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dc.contributor.authorStruhár, Juraj
dc.contributor.authorRapant, Petr
dc.date.accessioned2023-03-28T13:20:56Z
dc.date.available2023-03-28T13:20:56Z
dc.date.issued2022
dc.identifier.citationRemote Sensing. 2022, vol. 14, issue 9, art. no. 2184.cs
dc.identifier.issn2072-4292
dc.identifier.urihttp://hdl.handle.net/10084/149230
dc.description.abstractThe space–time series carry information on temporal and spatial patterns in observed phenomena. The reported research integrates computational, visual and cartographic methods to support visual analysis of space–time series describing terrain surface movement. The proposed methodology for space–time series visualisation can support their analysts in investigating space– time patterns using transformation, clustering, filtration and visualisation. The presented approach involves spiral graphs for representation time dimension and cartographic visualisation through proportional point symbol map for representation of spatial dimension. The result is an intuitive visualisation of space–time series, conveying the sought-after spatio-temporal information. For practical tests, we used space–time series obtained by permanent scatterers interferometry (PS InSAR) to monitor the Earth’s surface movement above the underground gas storage (UGS) Tvrdonice, the Czech Republic. An UGS is characterised by periodic injection and withdrawal of natural gas, which induces periodic movement of the terrain above it. We have verified that our visualisation method provides the required pattern information and is easy to use.cs
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofseriesRemote Sensingcs
dc.relation.urihttps://doi.org/10.3390/rs14092184cs
dc.rights© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjecttime seriescs
dc.subjectspace–time seriescs
dc.subjectPS InSARcs
dc.subjectvisualisationcs
dc.subjectvisual analyticscs
dc.subjectspiral graphcs
dc.titleSpatiotemporal visualisation of PS InSAR generated space–time series describing large areal land deformations using diagram map with spiral graphcs
dc.typearticlecs
dc.identifier.doi10.3390/rs14092184
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume14cs
dc.description.issue9cs
dc.description.firstpageart. no. 2184cs
dc.identifier.wos000794741700001


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© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Except where otherwise noted, this item's license is described as © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.