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Article

An Improved Method of Determining Human Population Distribution Based on Luojia 1-01 Nighttime Light Imagery and Road Network Data—A Case Study of the City of Shenzhen

1
Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Received: 16 August 2020 / Revised: 29 August 2020 / Accepted: 2 September 2020 / Published: 4 September 2020
(This article belongs to the Special Issue Distributed and Remote Sensing of the Urban Environment)
Previously published studies on population distribution were based on the provincial level, while the number of urban-level studies is more limited. In addition, the rough spatial resolution of traditional nighttime light (NTL) data has limited their fine application in current small-scale population distribution research. For the purpose of studying the spatial distribution of populations at the urban scale, we proposed a new index (i.e., the road network adjusted human settlement index, RNAHSI) by integrating Luojia 1-01 (LJ 1-01) NTL data, the enhanced vegetation index (EVI), and road network density (RND) data based on population density relationships to depict the spatial distribution of urban human settlements. The RNAHSI updated the high-resolution NTL data and combined the RND data on the basis of human settlement index (HSI) data to refine the spatial pattern of urban population distribution. The results indicated that the mean relative error (MRE) between the population estimation data based on the RNAHSI and the demographic data was 34.80%, which was lower than that in the HSI and WorldPop dataset. This index is suitable primarily for the study of urban population distribution, as the RNAHSI can clearly highlight human activities in areas with dense urban road networks and can refine the spatial heterogeneity of impervious areas. In addition, we also drew a population density map of the city of Shenzhen with a 100 m spatial resolution for 2018 based on the RNAHSI, which has great reference significance for urban management and urban resource allocation. View Full-Text
Keywords: urban population distribution; road network density; nighttime light imagery; Luojia 1-01 data; human settlement index urban population distribution; road network density; nighttime light imagery; Luojia 1-01 data; human settlement index
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MDPI and ACS Style

Zhou, Q.; Zheng, Y.; Shao, J.; Lin, Y.; Wang, H. An Improved Method of Determining Human Population Distribution Based on Luojia 1-01 Nighttime Light Imagery and Road Network Data—A Case Study of the City of Shenzhen. Sensors 2020, 20, 5032. https://0-doi-org.brum.beds.ac.uk/10.3390/s20185032

AMA Style

Zhou Q, Zheng Y, Shao J, Lin Y, Wang H. An Improved Method of Determining Human Population Distribution Based on Luojia 1-01 Nighttime Light Imagery and Road Network Data—A Case Study of the City of Shenzhen. Sensors. 2020; 20(18):5032. https://0-doi-org.brum.beds.ac.uk/10.3390/s20185032

Chicago/Turabian Style

Zhou, Qiang, Yuanmao Zheng, Jinyuan Shao, Yinglun Lin, and Haowei Wang. 2020. "An Improved Method of Determining Human Population Distribution Based on Luojia 1-01 Nighttime Light Imagery and Road Network Data—A Case Study of the City of Shenzhen" Sensors 20, no. 18: 5032. https://0-doi-org.brum.beds.ac.uk/10.3390/s20185032

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