NDLI: Comparing the Use of Spatially Explicit Indicators and Conventional Indicators in the Evaluation of Healthy Cities: A Case Study in Shenzhen, China

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Comparing the Use of Spatially Explicit Indicators and Conventional Indicators in the Evaluation of Healthy Cities: A Case Study in Shenzhen, China

Content Provider	MDPI
Author	Yang, Jun Luo, Xiangyu Xiao, Yixiong Shen, Shaoqing Su, Mo Bai, Yuqi Gong, Peng
Copyright Year	2020
Description	Various indicator systems have been developed to monitor and assess healthy cities. However, few of them contain spatially explicit indicators. In this study, we assessed four health determinants in Shenzhen, China, using both indicators commonly included in healthy city indicator systems and spatially explicit indicators. The spatially explicit indicators were developed using detailed building information or social media data. Our results showed that the evaluation results of districts and sub-districts in Shenzhen based on spatially explicit indicators could be positively, negatively, or not associated with the evaluation results based on conventional indicators. The discrepancy may be caused by the different information contained in the two types of indicators. The spatially explicit indicators measure the quantity of the determinants and the spatial accessibility of these determinants, while the conventional indicators only measure the quantity. Our results also showed that social media data have great potential to represent the high-resolution population distribution required to estimate spatially explicit indicators. Based on our findings, we recommend that spatially explicit indicators should be included in healthy city indicator systems to allow for a more comprehensive assessment of healthy cities.
Starting Page	7409
e-ISSN	16604601
DOI	10.3390/ijerph17207409
Journal	International Journal of Environmental Research and Public Health
Issue Number	20
Volume Number	17
Language	English
Publisher	MDPI
Publisher Date	2020-10-12
Access Restriction	Open
Subject Keyword	International Journal of Environmental Research and Public Health Social Sciences, Interdisciplinary Indicator System Health Cities Evaluation Spatial Distance Social Media Data
Content Type	Text
Resource Type	Article

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