant professor of Geography at Kalinga Institute of Social Sciences (KISS) Deemed University, Bhubaneswar, India, specializing in Remote Sensing (RS) and Geographic Information Systems (GIS). She has over 13 years of teaching and industry experience, and has published many articles on natural hazards, disaster management, and coastal geography.

• Part I: Advanced Technologies for Disaster Risk Assessment. 1. Damage Assessment and Situational Awareness: Application of Advanced Technologies. 2. Applying Machine Learning for Poverty Mapping and Mitigating Social Disasters: A Data-Driven Approach. 3. Prioritization of Watersheds for Estimating Sediment Yield by Geographic Information Systems. 4. An Efficient and Lightweight Technique for Flood Image Classification Using MobileNet: A Deep Learning Approach. Part II: Applications for Risk Assessment and Vulnerability Mapping. 5. Artificial Intelligence Based Predictive Model for Assessing the Economic Impact of Water Release from the Mukutmonipur Dam in West Bengal, India. 6. Integrating Coastal Hazard Risk Assessment and Machine Learning for Vulnerability Mapping along the east coast of Odisha, India. 7. Earthquake Risk and Resilience in Jammu and Kashmir, Northwestern Himalaya, India. 8. Identification of Earthquake Potential Zone for Reducing Vulnerability in Sikkim (Eastern Himalaya) using Machine Learning and Geospatial Techniques. 9. Understanding Spatial Variation of Glacier Zones and Slope induced Risk through Deep Learning and Statistical Methods on selected glaciers of Western Himalaya. 10. A Hybrid IoT–LoRaWAN and Deep Learning Framework for Real-Time Landslide Monitoring and Early Warning. 11. Environmental Effects of Sand Mining: Implications for Vegetation and Climate Risks in Anambra State, Nigeria. Part III: Integrated Systems and Urban Disaster Resilience. 12. Mapping of Flood Risk and Shelter Suitability: A Case Study in Diphu Town, Karbi Anglong District, Assam, India. 13. Integrating AI-Driven Last-Mile Logistics into Urban Disaster Resilience Frameworks.