This 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/As 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.PLATINUM 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:
Boundles
