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Spatial Intelligence for Hydrometeorological Hazards in a Changing Climate

  • Book

  • July 2025
  • Elsevier Science and Technology
  • ID: 6042218
Spatial Intelligence for Hydrometeorological Hazards in a Changing Climate explores the intersection of advanced machine learning techniques and the intricate challenges posed by shifting hydrometeorological patterns. This comprehensive guide navigates readers through a diverse landscape of topics, ranging from data-driven models for early prediction of floods, landslides, soil erosion, heat waves, droughts, and novel approaches for assessing the impacts of extreme weather events on ecosystems and societies. Through real-world case studies and practical examples, the book demystifies complex algorithms and equips readers with the skills to harness the power of machine learning.

Whether you are a researcher, practitioner, or enthusiast, this book empowers you to leverage cutting-edge technology to address the urgent and evolving threats of a changing climate.

Table of Contents

1. Spatial Intelligence in Hydrometeorological hazard context
2. Future hazard scenarios using climate models (CMIP-6)
3. Impact of climate change on landslide types
4. Landslide Modelling in a Changing Climate
5. Landslide Risk
6. Linkage between drought and climate change
7. Analyzing spatio-temporal droughts using next-gen geostationary satellites
8. Drought Forecasting using Advanced Machine Learning Techniques
9. Quantifying soil erosion impacts due to future climate scenario
10. Flood Modelling using Explainable AI models
11. Flood Mitigation Strategies in a Changing Climate
12. Climate Change and Heat Events
13. Flash Droughts
14. Ethical and Societal Implications of Machine Learning in Climate Hazards

Authors

Biswajeet Pradhan Distinguished Professor and Director, Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), University of Technology Sydney, School of Information, Systems and Modelling; Faculty of Engineering and IT, New South Wales, Australia. Biswajeet Pradhan is a distinguished professor at UTS School of Civil and Environmental Engineering. He is an international expert in data-driven modelling and a pioneer in combining spatial modelling with statistical and machine learning models for natural hazard predictions including landslides. He has a track record of outstanding research outputs, with over 600 journal articles. He is a highly interdisciplinary researcher with publications across 12 areas, listed as having 'Excellent' international collaboration status. He has been a Highly Cited Researcher for five consecutive years (2016-2020) and ranks fifth in the field of Geological & Geoenvironmental Engineering. Mahesh Kumar Jat 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 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.