SDG 11.3 Assessment of African Industrial Cities by Integrating Remote Sensing and Spatial Cooperative Simulation: With MFEZ in Zambia as a Case Study

Urban areas in sub-Saharan Africa are facing significant developmental challenges due to rapid population growth and urban expansion, this study aims to predict urban growth and assess the SDG 11.3.1 indicator in the Chambishi multi-facility economic zone (CFEMZ) in Zambia through the integration of remote sensing data and spatial cooperative simulation so as to realize sustainable development goals (SDGs). The study utilized DMSP-OLS and VIIRS nighttime light data between 2000 and 2020 to extract the urban built-up area by applying the Pseudo-Invariant Features (PIFs) method to determine thresholds. The land-use and population changes under several development scenarios in 2030 were simulated in the study using the Spatial Cooperative Simulation (SCS) approach. The changes in SDG 11.3.1 indicators were also calculated in the form of a spatialized kilometer grid. The findings show a substantial rise in the built-up area and especially indicate a most notable increase in Chambishi. The primary cause of this growth is the development of industrial parks, which act as the region’s principal engine for urban expansion. Under the natural scenario, the land-use distribution in the study area presents an unplanned state that will make it difficult to realize SDGs. The results of the spatialization form of the SDG 11.3.1 indicator demonstrate the areas and problems of imbalance between urban construction and population growth in the CMFEZ. This study demonstrates the importance of remote sensing of nighttime lighting and spatial simulation in urban planning to achieve SDG 11.3.1 for sustainable urbanization in industrial cities.

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Publication Details

Journal
Remote Sensing
Published
2024-08-15
DOI
https://doi.org/10.3390/rs16162995
Citations
3
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.85

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article

SDG 11.3 Assessment of African Industrial Cities by Integrating Remote Sensing and Spatial Cooperative Simulation: With MFEZ in Zambia as a Case Study

Dongping Ming, Yuchen Huang
3 citations
Remote Sensing
Land Use and Ecosystem Services
0.85
article

SDG 11.3 Assessment of African Industrial Cities by Integrating Remote Sensing and Spatial Cooperative Simulation: With MFEZ in Zambia as a Case Study

Dongping Ming, Yuchen Huang
article en
3 citations

Abstract

Urban areas in sub-Saharan Africa are facing significant developmental challenges due to rapid population growth and urban expansion, this study aims to predict urban growth and assess the SDG 11.3.1 indicator in the Chambishi multi-facility economic zone (CFEMZ) in Zambia through the integration of remote sensing data and spatial cooperative simulation so as to realize sustainable development goals (SDGs). The study utilized DMSP-OLS and VIIRS nighttime light data between 2000 and 2020 to extract the urban built-up area by applying the Pseudo-Invariant Features (PIFs) method to determine thresholds. The land-use and population changes under several development scenarios in 2030 were simulated in the study using the Spatial Cooperative Simulation (SCS) approach. The changes in SDG 11.3.1 indicators were also calculated in the form of a spatialized kilometer grid. The findings show a substantial rise in the built-up area and especially indicate a most notable increase in Chambishi. The primary cause of this growth is the development of industrial parks, which act as the region’s principal engine for urban expansion. Under the natural scenario, the land-use distribution in the study area presents an unplanned state that will make it difficult to realize SDGs. The results of the spatialization form of the SDG 11.3.1 indicator demonstrate the areas and problems of imbalance between urban construction and population growth in the CMFEZ. This study demonstrates the importance of remote sensing of nighttime lighting and spatial simulation in urban planning to achieve SDG 11.3.1 for sustainable urbanization in industrial cities.

Remote SensingVol. 16(16)
China University of Geosciences (Beijing) (CN)
China University of Geosciences, Beijing, China University of Geosciences, Fundamental Research Funds for the Central Universities
Sustainable cities and communities
Openalex Percentile: Top 28%
Land Use and Ecosystem Services
0.85
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