Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/79947
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorChen, PF-
dc.creatorShi, WZ-
dc.date.accessioned2018-12-21T07:14:00Z-
dc.date.available2018-12-21T07:14:00Z-
dc.identifier.urihttp://hdl.handle.net/10397/79947-
dc.language.isoenen_US
dc.publisherMolecular Diversity Preservation International (MDPI)en_US
dc.rights© 2018 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 (http://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Chen, P. F., & Shi, W. Z. (2018). Measuring the spatial relationship information of multi-layered vector data. ISPRS International Journal of Geo-Information, 7(3), 88, 1-16 is available at https://dx.doi.org/10.3390/ijgi7030088en_US
dc.subjectSpatial informationen_US
dc.subjectMulti-layered vector dataen_US
dc.subjectSpatial relationshipen_US
dc.subjectEntropyen_US
dc.subjectQuantitative measurementen_US
dc.titleMeasuring the spatial relationship information of multi-layered vector dataen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1en_US
dc.identifier.epage16en_US
dc.identifier.volume7en_US
dc.identifier.issue3en_US
dc.identifier.doi10.3390/ijgi7030088en_US
dcterms.abstractGeospatial data is a carrier of information that represents the geography of the real world. Measuring the information contents of geospatial data is always a hot topic in spatial-information science. As the main type of geospatial data, spatial vector data models provide an effective framework for encoding spatial relationships and manipulating spatial data. In particular, the spatial relationship information of vector data is a complicated problem but meaningful to help human beings evaluate the complexity of spatial data and thus guide further analysis. However, existing measures of spatial information usually focus on the 'disjointed' relationship in one layer and cannot cover the various spatial relationships within the multi-layered structure of vector data. In this study, a new method is proposed to measure the spatial relationship information of multi-layered vector data. The proposed method focuses on spatial distance and topological relationships and provides quantitative measurements by extending the basic thought of Shannon's entropy. The influence of any vector feature is modeled by introducing the concept of the energy field, and the energy distribution of one layer is described by an energy map and a weight map. An operational process is also proposed to measure the overall information content. Two experiments are conducted to validate the proposed method. In the experiment with real-life data, the proposed method shows the efficiency of the quantification of spatial relationship information under a multi-layered structure. In another experiment with simulated data, the characteristics and advantages of our method are demonstrated through a comparison with classical measurements.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationISPRS international journal of geo-information, Mar. 2018, v. 7, no. 3, 88, p. 1-16-
dcterms.isPartOfISPRS international journal of geo-information-
dcterms.issued2018-
dc.identifier.isiWOS:000428557700009-
dc.identifier.scopus2-s2.0-85044503476-
dc.identifier.eissn2220-9964en_US
dc.identifier.artn88en_US
dc.identifier.rosgroupid2017002376-
dc.description.ros2017-2018 > Academic research: refereed > Publication in refereed journal-
dc.description.validate201812 bcrcen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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