Investigating Public Facility Characteristics from a Spatial Interaction Perspective: A Case Study of Beijing Hospitals Using Taxi Data
Services provided by public facilities are essential to people’s lives and are closely associated with human mobility. Traditionally, public facility access characteristics, such as accessibility, equity issues and service areas, are investigated mainly based on static data (census data, travel surv...
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doaj-5db8a714564647778a6f959b519c56cb2020-11-25T01:09:34ZengMDPI AGISPRS International Journal of Geo-Information2220-99642017-02-01623810.3390/ijgi6020038ijgi6020038Investigating Public Facility Characteristics from a Spatial Interaction Perspective: A Case Study of Beijing Hospitals Using Taxi DataXiaoqing Kong0Yu Liu1Yuxia Wang2Daoqin Tong3Jing Zhang4College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, ChinaInstitute of Remote Sensing and Geographical Information Systems, Peking University, Beijing 100871, ChinaInstitute of Remote Sensing and Geographical Information Systems, Peking University, Beijing 100871, ChinaSchool of Geography and Development, The University of Arizona, Tucson, AZ 85721, USACollege of Resources Environment and Tourism, Capital Normal University, Beijing 100048, ChinaServices provided by public facilities are essential to people’s lives and are closely associated with human mobility. Traditionally, public facility access characteristics, such as accessibility, equity issues and service areas, are investigated mainly based on static data (census data, travel surveys and particular records, such as medical records). Currently, the advent of big data offers an unprecedented opportunity to obtain large-scale human mobility data, which can be used to study the characteristics of public facilities from the spatial interaction perspective. Intuitively, spatial interaction characteristics and service areas of different types and sizes of public facilities are different, but how different remains an open question, so we, in turn, examine this question. Based on spatial interaction, we classify public facilities and explore the differences in facilities. In the research, based on spatial interaction extracted from taxi data, we introduce an unsupervised classification method to classify 78 hospitals in 6 districts of Beijing, and the results better reflect the type of hospital. The findings are of great significance for optimizing the spatial configuration of medical facilities or other types of public facilities, allocating public resources reasonably and relieving traffic pressure.http://www.mdpi.com/2220-9964/6/2/38spatial interactionhospital service areapublic facility characteristicsclassificationtaxi dataBeijing |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xiaoqing Kong Yu Liu Yuxia Wang Daoqin Tong Jing Zhang |
spellingShingle |
Xiaoqing Kong Yu Liu Yuxia Wang Daoqin Tong Jing Zhang Investigating Public Facility Characteristics from a Spatial Interaction Perspective: A Case Study of Beijing Hospitals Using Taxi Data ISPRS International Journal of Geo-Information spatial interaction hospital service area public facility characteristics classification taxi data Beijing |
author_facet |
Xiaoqing Kong Yu Liu Yuxia Wang Daoqin Tong Jing Zhang |
author_sort |
Xiaoqing Kong |
title |
Investigating Public Facility Characteristics from a Spatial Interaction Perspective: A Case Study of Beijing Hospitals Using Taxi Data |
title_short |
Investigating Public Facility Characteristics from a Spatial Interaction Perspective: A Case Study of Beijing Hospitals Using Taxi Data |
title_full |
Investigating Public Facility Characteristics from a Spatial Interaction Perspective: A Case Study of Beijing Hospitals Using Taxi Data |
title_fullStr |
Investigating Public Facility Characteristics from a Spatial Interaction Perspective: A Case Study of Beijing Hospitals Using Taxi Data |
title_full_unstemmed |
Investigating Public Facility Characteristics from a Spatial Interaction Perspective: A Case Study of Beijing Hospitals Using Taxi Data |
title_sort |
investigating public facility characteristics from a spatial interaction perspective: a case study of beijing hospitals using taxi data |
publisher |
MDPI AG |
series |
ISPRS International Journal of Geo-Information |
issn |
2220-9964 |
publishDate |
2017-02-01 |
description |
Services provided by public facilities are essential to people’s lives and are closely associated with human mobility. Traditionally, public facility access characteristics, such as accessibility, equity issues and service areas, are investigated mainly based on static data (census data, travel surveys and particular records, such as medical records). Currently, the advent of big data offers an unprecedented opportunity to obtain large-scale human mobility data, which can be used to study the characteristics of public facilities from the spatial interaction perspective. Intuitively, spatial interaction characteristics and service areas of different types and sizes of public facilities are different, but how different remains an open question, so we, in turn, examine this question. Based on spatial interaction, we classify public facilities and explore the differences in facilities. In the research, based on spatial interaction extracted from taxi data, we introduce an unsupervised classification method to classify 78 hospitals in 6 districts of Beijing, and the results better reflect the type of hospital. The findings are of great significance for optimizing the spatial configuration of medical facilities or other types of public facilities, allocating public resources reasonably and relieving traffic pressure. |
topic |
spatial interaction hospital service area public facility characteristics classification taxi data Beijing |
url |
http://www.mdpi.com/2220-9964/6/2/38 |
work_keys_str_mv |
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