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Digital
Geospatial Data Science in Healthcare for Society 5.0
Authors: --- --- ---
ISBN: 9789811694769 9789811694752 9789811694776 9789811694783 Year: 2022 Publisher: Singapore Springer Nature

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Abstract

The book introduces a variety of latest techniques designed to represent, enhance, and empower multi-disciplinary approaches of geographic information system (GIS), artificial intelligence (AI), deep learning (DL), machine learning, and cloud computing research in healthcare. It provides a unique compendium of the current and emerging use of geospatial data for healthcare and reflects the diversity, complexity, and depth and breadth of this multi-disciplinary area. This book addresses various aspects of how smart healthcare devices can be used to detect and analyze diseases. Further, it describes various tools and techniques to evaluate the efficacy, suitability, and efficiency of geospatial data for health-related applications. It features illustrative case studies, including future applications and healthcare challenges. This book is beneficial for computer science and engineering students and researchers, medical professionals, and anyone interested in using geospatial data in healthcare. It is also intended for experts, offering them a valuable retrospective and a global vision for the future, as well as for non-experts who are curious to learn about this important subject. The book presents an effort to draw how we can build health-related applications using geospatial big data and their subsequent analysis.


Book
Digital Mapping of Soil Landscape Parameters : Geospatial Analyses using Machine Learning and Geomatics
Authors: --- --- ---
ISBN: 9811532389 9811532370 Year: 2020 Publisher: Singapore : Springer Singapore : Imprint: Springer,

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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. .


Book
Digital Mapping of Soil Landscape Parameters
Authors: --- --- --- ---
ISBN: 9789811532382 Year: 2020 Publisher: Singapore Springer Singapore :Imprint: Springer

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Abstract


Book
Geospatial Data Science in Healthcare for Society 5.0
Authors: --- --- --- ---
ISBN: 9789811694769 9789811694752 9789811694776 9789811694783 Year: 2022 Publisher: Singapore Springer Nature Singapore :Imprint: Springer


Digital
Digital Mapping of Soil Landscape Parameters : Geospatial Analyses using Machine Learning and Geomatics
Authors: --- --- ---
ISBN: 9789811532382 Year: 2020 Publisher: Singapore Springer Singapore, Imprint: Springer

Loading...
Export citation

Choose an application

Bookmark

Abstract

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. .

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