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Big Data Computing for Geospatial Applications

dc.contributor.editorLi, Zhenlong
dc.contributor.editorTang, Wenwu
dc.contributor.editorHuang, Qunying
dc.contributor.editorShook, Eric
dc.contributor.editorGuan, Qingfeng
dc.date.accessioned2021-05-01T15:46:51Z
dc.date.available2021-05-01T15:46:51Z
dc.date.issued2020
dc.identifierONIX_20210501_9783039432448_1075
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/69329
dc.description.abstractThe convergence of big data and geospatial computing has brought forth challenges and opportunities to Geographic Information Science with regard to geospatial data management, processing, analysis, modeling, and visualization. This book highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates opportunities for using big data for geospatial applications. Crucial to the advancements highlighted in this book is the integration of computational thinking and spatial thinking and the transformation of abstract ideas and models to concrete data structures and algorithms.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: generalen_US
dc.subject.classificationthema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geographyen_US
dc.subject.othertask
dc.subject.otherworkflow
dc.subject.othergeospatial problem-solving
dc.subject.otherknowledge base
dc.subject.othersocial media
dc.subject.otherbig data
dc.subject.otherfine-grained emotion classification
dc.subject.otherspatio-temporal analysis
dc.subject.otherhazard mitigation
dc.subject.othermissing road
dc.subject.othercity blocks
dc.subject.othertopology
dc.subject.otherbig mobile navigation trajectory data
dc.subject.othergeographic knowledge representation
dc.subject.othergeographic knowledge graph
dc.subject.otherformalization
dc.subject.otherGeoKG
dc.subject.otheroverlay analysis
dc.subject.othershape complexity
dc.subject.othermassive data
dc.subject.othercloud
dc.subject.otherparallel computing
dc.subject.othergeovisual analytics
dc.subject.othermachine learning
dc.subject.othersmart card data
dc.subject.othertransit corridor
dc.subject.othermobility community
dc.subject.othertrip
dc.subject.otherCA Markov
dc.subject.otherland-use change prediction
dc.subject.otherHadoop
dc.subject.otherMapReduce
dc.subject.othercloud computing
dc.subject.otherETL
dc.subject.otherELT
dc.subject.othersensor data
dc.subject.otherIoT
dc.subject.othergeospatial big data
dc.subject.otherclimate science
dc.subject.othermetadata
dc.subject.otherweb cataloging service
dc.subject.otherbig geospatial data
dc.subject.othergeospatial cyberinfrastructure
dc.subject.othertopographic surface
dc.subject.otherterrain modeling
dc.subject.otherglobal terrain dataset
dc.subject.othergeospatial computing
dc.subject.othercyberGIS
dc.subject.otherGeoAI
dc.subject.otherspatial thinking
dc.titleBig Data Computing for Geospatial Applications
dc.typebook
oapen.identifier.doi10.3390/books978-3-03943-245-5
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0
oapen.relation.isbn9783039432448
oapen.relation.isbn9783039432455
oapen.pages222
oapen.place.publicationBasel, Switzerland


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