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...
Autores principales: | , , , , |
---|---|
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 |