TY - BOOK ID - 64866012 TI - Digital Mapping of Soil Landscape Parameters : Geospatial Analyses using Machine Learning and Geomatics AU - Garg, Pradeep Kumar. AU - Garg, Rahul Dev. AU - Shukla, Gaurav. AU - Srivastava, Hari Shanker. PY - 2020 SN - 9811532389 9811532370 PB - Singapore : Springer Singapore : Imprint: Springer, DB - UniCat KW - Digital soil mapping. KW - Predictive soil mapping KW - Soil mapping KW - Computational intelligence. KW - Big data. KW - Remote sensing. KW - Computational Intelligence. KW - Big Data. KW - Remote Sensing/Photogrammetry. KW - Remote-sensing imagery KW - Remote sensing systems KW - Remote terrain sensing KW - Sensing, Remote KW - Terrain sensing, Remote KW - Aerial photogrammetry KW - Aerospace telemetry KW - Detectors KW - Space optics KW - Data sets, Large KW - Large data sets KW - Data sets KW - Intelligence, Computational KW - Artificial intelligence KW - Soft computing UR - https://www.unicat.be/uniCat?func=search&query=sysid:64866012 AB - 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. . ER -