Identification of the urban functional regions considering the potential context of interest points
The exploration of urban functional structure plays an important role in understanding urban and urban planning. POI(point of interest) data, as a representative of urban facilities, is widely used to extract urban functional areas. In the past, most of the researches on urban functional areas only...
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doaj-1c5095fb453e4fd8906d534da6d62b2a2020-11-25T03:48:29ZzhoSurveying and Mapping PressActa Geodaetica et Cartographica Sinica1001-15951001-15952020-07-0149790792010.11947/j.AGCS.2020.2019031520200711Identification of the urban functional regions considering the potential context of interest pointsCHEN Zhanlong0ZHOU Lulin1YU Wenhao2WU Liang3XIE Zhong4School of Geography and Information Engineering, China University of Geoscience, Wuhan 430074, ChinatSchool of Geography and Information Engineering, China University of Geoscience, Wuhan 430074, ChinatSchool of Geography and Information Engineering, China University of Geoscience, Wuhan 430074, ChinatSchool of Geography and Information Engineering, China University of Geoscience, Wuhan 430074, ChinatSchool of Geography and Information Engineering, China University of Geoscience, Wuhan 430074, ChinatThe exploration of urban functional structure plays an important role in understanding urban and urban planning. POI(point of interest) data, as a representative of urban facilities, is widely used to extract urban functional areas. In the past, most of the researches on urban functional areas only considered POI statistical information. However, they ignored the abundant spatial distribution characteristics of POI, which are closely related to regional functions. Therefore, we firstly use spatial co-location pattern mining to mine the potential context of POI, extract the spatial distribution information of POI, construct regional feature vectors, and carries out the regional clustering through the clustering algorithm. Then we use the POI class ratio and residents’ travel characteristics to identify the clustering results. We experimented our method on the core urban functional areas of Beijing, the results, which were verified with Baidu Map and residents’ travel characteristics, showed that they can identify urban functional areas with obvious characteristics, such as mature entertainment business areas, science and education cultural areas, residential areas, etc. We also proved the superiority of our method compared with the LDA method based on POI semantic information and the Word2Vec method considering the linear spatial relationship of POI.http://html.rhhz.net/CHXB/html/2020-7-907.htmurban functional area identificationcontextual relationshippoint of interestspatial co-location modebeijing |
collection |
DOAJ |
language |
zho |
format |
Article |
sources |
DOAJ |
author |
CHEN Zhanlong ZHOU Lulin YU Wenhao WU Liang XIE Zhong |
spellingShingle |
CHEN Zhanlong ZHOU Lulin YU Wenhao WU Liang XIE Zhong Identification of the urban functional regions considering the potential context of interest points Acta Geodaetica et Cartographica Sinica urban functional area identification contextual relationship point of interest spatial co-location mode beijing |
author_facet |
CHEN Zhanlong ZHOU Lulin YU Wenhao WU Liang XIE Zhong |
author_sort |
CHEN Zhanlong |
title |
Identification of the urban functional regions considering the potential context of interest points |
title_short |
Identification of the urban functional regions considering the potential context of interest points |
title_full |
Identification of the urban functional regions considering the potential context of interest points |
title_fullStr |
Identification of the urban functional regions considering the potential context of interest points |
title_full_unstemmed |
Identification of the urban functional regions considering the potential context of interest points |
title_sort |
identification of the urban functional regions considering the potential context of interest points |
publisher |
Surveying and Mapping Press |
series |
Acta Geodaetica et Cartographica Sinica |
issn |
1001-1595 1001-1595 |
publishDate |
2020-07-01 |
description |
The exploration of urban functional structure plays an important role in understanding urban and urban planning. POI(point of interest) data, as a representative of urban facilities, is widely used to extract urban functional areas. In the past, most of the researches on urban functional areas only considered POI statistical information. However, they ignored the abundant spatial distribution characteristics of POI, which are closely related to regional functions. Therefore, we firstly use spatial co-location pattern mining to mine the potential context of POI, extract the spatial distribution information of POI, construct regional feature vectors, and carries out the regional clustering through the clustering algorithm. Then we use the POI class ratio and residents’ travel characteristics to identify the clustering results. We experimented our method on the core urban functional areas of Beijing, the results, which were verified with Baidu Map and residents’ travel characteristics, showed that they can identify urban functional areas with obvious characteristics, such as mature entertainment business areas, science and education cultural areas, residential areas, etc. We also proved the superiority of our method compared with the LDA method based on POI semantic information and the Word2Vec method considering the linear spatial relationship of POI. |
topic |
urban functional area identification contextual relationship point of interest spatial co-location mode beijing |
url |
http://html.rhhz.net/CHXB/html/2020-7-907.htm |
work_keys_str_mv |
AT chenzhanlong identificationoftheurbanfunctionalregionsconsideringthepotentialcontextofinterestpoints AT zhoululin identificationoftheurbanfunctionalregionsconsideringthepotentialcontextofinterestpoints AT yuwenhao identificationoftheurbanfunctionalregionsconsideringthepotentialcontextofinterestpoints AT wuliang identificationoftheurbanfunctionalregionsconsideringthepotentialcontextofinterestpoints AT xiezhong identificationoftheurbanfunctionalregionsconsideringthepotentialcontextofinterestpoints |
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