Cargando…

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

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 populatio...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhou, Qiang, Zheng, Yuanmao, Shao, Jinyuan, Lin, Yinglun, Wang, Haowei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570547/
https://www.ncbi.nlm.nih.gov/pubmed/32899875
http://dx.doi.org/10.3390/s20185032
_version_ 1783596971940904960
author Zhou, Qiang
Zheng, Yuanmao
Shao, Jinyuan
Lin, Yinglun
Wang, Haowei
author_facet Zhou, Qiang
Zheng, Yuanmao
Shao, Jinyuan
Lin, Yinglun
Wang, Haowei
author_sort Zhou, Qiang
collection PubMed
description 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.
format Online
Article
Text
id pubmed-7570547
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-75705472020-10-28 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 Zhou, Qiang Zheng, Yuanmao Shao, Jinyuan Lin, Yinglun Wang, Haowei Sensors (Basel) Article 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. MDPI 2020-09-04 /pmc/articles/PMC7570547/ /pubmed/32899875 http://dx.doi.org/10.3390/s20185032 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhou, Qiang
Zheng, Yuanmao
Shao, Jinyuan
Lin, Yinglun
Wang, Haowei
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570547/
https://www.ncbi.nlm.nih.gov/pubmed/32899875
http://dx.doi.org/10.3390/s20185032
work_keys_str_mv AT zhouqiang animprovedmethodofdetermininghumanpopulationdistributionbasedonluojia101nighttimelightimageryandroadnetworkdataacasestudyofthecityofshenzhen
AT zhengyuanmao animprovedmethodofdetermininghumanpopulationdistributionbasedonluojia101nighttimelightimageryandroadnetworkdataacasestudyofthecityofshenzhen
AT shaojinyuan animprovedmethodofdetermininghumanpopulationdistributionbasedonluojia101nighttimelightimageryandroadnetworkdataacasestudyofthecityofshenzhen
AT linyinglun animprovedmethodofdetermininghumanpopulationdistributionbasedonluojia101nighttimelightimageryandroadnetworkdataacasestudyofthecityofshenzhen
AT wanghaowei animprovedmethodofdetermininghumanpopulationdistributionbasedonluojia101nighttimelightimageryandroadnetworkdataacasestudyofthecityofshenzhen
AT zhouqiang improvedmethodofdetermininghumanpopulationdistributionbasedonluojia101nighttimelightimageryandroadnetworkdataacasestudyofthecityofshenzhen
AT zhengyuanmao improvedmethodofdetermininghumanpopulationdistributionbasedonluojia101nighttimelightimageryandroadnetworkdataacasestudyofthecityofshenzhen
AT shaojinyuan improvedmethodofdetermininghumanpopulationdistributionbasedonluojia101nighttimelightimageryandroadnetworkdataacasestudyofthecityofshenzhen
AT linyinglun improvedmethodofdetermininghumanpopulationdistributionbasedonluojia101nighttimelightimageryandroadnetworkdataacasestudyofthecityofshenzhen
AT wanghaowei improvedmethodofdetermininghumanpopulationdistributionbasedonluojia101nighttimelightimageryandroadnetworkdataacasestudyofthecityofshenzhen