Spatial Techniques for Soil Erosion Estimation: Remote Sensing and GIS Approach

Author:   Rupesh Jayaram Patil
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2018
ISBN:  

9783319742854


Pages:   81
Publication Date:   16 February 2018
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Spatial Techniques for Soil Erosion Estimation: Remote Sensing and GIS Approach


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Overview

This book presents a novel computation of the topographic LS factor of the USLE model to estimate spatial soil erosion. In developing countries, soil erosion is one of the main concerns as it adversely affects agriculture and reduces food production. Therefore, the author presents a particularly relevant approach, as he demonstrates how the C++ programming allows us to identify important erosion stages like detachment and deposition. He does this by assessing the annual rate of soil erosion from the Shakkar River watershed in India using distributed information and applying RS and GIS techniques. He also discusses different approaches that have been proposed to work out the influence of topography on erosion. Simulated and observed data of sediment loss are compared for the period 1992 to 2006.This book provides an easy-to-understand basic piece of soil erosion and hydrological research and reaches out to young researchers and students at the graduate and undergraduate levelas well as applicants of soil erosion models.

Full Product Details

Author:   Rupesh Jayaram Patil
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2018
Weight:   0.454kg
ISBN:  

9783319742854


ISBN 10:   331974285
Pages:   81
Publication Date:   16 February 2018
Audience:   College/higher education ,  College/higher education ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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