Spatial Intelligence for Hydrometeorological Hazards in a Changing Climate

Professor Pradhan is a globally recognized expert in geospatial analytics and artificial intelligence applications in Earth and environmental sciences. Currently a Distinguished Professor at the University of Technology Sydney (UTS), Australia, he also leads the Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS). With a PhD in GIS-based modeling, Prof. Pradhan has over two decades of experience in spatial data science, remote sensing, natural hazard modeling, and environmental monitoring. He has been listed among the world's top 2% scientists by Stanford University and received numerous international awards, including from IEEE and Elsevier. A Fellow of the Royal Geographical Society (FRGS), he also serves on editorial boards of several top-tier journals. His research integrates geospatial AI and deep learning for disaster risk reduction, land use planning, and sustainability.Prof. Mahesh Kumar Jat holds B.E. in Civil Engineering (Hons.); M. E. (Water Resources Engineering) and Ph.D. (Integrated Water Resource Management) from IIT Roorkee. The major areas of his research are Integrated Water Resources Management; Hydrological modelling; Climate change, Remote Sensing and GIS Applications. Dr. Abhirup Dikshit is a geospatial ecohydrologist using advanced remote sensing tools and machine learning models to monitor vegetation health and function in the face of climate change, land use, and other major disturbance events. He has published more than 30 articles and was awarded the International Research Training Program (IRTP) scholarship funded by the Australian Government under Department of Education and Training to pursue my doctoral studies in Australia.

• 1. Spatial Intelligence in Hydrometeorological hazard context2. Future hazard scenarios using climate models (CMIP-6)3. Impact of climate change on landslide types4. Landslide Modelling in a Changing Climate5. Landslide Risk6. Linkage between drought and climate change7. Analyzing spatio-temporal droughts using next-gen geostationary satellites8. Drought Forecasting using Advanced Machine Learning Techniques9. Quantifying soil erosion impacts due to future climate scenario10. Flood Modelling using Explainable AI models11. Flood Mitigation Strategies in a Changing Climate12. Climate Change and Heat Events13. Flash Droughts14. Ethical and Societal Implications of Machine Learning in Climate Hazards