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Land degradation in Indialinkages wi...

Priya, Ratan.

Land degradation in Indialinkages with deforestation, climate and agriculture /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Land degradation in Indiaby Ratan Priya.
Reminder of title:	linkages with deforestation, climate and agriculture /
Author:	Priya, Ratan.
Published:	Cham :Springer International Publishing :2021.
Description:	vii, 111 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Land degradationStatistical methods.India
Online resource:	https://doi.org/10.1007/978-3-030-68848-6
ISBN:	9783030688486$q(electronic bk.)

Land degradation in Indialinkages with deforestation, climate and agriculture /
Priya, Ratan.

Land degradation in Indialinkages with deforestation, climate and agriculture /[electronic resource] :by Ratan Priya. - Cham :Springer International Publishing :2021. - vii, 111 p. :ill., digital ;24 cm. - SpringerBriefs in environmental science,2191-5547. - SpringerBriefs in environmental science..

Chapter1. Introduction -- Chapter2. Land Degradation: Indian Scenario -- Chapter3. Land Degradation in India: Relationship with Deforestation and Population -- Chapter4. Land Degradation in India and Propinquity with Rainfall -- Chapter5. Land Degradation and Agricultural Productivity -- Chapter6. Land Degradation: Reclamation and Policy Adaptation.

This book discusses land degradation in India using statistical tools such as Principal Component Analysis (PCA) and Regression Analysis (RA), and uses statistical analyses and graphical representations of the causal relationship between land degradation and land productivity to determine linkages with deforestation, climate change and agricultural productivity. While most studies of land degradation in India focus on economic outcomes and physical processes at macro and micro levels, this study addresses land degradation at the meso-level to fill in this gap and provide up-to-date information on often overlooked factors associated with land degradation issues using the latest available data. Districts in the study were selected by land degradation intensity, forming an index of the severity of land degradation in the area, with a focus on gullied lands, soil salinity/alkalinity and open and dense scrubs as indicators. Though the study areas are in India, researchers, policy makers and students around the world will be able to learn from these inputs regarding land degradation to address various challenges associated with sustainable land management and agricultural productivity.

ISBN: 9783030688486$q(electronic bk.)

Standard No.: 10.1007/978-3-030-68848-6doiSubjects--Topical Terms:

893504
Land degradation
--Statistical methods.--India

LC Class. No.: GE160.I4 / P759 2021

Dewey Class. No.: 333.71370954

Land degradation in Indialinkages with deforestation, climate and agriculture /
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520 $a This book discusses land degradation in India using statistical tools such as Principal Component Analysis (PCA) and Regression Analysis (RA), and uses statistical analyses and graphical representations of the causal relationship between land degradation and land productivity to determine linkages with deforestation, climate change and agricultural productivity. While most studies of land degradation in India focus on economic outcomes and physical processes at macro and micro levels, this study addresses land degradation at the meso-level to fill in this gap and provide up-to-date information on often overlooked factors associated with land degradation issues using the latest available data. Districts in the study were selected by land degradation intensity, forming an index of the severity of land degradation in the area, with a focus on gullied lands, soil salinity/alkalinity and open and dense scrubs as indicators. Though the study areas are in India, researchers, policy makers and students around the world will be able to learn from these inputs regarding land degradation to address various challenges associated with sustainable land management and agricultural productivity.
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