Isbn: 9789811532405 - digital mapping of soil landscape parameters: geospatial analyses using machine learning and geomatics: 72 (studies in big data) (10 resultados)

Digital Mapping of Soil Landscape Parameters: Geospatial Analyses using Machine Learning and Geomatics (Studies in Big Data, 72)
Garg, Pradeep Kumar; Garg, Rahul Dev; Shukla, Gaurav; Srivastava, Hari Shanker
Idioma: Inglés
Editorial: Springer, 2021
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Digital Mapping of Soil Landscape Parameters: Geospatial Analyses using Machine Learning and Geomatics (Studies in Big Data)
Garg, Pradeep Kumar; Garg, Rahul Dev; Shukla, Gaurav; Srivastava, Hari Shanker
Idioma: Inglés
Editorial: Springer, 2021
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Digital Mapping of Soil Landscape Parameters: Geospatial Analyses Using Machine Learning and Geomatics
Garg, Pradeep Kumar/ Garg, Rahul Dev/ Shukla, Gaurav/ Srivastava, Hari Shanker
Idioma: Inglés
Editorial: Springer Nature, 2021
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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Paperback. Condición: Brand New. 164 pages. 9.25x6.10x0.39 inches. In Stock.

Idioma: Inglés
Editorial: Springer, 2021
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Idioma: Inglés
Editorial: Springer Nature Singapore, Springer Nature Singapore Feb 2021, 2021
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 164 pp. Englisch.…

Digital Mapping of Soil Landscape Parameters: Geospatial Analyses Using Machine Learning and Geomatics
Pradeep Kumar Garg|Rahul Dev Garg|Gaurav Shukla|Hari Shanker Srivastava
Idioma: Inglés
Editorial: Springer Singapore, 2021
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Librería: moluna, Greven, Alemaniamoluna
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 practical applications.…

Idioma: Inglés
Editorial: Palgrave Macmillan, 2021
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.…

Idioma: Inglés
Editorial: Springer, Springer Feb 2021, 2021
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 164 pp. Englisch.…

Digital Mapping of Soil Landscape Parameters: Geospatial Analyses using Machine Learning and Geomatics (Studies in Big Data)
Garg, Pradeep Kumar; Garg, Rahul Dev; Shukla, Gaurav; Srivastava, Hari Shanker
Idioma: Inglés
Editorial: Springer, 2021
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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Digital Mapping of Soil Landscape Parameters: Geospatial Analyses using Machine Learning and Geomatics (Studies in Big Data)
Garg, Pradeep Kumar; Garg, Rahul Dev; Shukla, Gaurav; Srivastava, Hari Shanker
Idioma: Inglés
Editorial: Springer, 2021
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 241,94
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