Urban Development Detection Along the Transportation Corridors of the Mongolian Plateau Supported by SDGSAT-1 NTL Data

Conducting urbanization monitoring at key nodes of the Mongolian Plateau holds significant importance for evaluating the economic and social development of cities within the China–Mongolia–Russia transportation corridor. These cities are sparsely distributed in the vast grassland areas, posing challenges for detecting urban changes in the transboundary regions. This study proposes a method for characterizing urban development supported by multi-source remote sensing data, including nighttime light (NTL) data with superior resolution, focusing on 11 major cities along the China-Mongolia-Russia Economic Corridor within the Mongolian Plateau. A City Development Index (CDI) is introduced, utilizing “information entropy” with the entropy weight method. The development status of 11 cities in the study area was analyzed using fractal dimensions, compactness, index of economy, index of social development, and the CDI. Results show Baotou has the highest CDI (0.82), followed by Hohhot (0.77), Ordos (0.73), and Ulanqab (0.66). In contrast, Mongolian cities exhibit significantly lower CDIs, relatively. The capital, Ulaanbaatar, has a CDI of 0.63, while no other Mongolian city exceeds 0.60, correlating with scattered populations. The results indicate that Inner Mongolia and Mongolia exhibit different geographical features in urban development. This approach provides a quantitative method for detecting and assessing urban development of the arid and semi-arid regions using NTL satellite data.

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Publication Details

Journal
Remote Sensing
Published
2026-07-17
DOI
https://doi.org/10.3390/rs18142380
Primary Topic
Impact of Light on Environment and Health
Type
article
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article

Urban Development Detection Along the Transportation Corridors of the Mongolian Plateau Supported by SDGSAT-1 NTL Data

Congrong Li, Juanle Wang, Z X Sun, Wulan Tuya et al.
Remote Sensing
Impact of Light on Environment and Health
article

Urban Development Detection Along the Transportation Corridors of the Mongolian Plateau Supported by SDGSAT-1 NTL Data

Congrong Li, Juanle Wang, Z X Sun, Wulan Tuya, Jinbao Jiang
article en

Abstract

Conducting urbanization monitoring at key nodes of the Mongolian Plateau holds significant importance for evaluating the economic and social development of cities within the China–Mongolia–Russia transportation corridor. These cities are sparsely distributed in the vast grassland areas, posing challenges for detecting urban changes in the transboundary regions. This study proposes a method for characterizing urban development supported by multi-source remote sensing data, including nighttime light (NTL) data with superior resolution, focusing on 11 major cities along the China-Mongolia-Russia Economic Corridor within the Mongolian Plateau. A City Development Index (CDI) is introduced, utilizing “information entropy” with the entropy weight method. The development status of 11 cities in the study area was analyzed using fractal dimensions, compactness, index of economy, index of social development, and the CDI. Results show Baotou has the highest CDI (0.82), followed by Hohhot (0.77), Ordos (0.73), and Ulanqab (0.66). In contrast, Mongolian cities exhibit significantly lower CDIs, relatively. The capital, Ulaanbaatar, has a CDI of 0.63, while no other Mongolian city exceeds 0.60, correlating with scattered populations. The results indicate that Inner Mongolia and Mongolia exhibit different geographical features in urban development. This approach provides a quantitative method for detecting and assessing urban development of the arid and semi-arid regions using NTL satellite data.

Remote SensingVol. 18(14)
Chinese Academy of Sciences (CN), Inner Mongolia Normal University (CN), China University of Mining and Technology (CN), Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application (CN), Institute of Geographic Sciences and Natural Resources Research (CN), University of Chinese Academy of Sciences (CN)
Sustainable cities and communities
Openalex Percentile: Top 10%
Impact of Light on Environment and Health
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