Shape Similarity Assessment Method for Coastline Generalization

Although shape similarity is one fundamental element in coastline generalization quality, its related research is still inadequate. Consistent with the hierarchical pattern of shape recognition, the Dual-side Bend Forest Shape Representation Model is presented by reorganizing the coastline into bila...

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Main Authors: Zhaoxing Li, Jingsheng Zhai, Fang Wu
Format: Article
Language:English
Published: MDPI AG 2018-07-01
Series:ISPRS International Journal of Geo-Information
Subjects:
Online Access:http://www.mdpi.com/2220-9964/7/7/283
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spelling doaj-9ec3eb8feeb342d8abe02c91c0119af22020-11-25T01:03:14ZengMDPI AGISPRS International Journal of Geo-Information2220-99642018-07-017728310.3390/ijgi7070283ijgi7070283Shape Similarity Assessment Method for Coastline GeneralizationZhaoxing Li0Jingsheng Zhai1Fang Wu2Zhengzhou Institute of Surveying and Mapping, Zhengzhou 450000, ChinaSchool of Marine Science and Technology, Tianjin University, Tianjin 300072, ChinaZhengzhou Institute of Surveying and Mapping, Zhengzhou 450000, ChinaAlthough shape similarity is one fundamental element in coastline generalization quality, its related research is still inadequate. Consistent with the hierarchical pattern of shape recognition, the Dual-side Bend Forest Shape Representation Model is presented by reorganizing the coastline into bilateral bend forests, which are made of continuous root-bends based on Constrained Delaunay Triangulation and Convex Hull. Subsequently, the shape contribution ratio of each level in the model is expressed by its area distribution in the model. Then, the shape similarity assessment is conducted on the model in a top–down layer by layer pattern. Contrast experiments are conducted among the presented method and the Length Ratio, Hausdorff Distance and Turning Function, showing the improvements of the presented method over the others, including (1) the hierarchical shape representation model can distinguish shape features of different layers on dual-side effectively, which is consistent with shape recognition, (2) its usability and stability among coastlines and scales, and (3) it is sensitive to changes in main shape features caused by coastline generalization.http://www.mdpi.com/2220-9964/7/7/283coastlinegeneralization qualityshape similarityconstrained Delaunay trianglebend
collection DOAJ
language English
format Article
sources DOAJ
author Zhaoxing Li
Jingsheng Zhai
Fang Wu
spellingShingle Zhaoxing Li
Jingsheng Zhai
Fang Wu
Shape Similarity Assessment Method for Coastline Generalization
ISPRS International Journal of Geo-Information
coastline
generalization quality
shape similarity
constrained Delaunay triangle
bend
author_facet Zhaoxing Li
Jingsheng Zhai
Fang Wu
author_sort Zhaoxing Li
title Shape Similarity Assessment Method for Coastline Generalization
title_short Shape Similarity Assessment Method for Coastline Generalization
title_full Shape Similarity Assessment Method for Coastline Generalization
title_fullStr Shape Similarity Assessment Method for Coastline Generalization
title_full_unstemmed Shape Similarity Assessment Method for Coastline Generalization
title_sort shape similarity assessment method for coastline generalization
publisher MDPI AG
series ISPRS International Journal of Geo-Information
issn 2220-9964
publishDate 2018-07-01
description Although shape similarity is one fundamental element in coastline generalization quality, its related research is still inadequate. Consistent with the hierarchical pattern of shape recognition, the Dual-side Bend Forest Shape Representation Model is presented by reorganizing the coastline into bilateral bend forests, which are made of continuous root-bends based on Constrained Delaunay Triangulation and Convex Hull. Subsequently, the shape contribution ratio of each level in the model is expressed by its area distribution in the model. Then, the shape similarity assessment is conducted on the model in a top–down layer by layer pattern. Contrast experiments are conducted among the presented method and the Length Ratio, Hausdorff Distance and Turning Function, showing the improvements of the presented method over the others, including (1) the hierarchical shape representation model can distinguish shape features of different layers on dual-side effectively, which is consistent with shape recognition, (2) its usability and stability among coastlines and scales, and (3) it is sensitive to changes in main shape features caused by coastline generalization.
topic coastline
generalization quality
shape similarity
constrained Delaunay triangle
bend
url http://www.mdpi.com/2220-9964/7/7/283
work_keys_str_mv AT zhaoxingli shapesimilarityassessmentmethodforcoastlinegeneralization
AT jingshengzhai shapesimilarityassessmentmethodforcoastlinegeneralization
AT fangwu shapesimilarityassessmentmethodforcoastlinegeneralization
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