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Titlebook: Earth Data Analytics for Planetary Health; Tzai-Hung Wen,Ting-Wu Chuang,Mathuros Tipayamongkh Book 2023 The Editor(s) (if applicable) and

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發(fā)表于 2025-3-21 17:21:24 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Earth Data Analytics for Planetary Health
編輯Tzai-Hung Wen,Ting-Wu Chuang,Mathuros Tipayamongkh
視頻videohttp://file.papertrans.cn/301/300831/300831.mp4
概述Gives a practical introduction and applications of earth data analytics.Provides a broad focus on measuring the mechanisms of planetary health.Highlights the issue of environmental health in Southeast
叢書名稱Atmosphere, Earth, Ocean & Space
圖書封面Titlebook: Earth Data Analytics for Planetary Health;  Tzai-Hung Wen,Ting-Wu Chuang,Mathuros Tipayamongkh Book 2023 The Editor(s) (if applicable) and
描述Planetary health involves complex spatial–temporal interactions among agents, hosts, and earth environment. Due to rapid technical development of geomatics, including geographic information systems (GIS) and remote sensing (RS) in the era of big data analytics, therefore, earth data analytics has become one of the important approaches for monitoring earth surface process and measuring of the effects of environment changes on all humans and other living organisms on earth. Various methods in earth data analytics, including spatial–temporal statistics, spatial evolutionary algorithms, remote sensing image analysis, wireless geo-sensors, and location-based analytics, are an emerging discipline in understanding complex interactions in planetary health. This edited book provides a broad focus on methodological theories of earth data analytics and their applications to measuring the process of planetary health, with the goal to build scientific understanding on how geospatial analytics can provide valuable insights in measuring environmental risks in Southeast Asian regions. It is collection of selected papers covering both theoretical and empirical studies focusing on topics relevant to
出版日期Book 2023
關(guān)鍵詞Geographic Information System (GIS); Earth Data Analytics; Remote Sensing; Spatial Analysis; Planetary H
版次1
doihttps://doi.org/10.1007/978-981-19-8765-6
isbn_softcover978-981-19-8767-0
isbn_ebook978-981-19-8765-6Series ISSN 2524-440X Series E-ISSN 2524-4418
issn_series 2524-440X
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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Detecting Urban form Using Remote Sensing: Spatiotemporal Research Gaps for Sustainable Environment and human well-being. In this chapter, we synthesize 376 peer-reviewed studies on urban land cover, building density, three-dimensional (3-D) structure, and land use using remote sensing approaches. We evaluated the sources of data, detection methods, as well as the spatiotemporal characteristics (
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