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Geospatial Technologies for Resources Planning and Management

Title
Geospatial Technologies for Resources Planning and Management [electronic resource] / edited by Chandra Shekhar Jha, Ashish Pandey, V.M. Chowdary, Vijay Singh.
ISBN
9783030989811
Edition
1st ed. 2022.
Publication
Cham : Springer International Publishing : Imprint: Springer, 2022.
Physical Description
1 online resource (VIII, 750 p.) 378 illus., 351 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
This book focuses on the application of geospatial technologies for resource planning and management for the key natural resources, e.g. water, agriculture and forest as well as the decision support system (DSS) for infrastructure development. We have seen in the past four decades that the growing complexities of sustainable management of natural resources management have been very challenging. The book has been written to leverage the current geospatial technologies that integrate the remotely sensed data available from various platforms, the precise locational data providing geospatial intelligence, and the advanced integration tools of Geographical Information Systems (GIS). Geospatial technologies have been used for water resources management employing geomorphological characteristics, analysis of river migration pattern, understanding the large-scale hydrological process, wet land classification and monitoring, analysis of glacial lake outburst flood (GLOF), assessment of environmental flow and soil erosion studies, water quality modelling and assessment and rejuvenation of paleochannels through groundwater recharge. Geospatial technologies have been applied for crop classification and mapping, soil moisture determination using RISAT-1 C-band and PALSAR-2 L-band sensors, inventory of horticulture plantations, management of citrus orchards, crop yield forecasting, rice yield estimation, estimation of evapotranspiration and its evaluation against lysimeter and satellite-based evapotranspiration product for India to address the various issues of the agricultural system management. Geospatial technologies have been used for generation of digital elevation model, urban dynamics assessment, mobile GIS application at grass root level planning, cadastral level developmental planning and e-governance applications, system dynamics for sustainable development, micro-level water resources planning, site suitability for sewage treatment plant, traffic density assessment, geographical indications of India, archaeological applications and disasters interventions to elaborate various issues of DSS for infrastructure development and management. Geospatial technologies have been employed for the generation and reconciliation of the notified forest land boundaries, and also the land cover changes analysis within notified forest areas, forest resource assessment, management and monitoring and wildlife conservation and management. This book aims to present high-quality technical case studies representing the recent developments in the "application of geospatial technologies for resource planning and management". The editors hope that this book will serve as a valuable resource for scientists and researchers to plan and manage land and water resources sustainably.
Variant and related titles
Springer ENIN.
Other formats
Printed edition:
Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
June 07, 2022
Series
Water Science and Technology Library, 115
Water Science and Technology Library, 115
Contents
Geospatial Technology for Geomorphology Mapping and its Applications
Geospatial technology for estimation of geomorphological characteristics of an ungauged watershed
Long Term Analysis of River Migration Pattern using Geospatial Techniques - A case study of upper part of the Ganga River, India
Space borne Scatterometers for understanding the large-scale land hydrological processes
Wetland Classification and Monitoring Using Time Series Earth Observation Data and Machine Learning Algorithm: A Case Study in Upper Ganga River Stretch.
Citation

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