书目名称 | Digital Mapping of Soil Landscape Parameters | 副标题 | Geospatial Analyses | 编辑 | Pradeep Kumar Garg,Rahul Dev Garg,Hari Shanker Sri | 视频video | | 概述 | Provides a framework for model development for key parameters, below, at and above the surface.Presents color images for better visual interpretation and learning.Includes sample satellite images for | 丛书名称 | Studies in Big Data | 图书封面 |  | 描述 | .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 sm | 出版日期 | Book 2020 | 关键词 | Digital Mapping; Soil-landscape Parameters; Prediction Model; Environmental Covariates; Remote Sensing a | 版次 | 1 | doi | https://doi.org/10.1007/978-981-15-3238-2 | isbn_softcover | 978-981-15-3240-5 | isbn_ebook | 978-981-15-3238-2Series ISSN 2197-6503 Series E-ISSN 2197-6511 | issn_series | 2197-6503 | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
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