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035   $a(DE-He213)978-3-030-47998-5
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100   $a20200720d2020      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aHigh Performance Computing for Geospatial Applications /$fedited by Wenwu Tang, Shaowen Wang
205   $a1st ed. 2020.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020.
215   $a1 online resource (XIII, 296 p. 94 illus., 70 illus. in color.) 
225 1 $aGeotechnologies and the Environment,$x2365-0575 ;$v23
311   $a3-030-47997-8 
330   $aThis volume fills a research gap between the rapid development of High Performance Computing (HPC) approaches and their geospatial applications. With a focus on geospatial applications, the book discusses in detail how researchers apply HPC to tackle their geospatial problems. Based on this focus, the book identifies the opportunities and challenges revolving around geospatial applications of HPC. Readers are introduced to the fundamentals of HPC, and will learn how HPC methods are applied in various specific areas of geospatial study. The book begins by discussing theoretical aspects and methodological uses of HPC within a geospatial context, including parallel algorithms, geospatial data handling, spatial analysis and modeling, and cartography and geovisualization. Then, specific domain applications of HPC are addressed in the contexts of earth science, land use and land cover change, urban studies, transportation studies, and social science. The book will be of interest to scientists and engineers who are interested in applying cutting-edge HPC technologies in their respective fields, as well as students and faculty engaged in geography, environmental science, social science, and computer science.
410  0$aGeotechnologies and the Environment,$x2365-0575 ;$v23
606   $aRemote sensing
606   $aBig data
606   $aSociophysics
606   $aEconophysics
606   $aComputer simulation
606   $aEnvironmental sciences
606   $aLandscape ecology
606   $aRemote Sensing/Photogrammetry$3https://scigraph.springernature.com/ontologies/product-market-codes/J13010
606   $aBig Data$3https://scigraph.springernature.com/ontologies/product-market-codes/I29120
606   $aData-driven Science, Modeling and Theory Building$3https://scigraph.springernature.com/ontologies/product-market-codes/P33030
606   $aSimulation and Modeling$3https://scigraph.springernature.com/ontologies/product-market-codes/I19000
606   $aEnvironmental Science and Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/G37000
606   $aLandscape Ecology$3https://scigraph.springernature.com/ontologies/product-market-codes/L19058
615  0$aRemote sensing.
615  0$aBig data.
615  0$aSociophysics.
615  0$aEconophysics.
615  0$aComputer simulation.
615  0$aEnvironmental sciences.
615  0$aLandscape ecology.
615 14$aRemote Sensing/Photogrammetry.
615 24$aBig Data.
615 24$aData-driven Science, Modeling and Theory Building.
615 24$aSimulation and Modeling.
615 24$aEnvironmental Science and Engineering.
615 24$aLandscape Ecology.
676   $a004.35
702   $aTang$b Wenwu$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aWang$b Shaowen$4edt$4http://id.loc.gov/vocabulary/relators/edt
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910411920603321
996   $aHigh Performance Computing for Geospatial Applications$92065753
997   $aUNINA