Preliminary analysis of factors affecting economic well-being based on SDGSAT-1 nighttime light remote sensing and household survey data

Economic well-being is an important indicator for measuring the happiness of national residents and is of great significance for poverty assessment in the United Nations 2030 Sustainable Development Goals. Since economic well-being is a multidimensional indicator involving multiple aspects of econom...

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Main Authors: W. Jiang, J. Liu, T. Long, M. Liu, Z. Pang, G. Luo, E. Adam, X. Ding, S. Cui, C. Wen, L. Wang
Format: Article
Language:English
Published: Copernicus Publications 2025-07-01
Series:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://isprs-annals.copernicus.org/articles/X-G-2025/421/2025/isprs-annals-X-G-2025-421-2025.pdf
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author W. Jiang
J. Liu
J. Liu
T. Long
M. Liu
Z. Pang
G. Luo
E. Adam
X. Ding
S. Cui
C. Wen
L. Wang
author_facet W. Jiang
J. Liu
J. Liu
T. Long
M. Liu
Z. Pang
G. Luo
E. Adam
X. Ding
S. Cui
C. Wen
L. Wang
author_sort W. Jiang
collection DOAJ
description Economic well-being is an important indicator for measuring the happiness of national residents and is of great significance for poverty assessment in the United Nations 2030 Sustainable Development Goals. Since economic well-being is a multidimensional indicator involving multiple aspects of economic development level and individual residents' perception, its influencing factors are complex and lack empirical research. In order to explore the influencing factors of economic well-being, this study proposed an economic well-being factor analysis framework combining nighttime light remote sensing and household survey data. Taking Bazhou City, Hebei Province, China as an example, a household survey of economic well-being indicators was conducted in towns, and the spatial distribution feature of economic well-being in each town were statistically analyzed. Further, the Sustainable Development Satellite (SDGSAT-1) nighttime light remote sensing data and socioeconomic statistical data were used to conduct an analysis of the influencing factors of economic well-being. The results showed that: (1) there is spatial heterogeneity in economic well-being among towns, among which Dongduan has the highest economic well-being and Wangzhuangzi has the lowest economic well-being. The average economic well-being value of Bazhou City is 9.04; (2) A preliminary analysis of economic well-being and nighttime light remote sensing feature shows that the economic well-being of Dongduan and Tang'erli and other towns are consistent with the nighttime light remote sensing feature, but not in Bazhou and Shengfang. This indicates that the impact of economic well-being is multi-factorial, and there is no significant relationship between economic development level and economic well-being in local scale areas. This study is the first to use nighttime light remote sensing data and household survey data to analyze the factors affecting socioeconomic well-being, providing important support for subsequent large-scale global socioeconomic well-being modeling and poverty assessment. 
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spelling doaj-art-dab91eb7268c450da5aa90bc59d43e752025-08-20T02:36:06ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502025-07-01X-G-202542142610.5194/isprs-annals-X-G-2025-421-2025Preliminary analysis of factors affecting economic well-being based on SDGSAT-1 nighttime light remote sensing and household survey dataW. Jiang0J. Liu1J. Liu2T. Long3M. Liu4Z. Pang5G. Luo6E. Adam7X. Ding8S. Cui9C. Wen10L. Wang11China Institute of Water Resources and Hydropower Research, Beijing, 100038, ChinaChina Institute of Water Resources and Hydropower Research, Beijing, 100038, ChinaSchool of Architecture and Fine Art, Dalian University of Technology, 2 Linggong Road,Dalian 116024, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaSchool of Architecture and Fine Art, Dalian University of Technology, 2 Linggong Road,Dalian 116024, ChinaChina Institute of Water Resources and Hydropower Research, Beijing, 100038, ChinaChina Institute of Water Resources and Hydropower Research, Beijing, 100038, ChinaSchool of Geography, Archaeology and Environmental Studies, University of The Witwatersrand, Jan Smuts Ave, Johannesburg, South AfricaSchool of Software and Internet of Things Engineering, Jiangxi University of Finance and Economics, 665 Yuping Road, Nanchang 330013, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaEconomic well-being is an important indicator for measuring the happiness of national residents and is of great significance for poverty assessment in the United Nations 2030 Sustainable Development Goals. Since economic well-being is a multidimensional indicator involving multiple aspects of economic development level and individual residents' perception, its influencing factors are complex and lack empirical research. In order to explore the influencing factors of economic well-being, this study proposed an economic well-being factor analysis framework combining nighttime light remote sensing and household survey data. Taking Bazhou City, Hebei Province, China as an example, a household survey of economic well-being indicators was conducted in towns, and the spatial distribution feature of economic well-being in each town were statistically analyzed. Further, the Sustainable Development Satellite (SDGSAT-1) nighttime light remote sensing data and socioeconomic statistical data were used to conduct an analysis of the influencing factors of economic well-being. The results showed that: (1) there is spatial heterogeneity in economic well-being among towns, among which Dongduan has the highest economic well-being and Wangzhuangzi has the lowest economic well-being. The average economic well-being value of Bazhou City is 9.04; (2) A preliminary analysis of economic well-being and nighttime light remote sensing feature shows that the economic well-being of Dongduan and Tang'erli and other towns are consistent with the nighttime light remote sensing feature, but not in Bazhou and Shengfang. This indicates that the impact of economic well-being is multi-factorial, and there is no significant relationship between economic development level and economic well-being in local scale areas. This study is the first to use nighttime light remote sensing data and household survey data to analyze the factors affecting socioeconomic well-being, providing important support for subsequent large-scale global socioeconomic well-being modeling and poverty assessment. https://isprs-annals.copernicus.org/articles/X-G-2025/421/2025/isprs-annals-X-G-2025-421-2025.pdf
spellingShingle W. Jiang
J. Liu
J. Liu
T. Long
M. Liu
Z. Pang
G. Luo
E. Adam
X. Ding
S. Cui
C. Wen
L. Wang
Preliminary analysis of factors affecting economic well-being based on SDGSAT-1 nighttime light remote sensing and household survey data
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title Preliminary analysis of factors affecting economic well-being based on SDGSAT-1 nighttime light remote sensing and household survey data
title_full Preliminary analysis of factors affecting economic well-being based on SDGSAT-1 nighttime light remote sensing and household survey data
title_fullStr Preliminary analysis of factors affecting economic well-being based on SDGSAT-1 nighttime light remote sensing and household survey data
title_full_unstemmed Preliminary analysis of factors affecting economic well-being based on SDGSAT-1 nighttime light remote sensing and household survey data
title_short Preliminary analysis of factors affecting economic well-being based on SDGSAT-1 nighttime light remote sensing and household survey data
title_sort preliminary analysis of factors affecting economic well being based on sdgsat 1 nighttime light remote sensing and household survey data
url https://isprs-annals.copernicus.org/articles/X-G-2025/421/2025/isprs-annals-X-G-2025-421-2025.pdf
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