Generalization of GIS polygon data using curvature-based approach

Chi Farn Chen, Min Hsin Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations


Generalization is a procedure used extensively in GIS data reduction, where polygon shape generalization is considered the most complicated. Since most of polygon generalization methods need to convert the polygon to the poly-lines, the generalized result is significantly affected by the decision of the starting point, which is required in initiating the poly-line generalization algorithm. The purpose of this study is to develop a curvature-based generalization technique for polygon GIS data. Curvature is an obvious characteristic of a curve and it can be used to represent the curve quantitatively. In this study, the shape's feature points which with relatively large curvature are detected initially. Then the original polygon can be separated into several curves by the feature points and each curve will be simplified respectively. In order to reach different stage of the simplification, a shape distortion index is used as a criterion to decide those data points should be preserved. An experiment is performed to compare the proposed method with the Douglas-Peucker method. The comparisons show that the proposed method has better simplified result and less distorted shape both visually and quantitatively than Douglas and Peucker method.

Original languageEnglish
Title of host publication25th Anniversary IGARSS 2005
Subtitle of host publicationIEEE International Geoscience and Remote Sensing Symposium
Number of pages4
StatePublished - 2005
Event2005 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005 - Seoul, Korea, Republic of
Duration: 25 Jul 200529 Jul 2005

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)


Conference2005 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005
Country/TerritoryKorea, Republic of


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