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Open AccessArticle

A Moment-Based Shape Similarity Measurement for Areal Entities in Geographical Vector Data

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School of Remote Sensing and Information Engineering, Wuhan University, No. 129 Luoyu Road, Wuhan 430079, China
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Zhejiang Academy of Surveying & Mapping, Zhejiang Innovation Base of Surveying and Mapping, West wen’er Road, Yuhang District, Hangzhou 310012, China
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College of Resources and Environmental Sciences, Hunan Normal University, No. 36 Lushan Road, Changsha 410081, China
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Key Laboratory of Geospatial Big Data Mining and Application, Hunan Province, No. 36 Lushan Road, Changsha 410081, China
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Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2018, 7(6), 208; https://doi.org/10.3390/ijgi7060208
Received: 16 March 2018 / Revised: 19 May 2018 / Accepted: 27 May 2018 / Published: 31 May 2018
Shape similarity measurement model is often used to solve shape-matching problems in geospatial data matching. It is widely used in geospatial data integration, conflation, updating and quality assessment. Many shape similarity measurements apply only to simple polygons. However, areal entities can be represented either by simple polygons, holed polygons or multipolygons in geospatial data. This paper proposes a new shape similarity measurement model that can be used for all kinds of polygons. In this method, convex hulls of polygons are used to extract boundary features of entities and local moment invariants are calculated to extract overall shape features of entities. Combined with convex hull and local moment invariants, polygons can be represented by convex hull moment invariant curves. Then, a shape descriptor is obtained by applying fast Fourier transform to convex hull moment invariant curves, and shape similarity between areal entities is measured by the shape descriptor. Through similarity measurement experiments of different lakes in multiple representations and matching experiments between two urban area datasets, results showed that the method could distinguish areal entities even if they are represented by different kinds of polygons. View Full-Text
Keywords: similarity measurement; geographical vector data; moment invariants; convex hull similarity measurement; geographical vector data; moment invariants; convex hull
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Fu, Z.; Fan, L.; Yu, Z.; Zhou, K. A Moment-Based Shape Similarity Measurement for Areal Entities in Geographical Vector Data. ISPRS Int. J. Geo-Inf. 2018, 7, 208.

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