Sustainability and Health Informatics: A Systems Approach to Address the Climate Action Induced Global Challenge

This book offers a comprehensive overview of the latest research, technologies, and applications of health informatics to promote sustainability and address climate change. The book focuses on the complex and multi-faceted challenge induced by climate change — a challenge that requires a systems approach at the global, national, and local levels. It explores the ethical and social implications of health informatics and climate change solutions, including issues related to data privacy, equity, and access to healthcare. The book primarily fills the gap in the available literature on the subject by bringing together the concepts, theories, and practical experiences of specialists and professionals in one volume. In addition, examples of successful health informatics and climate change solutions from around the world are showcased, including innovative approaches to data collection, analysis, and dissemination. The book is an essential resource for researchers, practitioners, and policymakers in the fields of health informatics, sustainability, and climate change.

The interconnected challenges of climate change and human health require a multidisciplinary and integrated approach that includes the use of health informatics tools and methods. By leveraging the power of informatics, we can develop innovative solutions to mitigate the impacts of climate change on human health and to build more resilient and sustainable communities.

Dr. Gaurav Tripathi is an assistant professor at the Department of Geoinformatics, School of Basics and Applied Sciences, Shobhit University, Meerut, India. Previously, he worked with the Centre for Climate Change and Water Research, Suresh Gyan Vihar University, Jaipur, India. He completed his post-graduate diploma in geo-information science and earth observation with a specialization in geo-informatics from the International Institute for Geo-Information Science and Earth Observation (ITC) Netherlands/University of TWENTE and the Indian Institute of Remote Sensing, Indian Space Research Organization (ISRO), Dehradun. He has published 16 journal articles, 12 book chapters, 2 IEEE conference papers, 1 edited book, and 4 patents. He presented research papers at various national and international conferences. He has more than 7 years of research experience in geoinformatics and its application area. He was also involved in the NASA-ISRO Synthetic Aperture Radar Mission (NISAR) project. His research interests include atmospheric remote sensing, satellite navigation, disaster management, synthetic aperture radar (SAR), InSAR, DInSAR, SAR polarimetry, interferometry, tomography, information theory, and retrieval modeling.

Dr. Achala Shakya is an assistant professor at the School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India. Prior to that, she was associated with the Computer Science and Engineering Department at Sharda University, Greater Noida (U.P.), India. She was awarded a Ph.D. from the Computer Engineering Department at the National Institute of Technology Kurukshetra. She was also associated with the NASA-ISRO Synthetic Aperture Radar Mission (NISAR) project under the project entitled “Fusion of SAR and optical data for advance LULC classification”. She has completed a pilot project entitled “Kernel-based Noise Clustering Fuzzy Classification” at the Indian Institute of Remote Sensing, Dehradun. She has more than 4 years of research and 3 years of teaching experience. She has published 11 research articles, 5 book chapters, 2 IEEE conference papers, 1 edited book, and 4 patents. She presented research papers at various national and international conferences. For the last three years, she has been continuously serving as the brand ambassador and proctor of the IEEE Programming Competition. She had also edited a textbook entitled “Linear Programming”. She is working in the fields of image fusion and segmentation, optical, radar, and hyperspectral remote sensing, deep learning, machine learning, natural language processing, information retrieval, and web development.