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Digital Mapping of Soil Landscape Parameters - Geospatial Analyses using Machine Learning and Geomatics (Hardcover, 1st ed. 2020) Loot Price: R4,316
Discovery Miles 43 160
Digital Mapping of Soil Landscape Parameters - Geospatial Analyses using Machine Learning and Geomatics (Hardcover, 1st ed....

Digital Mapping of Soil Landscape Parameters - Geospatial Analyses using Machine Learning and Geomatics (Hardcover, 1st ed. 2020)

Pradeep Kumar Garg, Rahul Dev Garg, Gaurav Shukla, Hari Shanker Srivastava

Series: Studies in Big Data, 72

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Loot Price R4,316 Discovery Miles 43 160 | Repayment Terms: R404 pm x 12*

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This book addresses the mapping of soil-landscape parameters in the geospatial domain. It begins by discussing the fundamental concepts, and then explains how machine learning and geomatics can be applied for more efficient mapping and to improve our understanding and management of 'soil'. The judicious utilization of a piece of land is one of the biggest and most important current challenges, especially in light of the rapid global urbanization, which requires continuous monitoring of resource consumption. The book provides a clear overview of how machine learning can be used to analyze remote sensing data to monitor the key parameters, below, at, and above the surface. It not only offers insights into the approaches, but also allows readers to learn about the challenges and issues associated with the digital mapping of these parameters and to gain a better understanding of the selection of data to represent soil-landscape relationships as well as the complex and interconnected links between soil-landscape parameters under a range of soil and climatic conditions. Lastly, the book sheds light on using the network of satellite-based Earth observations to provide solutions toward smart farming and smart land management.

General

Imprint: Springer Verlag, Singapore
Country of origin: Singapore
Series: Studies in Big Data, 72
Release date: February 2020
First published: 2020
Authors: Pradeep Kumar Garg • Rahul Dev Garg • Gaurav Shukla • Hari Shanker Srivastava
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 142
Edition: 1st ed. 2020
ISBN-13: 978-981-15-3237-5
Categories: Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Geographical information systems (GIS)
Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Remote sensing
Books > Computing & IT > Applications of computing > Databases > General
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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LSN: 981-15-3237-0
Barcode: 9789811532375

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