Geospatial Modeling For Environmental Management


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Geospatial Modeling for Environmental Management


Geospatial Modeling for Environmental Management

Author: Shruti Kanga

language: en

Publisher:

Release Date: 2022


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This is a comprehensive resource that integrates the application of innovative remote sensing techniques and geospatial tools in modeling Earth systems for environmental management beyond customary digitization and mapping practices. It identifies the most suitable approaches for a specific environmental problem, emphasizes the importance of physically based modeling, their uncertainty analysis, advantages, and disadvantages. The case studies on the Himalayas with a complex topography call for innovation in geospatial techniques to find solutions for various environmental problems. Features: Presents innovative geospatial methods in environmental modeling of Earth systems. Includes case studies from South Asia and discusses different processes and outcomes using spatially explicit models. Explains contemporary environmental problems through the analysis of various information layers. Provides good practices for developing countries to help manage environmental issues using low-cost geospatial approaches. Integrates geospatial modeling with policy and analysis its direct implication in decision making. Using a systems' approach analysis, Geospatial Modeling for Environmental Management: Case Studies from South Asia shall serve environmental managers, students, researchers, and policymakers.

Geospatial Modeling for Environmental Management


Geospatial Modeling for Environmental Management

Author: Shruti Kanga

language: en

Publisher: CRC Press

Release Date: 2022-02-15


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This is a comprehensive resource that integrates the application of innovative remote sensing techniques and geospatial tools in modeling Earth systems for environmental management beyond customary digitization and mapping practices. It identifies the most suitable approaches for a specific environmental problem, emphasizes the importance of physically based modeling, their uncertainty analysis, advantages, and disadvantages. The case studies on the Himalayas with a complex topography call for innovation in geospatial techniques to find solutions for various environmental problems. Features: Presents innovative geospatial methods in environmental modeling of Earth systems. Includes case studies from South Asia and discusses different processes and outcomes using spatially explicit models. Explains contemporary environmental problems through the analysis of various information layers. Provides good practices for developing countries to help manage environmental issues using low-cost geospatial approaches. Integrates geospatial modeling with policy and analysis its direct implication in decision making. Using a systems’ approach analysis, Geospatial Modeling for Environmental Management: Case Studies from South Asia shall serve environmental managers, students, researchers, and policymakers.

Spatial Modeling in Forest Resources Management


Spatial Modeling in Forest Resources Management

Author: Pravat Kumar Shit

language: en

Publisher: Springer Nature

Release Date: 2020-10-08


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This book demonstrates the measurement, monitoring, mapping, and modeling of forest resources. It explores state-of-the-art techniques based on open-source software & R statistical programming and modeling specifically, with a focus on the recent trends in data mining/machine learning techniques and robust modeling in forest resources. Discusses major topics such as forest health assessment, estimating forest biomass & carbon stock, land use forest cover (LUFC), dynamic vegetation modeling (DVM) approaches, forest-based rural livelihood, habitat suitability analysis, biodiversity and ecology, and biodiversity, the book presents novel advances and applications of RS-GIS and R in a precise and clear manner. By offering insights into various concepts and their importance for real-world applications, it equips researchers, professionals, and policy-makers with the knowledge and skills to tackle a wide range of issues related to geographic data, including those with scientific, societal, and environmental implications.