Application Of Remote Sensing And Gis In Natural Resources And Built Infrastructure Management

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Application of Remote Sensing and GIS in Natural Resources and Built Infrastructure Management

Application of Remote Sensing and GIS in Natural Resources and Built Infrastructure Management
Author :
Publisher : Springer Nature
Total Pages : 409
Release :
ISBN-10 : 9783031140969
ISBN-13 : 3031140966
Rating : 4/5 (966 Downloads)

Book Synopsis Application of Remote Sensing and GIS in Natural Resources and Built Infrastructure Management by : Vijay P. Singh

Download or read book Application of Remote Sensing and GIS in Natural Resources and Built Infrastructure Management written by Vijay P. Singh and published by Springer Nature. This book was released on 2023-01-01 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the problems in planning, building, and management strategies in the wake of application and expansion of remote sensing and GIS products in natural resources and infrastructure management. The book suggests proactive solutions to problems of natural resources and infrastructure management, providing alternatives for strategic planning, effective delivery, and growth perspectives. The uniqueness of the book is its broader spectrum of coverage with related interconnections and interdependences across science, engineering, and innovation. The book contains information that can be downscaled to the local level. Presenting a wide spectrum of viewpoints and approaches, the book is a collective of topics such as application to agriculture and forestry (land and landscape, agriculture, forestry management and deforestation), water resources and ecology (hydro-meteorological, climate diagnostics, and prognostics, water resources management, environment management, cross-scale ecology and resilience), urban management (urban planning, design, construction and operations of infrastructure, natural disasters, novel approaches to upgrade old infrastructure), hydro informatics, predictive and geospatial data analytics, synthesis, and management through the various processes, tools, and technologies.


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