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Titlebook: Handbook of Big Geospatial Data; Martin Werner,Yao-Yi Chiang Book 2021 Springer Nature Switzerland AG 2021 Algorithms for Big Data.Geograp

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書目名稱Handbook of Big Geospatial Data
編輯Martin Werner,Yao-Yi Chiang
視頻videohttp://file.papertrans.cn/421/420876/420876.mp4
概述Covers current research in accessible language including references to the field, and therefore provides an ideal collection to explore the field of big geospatial data.Spans across traditionally isol
圖書封面Titlebook: Handbook of Big Geospatial Data;  Martin Werner,Yao-Yi Chiang Book 2021 Springer Nature Switzerland AG 2021 Algorithms for Big Data.Geograp
描述.This handbook covers a wide range of topics related to the collection, processing, analysis, and use of geospatial data in their various forms. This handbook provides an overview of how spatial computing technologies for big data can be organized and implemented to solve real-world problems. Diverse subdomains ranging from indoor mapping and navigation over trajectory computing to earth observation from space, are also present in this handbook. It combines fundamental contributions focusing on spatio-textual analysis, uncertain databases, and spatial statistics with application examples such as road network detection or colocation detection using GPUs. In summary, this handbook gives an essential introduction and overview of the rich field of spatial information science and big geospatial data.?.It introduces three different perspectives, which together define the field of big geospatial data: a societal, governmental, and governance perspective. It discusses questions ofhow the acquisition, distribution and exploitation of big geospatial data must be organized both on the scale of companies and countries. A second perspective is a theory-oriented set of contributions on arbitrary
出版日期Book 2021
關鍵詞Algorithms for Big Data; Geographic Information Science; Uncertain Databases; Spatial Databases; Histori
版次1
doihttps://doi.org/10.1007/978-3-030-55462-0
isbn_softcover978-3-030-55464-4
isbn_ebook978-3-030-55462-0
copyrightSpringer Nature Switzerland AG 2021
The information of publication is updating

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Atoms, Small, and Large Molecules,ntaining geo-referenced attributes can be considered big geospatial data. The increased proliferation of big geospatial data is currently reforming the geospatial industry into a data-driven enterprise. Challenges in the big spatial data domain can be summarized as the ‘Big Vs’ – variety, volume, ve
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Alhussein Albarbar,Canras Batunlu such as Statistical and Mapping Agencies. Together, these public institutions publish territorial statistics that are of utmost importance for policy-makers to conduct various analyses of their jurisdiction, in time and space, and observe its evolution over time. However, through times, all over th
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Reliability Assessment of TBCs, recent years, the widespread adoption of location-aware technologies such as the GPS-enabled smartphones amass flow data at individual level, along with much finer spatiotemporal granularity and abundant semantic information. The increasing availability of big spatial flow has brought us with unpre
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Outdoor Education and Thermal Comfortin a database system. Such a trajectory contains a sequence of time-stamped locations and a set of descriptive attributes. Multi-attribute trajectories mainly deal with attributes describing characteristics of objects, i.e., attributes that are not relevant to locations. This differs from semantic a
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K. V. Rao,Sigurds Arajs,D. Abukayon. Traditional methods of map vector data generation based on surveyor’s field work and map digitalization are costly and have a long update period. In the Big Data age, large-scale GPS-enabled taxi trajectories and high-volume ride-sharing datasets are increasingly available. These datasets provid
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