{"product_id":"9783032331328","title":"GeoAI for Deltas Remote Sensing, Simulation, and Smart Governance","description":"\u003ch3\u003eDeltas of the World\u003c\/h3\u003e\u003ch1\u003eGeoAI for Deltas\u003c\/h1\u003e\u003ch2\u003eRemote Sensing, Simulation, and Smart Governance\u003c\/h2\u003e\u003ch3\u003eShubham Mahajan | Amit Kant Pandit | Kamal Upreti\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eScience \/ Earth Sciences \/ General\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cp\u003eThe book provides a comprehensive guide on applying GeoAI for the sustainable management of vulnerable delta regions. It integrates remote sensing, simulation, and smart governance frameworks. Also, it demonstrates how artificial intelligence, when combined with geospatial technologies, can transform monitoring, prediction, and decision-making in environments. Moreover, the book addresses challenges like flooding, coastal erosion, and urbanization by presenting cutting-edge AI-driven methods. It covers advanced remote sensing, machine\/deep learning for geospatial analysis, flood risk prediction, coastal erosion modeling, water quality monitoring, and urbanization impact assessment. It also explores the creation of digital twins, AI-enabled early warning systems, and smart governance frameworks that include citizen science.\u003c\/p\u003e\r\n\u003cp\u003eAdditionally, it discusses ethical, legal, and societal considerations for responsible and sustainable GeoAI deployment. The book combines theoretical foundations with practical case studies across all chapters. It offers the audience actionable insights to enhance resilience, improve policy-making, and optimize resource allocation. \u003c\/p\u003e\r\n\u003cp\u003eThe book's beneficiaries include researchers, policymakers, engineers, planners, GIS specialists, and graduate students as an essential reference for leveraging AI and geospatial technologies for sustainable delta management.\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e\n\u003cp\u003e\u003cstrong\u003eDr. Shubham Mahajan\u003c\/strong\u003e, a distinguished member of prestigious organizations such as IEEE, ACM, and IAENG, boasts an impressive academic and professional background. He earned his B.Tech. degree from Baba Ghulam Shah Badshah University, his M.Tech. degree from Chandigarh University, his Ph.D. degree from Shri Mata Vaishno Devi University (SMVDU) in Katra, India. Currently, he serves as an Assistant Professor at Amity University, Haryana. \u003c\/p\u003e\r\n\u003cp\u003e\u003cstrong\u003eDr. Mahajan\u003c\/strong\u003e has a remarkable track record in the field of artificial intelligence and image processing, holding an impressive portfolio of eighteen Indian patents, as well as one Australian and one German patent. His contributions to the field are further evidenced by his extensive publication record, which includes over 88 articles published in peer-reviewed journals and conferences and 8 edited books. His research interests span a wide array of topics, encompassing image processing, video compression, image segmentation, fuzzy entropy, nature-inspired computing methods, optimization, data mining, machine learning, robotics, and optical communication. Notably, his dedication and expertise have earned him the 'Best Research Paper Award' from ICRIC 2019, published by Springer in the LNEE series.\u003c\/p\u003e\r\n\u003cp\u003e\u003cstrong\u003eDr. Amit Kant Pandit\u003c\/strong\u003e received his B. Tech in 1999 from IET Bareilly. He has completed his Ph.D. from Shri Mata Vaishno Devi University in 2009. He is currently working as Professor and is Ex-Hod, DECE, in Shri Mata Vaishno Devi University (SMVDU), Katra (India). He has authored\/co-authored more than 84 publications including peer-reviewed journals and conferences. He has two Indian and one Australian Patent to his credit in the area of artificial intelligence and image processing. He is a Senior member of IEEE and MIR labs member and has 22 years of academic experience. He is Ex Joint secretary IEEE India CS Conference and workshop Committee, Ex EC nominated member IEEE Delhi section Technical Director MIR Labs, Board member Walnut Technologies Bangalore. His main research interests are image processing, video compression, image segmentation, fuzzy entropy, nature-inspired computing methods with applications in optimization. He is also in the review panel of number of peer-reviewed journals and conferences.\u003cbr\u003e \u003cbr\u003e\u003cstrong\u003eDr. Kamal Upreti\u003c\/strong\u003e is currently working as an Associate Professor in Department of Computer Science, CHRIST (Deemed to be University), Delhi NCR, Ghaziabad, India. He completed is B. Tech (Hons) Degree from UPTU, M. Tech (Gold Medalist), PGDM(Executive) from IMT Ghaziabad and PhD in Department of Computer Science \u0026amp; Engineering. He has completed Postdoc from National Taipei University of Business, TAIWAN funded by MHRD.\u003cbr\u003e \u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e11 January 2027\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eSpringer Nature Switzerland\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eSpringer\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9783032331328\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003eHardback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Springer Nature Switzerland","offers":[{"title":"Default Title","offer_id":50805825831052,"sku":"9783032331328","price":179.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9783032331328.jpg?v=1781793060","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9783032331328","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}