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Spatial modeling in forest resources...

Shit, Pravat Kumar.

Spatial modeling in forest resources managementrural livelihood and sustainable development /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Spatial modeling in forest resources managementedited by Pravat Kumar Shit ... [et al.].
其他題名:	rural livelihood and sustainable development /
其他作者:	Shit, Pravat Kumar.
出版者:	Cham :Springer International Publishing :2021.
面頁冊數:	xix, 675 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Forest managementRemote sensing.
電子資源:	https://doi.org/10.1007/978-3-030-56542-8
ISBN:	9783030565428$q(electronic bk.)

Spatial modeling in forest resources managementrural livelihood and sustainable development /
Spatial modeling in forest resources managementrural livelihood and sustainable development /[electronic resource] :edited by Pravat Kumar Shit ... [et al.]. - Cham :Springer International Publishing :2021. - xix, 675 p. :ill., digital ;24 cm. - Environmental science and engineering,1863-5520. - Environmental science and engineering..

Forest Resources Measurement, Monitoring and Mapping -- Application of RS-GIS-R for forest resources assessment, monitoring, and modeling -- Assessment and measurement of forest resources for sustainable land use planning -- Species diversity mapping and modeling -- Afforestation -- Soil-Water-Vegetation Relationship -- Modeling, Risk Assessment, and Vulnerability -- Forest biomass and carbon stock modeling -- Remote sensing based deforestation analysis -- Forest and habitats suitability analysis -- Habitats and species modeling -- Google Earth Engine and its application in forest sciences -- Rural livelihood and Sustainable Management -- The role of timber and non-timber forest products in poverty reduction -- The role of communities in sustainable land and forest management -- Politics of co-optation: community forest management versus joint forest management -- Open source satellite data and GIS for forest resources mapping and monitoring -- Recent trends in forest resources management and land use planning.

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.

ISBN: 9783030565428$q(electronic bk.)

Standard No.: 10.1007/978-3-030-56542-8doiSubjects--Topical Terms:

774078
Forest management
--Remote sensing.

LC Class. No.: SD431 / .S63 2021

Dewey Class. No.: 634.92

Spatial modeling in forest resources managementrural livelihood and sustainable development /
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520 $a 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.
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