SPATIO-TEMPORAL CHARACTERISTICS OF RESIDENT TRIP BASED ON POI AND OD DATA OF FLOAT CAR IN BEIJING
Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some spatio-temporal patterns (periodic patterns, gathering patterns, etc.). In order to further understand the spatial and temporal characteristics of urban residents, this...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2017-09-01
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/99/2017/isprs-archives-XLII-2-W7-99-2017.pdf |
Summary: | Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some
spatio-temporal patterns (periodic patterns, gathering patterns, etc.). In order to further understand the spatial and temporal
characteristics of urban residents, this paper research takes the taxi trajectory data of Beijing as a sample data and studies the
spatio-temporal characteristics of the residents' activities on the weekdays. At first, according to the characteristics of the taxi
trajectory data distributed along the road network, it takes the Voronoi generated by the road nodes as the research unit. This paper
proposes a hybrid clustering method – based on grid density, which is used to cluster the OD (origin and destination) data of taxi at
different times. Then,combining with the POI data of Beijing, this research calculated the density of the POI data in the clustering
results, and analyzed the relationship between the activities of residents in different periods and the functional types of the region.
The final results showed that the residents were mainly commuting on weekdays. And it found that the distribution of travel density
showed a concentric circle of the characteristics, focusing on residential areas and work areas. The results of cluster analysis and POI
analysis showed that the residents' travel had experienced the process of "spatial relative dispersion – spatial aggregation – spatial
relative dispersion" in one day. |
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ISSN: | 1682-1750 2194-9034 |