Overview

Geospatial Information and Services for Climate Resilient Disaster Management explores how cutting-edge technology can shape our response to climate-related disasters. Leading experts uncover the indispensable role that geospatial information and services can play in disaster preparedness, response, and recovery. The book opens with an overview of climate resilient disaster management and the application of geospatial technology. The chapters next undertake a thorough examination of early warning systems, risk assessment, vulnerability mapping, resource allocation, and disaster response. Following from those vital tools and applications, the editors then evaluate climate adaptation planning and community engagement in the light of geospatial technology. The book wraps up with real-world case studies and success stories along with a discussion of current challenges and future trends. Readers concerned with the rising connections between natural disaster and climate change will be inspired by this inside view of the latest innovations in geospatial information and services.

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9780443292163

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Dr. Deepak Kumar is an academic researcher with a multidisciplinary background in Geospatial Sciences, Computational Sciences, Climate Change, and Sustainability. Currently a Research Scientist in the Atmospheric Sciences Group at Texas Tech University. Previously he served as Research Scientist in the Atmospheric Sciences Research Center at the State University of New York at Albany from August 2022 to November 2024. He's worked in the interdisciplinary research domain of the Urban-Climate-Energy nexus for policy making with humanities, social science, and technology perspectives. At Amity University, Delhi-NCR he was an Assistant Professor. His wide experience in the research development-cum-implementation pipeline comprising idea conceptualization, research design, data collection, processing, analysis, with result creation in the intersection areas of remote sensing and geoinformatics, environment, energy, climate change, urban weather and climate modelling, analysis, and visualization. He enjoys developing skills through conference appearances, outreach activities, training services and contributions to professional membership of scholarly associations. Nick P. Bassill has several years of experience in climate computing research and its impact assessment. Dr. Bassill received his PhD in Atmospheric and Oceanic Sciences from the University of Wisconsin-Madison, with a research focus on ensemble and parameterization studies. Afterwards, he worked as a post-Doctoral researcher at the University of Utah, where he studied aspects of Hurricane Sandy’s unusual track (including what led some models to make an incorrect forecast). Afterwards, he began work as a Post-Doctoral researcher with the New York State Mesonet to begin building an operational analysis system that would utilize Mesonet observations. Concurrently, he is actively involved in building meteorological products for and doing basic research with the New York State Mesonet. Currently, Nick predominantly spends his time working with the Center of Excellence on a variety of projects. He has published various research papers in international journals of high repute. He has also conducted sessions on Numerical weather prediction, with a specialization in WRF modelling, Data assimilation, Weather forecasting, Tropical cyclones, Data analysis of both gridded model data and weather observations and the New York State Mesonet. He also has experience in providing scientific leadership to high-profile strategic computational sustainability and conservation initiatives with several years of research experience. Managed cross-sectoral and interdisciplinary teams of professionals to deliver on complex research projects. Currently, he is working as a Director of Research & Development the at Center of Excellence, State University of New York at Albany. His core area of Interest covers Financial Markets, Energy & Utilities, Emergency Management, Risk Management, Climate Computing, AI and Machine Learning, and Industry 4.0.

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