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dc.contributor.authorLei, Ting
dc.contributor.authorYang, Wenjun
dc.date.accessioned2020-03-24T20:04:52Z
dc.date.available2020-03-24T20:04:52Z
dc.date.issued2019-11-13
dc.identifier.urihttp://hdl.handle.net/1808/30157
dc.descriptionThis presentation was given as part of the GIS Day@KU symposium on November 13, 2019. For more information about GIS Day@KU activities, please see http://gis.ku.edu/gisday/2019/en_US
dc.description.abstractAs a critical data management task, conflation in GIS aims to determine the corresponding features from different datasets that in reality represent the same entities. This is called feature matching, which is used as a guidance to merge attributes of corresponding features between datasets. Based on the classification of features, there are point, polyline, and polygon matching methods. This study focuses on matching polygons and explores optimization–based matching methods for conflating two datasets.en_US
dc.description.sponsorshipPLATINUM SPONSORS: KU Department of Geography and Atmospheric Science KU Institute for Policy & Social Research

GOLD SPONSORS: KU Libraries State of Kansas Data Access & Support Center (DASC)

SILVER SPONSORS: Bartlett & West Kansas Applied Remote Sensing Program KU Center for Global and International Studies

BRONZE SPONSORS: Boundless
en_US
dc.publisherGIS Day @ KU Planning Committeeen_US
dc.relation.isversionofhttp://gis.ku.edu/gisday/2019/en_US
dc.subjectGIS Dayen_US
dc.titleAn Optimization-based Matching Method and its Application in Merging Administrative Boundary Dataen_US
dc.typePresentationen_US
kusw.kuauthorLei, Ting
kusw.kuauthorYang, Wenjun
kusw.kudepartmentGeography and Atmosphere Scieneen_US
kusw.oastatusna
dc.rights.accessrightsopenAccessen_US


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