Analytical Data Transformations in Space–Time Region: Three Stories of Space–Time Cube.
In this era of abundant space–time geographic information systems (GIS) data, one challenge in GIScience is to adapt and improve current GIS environments to facilitate new ways of space–time thinking and to fully exploit the information in these data. This article focuses on the use of spatiotempora...
| Publicado en: | Annals of the Association of American Geographers Vol. 103; no. 5; pp. 1100 - 1107 |
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| Formato: | Artículo |
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Taylor & Francis Ltd
Sep2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=89890970&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 89890970 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00045608 AAG jtl: Annals of the Association of American Geographers issn: 00045608 maglogo: Y pubinfo: dt: Sep2013 vid: 103 iid: 5 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 89890970 10.1080/00045608.2013.792184 ppf: 1100 ppct: 7 formats: tig: atl: Analytical Data Transformations in Space–Time Region: Three Stories of Space–Time Cube. aug: au: Nakaya, Tomoki affil: Department of Geography, Ritsumeikan University su: Geography Spacetime Geographic information systems Interpolation Data analysis Data transformations (Statistics) sug: subj: Geography Spacetime Geographic information systems Interpolation Data analysis Data transformations (Statistics) keyword: GIS space–time cube space–time thinking space–time cube space–time thinking transformative operations cubo del espacio–tiempo cubo del espacio–tiempo operaciones transformativas pensando el espacio–tiempo pensando el espacio–tiempo SIG GIS space–time cube space–time thinking space–time cube space–time thinking transformative operations cubo del espacio–tiempo cubo del espacio–tiempo operaciones transformativas pensando el espacio–tiempo pensando el espacio–tiempo SIG ab: In this era of abundant space–time geographic information systems (GIS) data, one challenge in GIScience is to adapt and improve current GIS environments to facilitate new ways of space–time thinking and to fully exploit the information in these data. This article focuses on the use of spatiotemporal data transformations using the construct of a space–time cube, which is a space–time coordinate space with geographical horizontal axes and a temporal vertical axis. I have chosen three examples in which the concept of space–time cubes is applied to different themes and on different scales to illustrate how diverse subjects can be interpreted with space–time analysis and transformations of space–time data. The transformation functions, such as space–time overlays, interpolation, and surface operations, can be understood as natural extensions of popular analytical operations already present in current GIS and should be intrinsic in the next generation of GIS to handle the dense space–time information that is available to us. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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