A Linkage Matching Method for Road Networks Considering the Similarity of Upper and Lower Spatial Relation
Existing road network matching methods mostly use the characteristics of the road's own nodes and arcs to carry on the matching process, while less attention is focused on the importance of the road neighborhood elements in the road network matching, thus affecting further improvement of the ma...
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doaj-638d6408ea4141d18c2e310aa7e4667e2020-11-24T22:07:18ZzhoSurveying and Mapping PressActa Geodaetica et Cartographica Sinica1001-15951001-15952016-11-0145111371138310.11947/j.AGCS.2016.2016006220161114A Linkage Matching Method for Road Networks Considering the Similarity of Upper and Lower Spatial RelationLIU Chuang0QIAN Haizhong1WANG Xiao2HE Haiwei3CHEN Jingnan4Institute of Geospatial Information, Information Engineering University, Zhengzhou 450052, ChinaInstitute of Geospatial Information, Information Engineering University, Zhengzhou 450052, ChinaInstitute of Geospatial Information, Information Engineering University, Zhengzhou 450052, ChinaInstitute of Geospatial Information, Information Engineering University, Zhengzhou 450052, ChinaInstitute of Geospatial Information, Information Engineering University, Zhengzhou 450052, ChinaExisting road network matching methods mostly use the characteristics of the road's own nodes and arcs to carry on the matching process, while less attention is focused on the importance of the road neighborhood elements in the road network matching, thus affecting further improvement of the matching efficiency and accuracy. In response to these problems, a linkage matching method for road network considering the similarity of upper and lower spatial relation is proposed. The linkage matching imitates the human thinking process of searching for target objects by the signal features and spatial correlation when reading maps, regarding matching as a reasoning process of goal feature searching and information association transmitting. Firstly, classify the complex road network by using Stroke technology. Secondly, establish the road network linkage matching model based on road skeleton relation tree. Finally, select the high-level road in the classifying results of the source data as the reference road to start matching, calculate the road between the upper and lower levels of the spatial relationship similarity, and through a step-by-step iteration, make the matching information transmit in the road network linkage matching model thus to obtain the final matching results. Experiment shows that the mentioned algorithm can narrow the search range of the data to be matched, effectively improving the match efficiency and accuracy, especially applicable to the data with large non systematic geometric location deviation.http://html.rhhz.net/CHXB/html/2016-11-1371.htmlinkage matchingspatial relationsStroke technologyinformation transfer |
collection |
DOAJ |
language |
zho |
format |
Article |
sources |
DOAJ |
author |
LIU Chuang QIAN Haizhong WANG Xiao HE Haiwei CHEN Jingnan |
spellingShingle |
LIU Chuang QIAN Haizhong WANG Xiao HE Haiwei CHEN Jingnan A Linkage Matching Method for Road Networks Considering the Similarity of Upper and Lower Spatial Relation Acta Geodaetica et Cartographica Sinica linkage matching spatial relations Stroke technology information transfer |
author_facet |
LIU Chuang QIAN Haizhong WANG Xiao HE Haiwei CHEN Jingnan |
author_sort |
LIU Chuang |
title |
A Linkage Matching Method for Road Networks Considering the Similarity of Upper and Lower Spatial Relation |
title_short |
A Linkage Matching Method for Road Networks Considering the Similarity of Upper and Lower Spatial Relation |
title_full |
A Linkage Matching Method for Road Networks Considering the Similarity of Upper and Lower Spatial Relation |
title_fullStr |
A Linkage Matching Method for Road Networks Considering the Similarity of Upper and Lower Spatial Relation |
title_full_unstemmed |
A Linkage Matching Method for Road Networks Considering the Similarity of Upper and Lower Spatial Relation |
title_sort |
linkage matching method for road networks considering the similarity of upper and lower spatial relation |
publisher |
Surveying and Mapping Press |
series |
Acta Geodaetica et Cartographica Sinica |
issn |
1001-1595 1001-1595 |
publishDate |
2016-11-01 |
description |
Existing road network matching methods mostly use the characteristics of the road's own nodes and arcs to carry on the matching process, while less attention is focused on the importance of the road neighborhood elements in the road network matching, thus affecting further improvement of the matching efficiency and accuracy. In response to these problems, a linkage matching method for road network considering the similarity of upper and lower spatial relation is proposed. The linkage matching imitates the human thinking process of searching for target objects by the signal features and spatial correlation when reading maps, regarding matching as a reasoning process of goal feature searching and information association transmitting. Firstly, classify the complex road network by using Stroke technology. Secondly, establish the road network linkage matching model based on road skeleton relation tree. Finally, select the high-level road in the classifying results of the source data as the reference road to start matching, calculate the road between the upper and lower levels of the spatial relationship similarity, and through a step-by-step iteration, make the matching information transmit in the road network linkage matching model thus to obtain the final matching results. Experiment shows that the mentioned algorithm can narrow the search range of the data to be matched, effectively improving the match efficiency and accuracy, especially applicable to the data with large non systematic geometric location deviation. |
topic |
linkage matching spatial relations Stroke technology information transfer |
url |
http://html.rhhz.net/CHXB/html/2016-11-1371.htm |
work_keys_str_mv |
AT liuchuang alinkagematchingmethodforroadnetworksconsideringthesimilarityofupperandlowerspatialrelation AT qianhaizhong alinkagematchingmethodforroadnetworksconsideringthesimilarityofupperandlowerspatialrelation AT wangxiao alinkagematchingmethodforroadnetworksconsideringthesimilarityofupperandlowerspatialrelation AT hehaiwei alinkagematchingmethodforroadnetworksconsideringthesimilarityofupperandlowerspatialrelation AT chenjingnan alinkagematchingmethodforroadnetworksconsideringthesimilarityofupperandlowerspatialrelation AT liuchuang linkagematchingmethodforroadnetworksconsideringthesimilarityofupperandlowerspatialrelation AT qianhaizhong linkagematchingmethodforroadnetworksconsideringthesimilarityofupperandlowerspatialrelation AT wangxiao linkagematchingmethodforroadnetworksconsideringthesimilarityofupperandlowerspatialrelation AT hehaiwei linkagematchingmethodforroadnetworksconsideringthesimilarityofupperandlowerspatialrelation AT chenjingnan linkagematchingmethodforroadnetworksconsideringthesimilarityofupperandlowerspatialrelation |
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1725820963274096640 |