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How Good Are Global Layers for Mapping Rural Settlements? Evidence from China

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  • Ningcheng Wang

    (Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
    School of Geographic Sciences, East China Normal University, Shanghai 200241, China
    Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities (Ministry of Natural Resources), Shanghai 200241, China)

  • Xinyi Zhang

    (Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
    School of Geographic Sciences, East China Normal University, Shanghai 200241, China
    Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities (Ministry of Natural Resources), Shanghai 200241, China)

  • Shenjun Yao

    (Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
    School of Geographic Sciences, East China Normal University, Shanghai 200241, China
    Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities (Ministry of Natural Resources), Shanghai 200241, China
    Research Center for China Administrative Division, East China Normal University, Shanghai 200241, China)

  • Jianping Wu

    (Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
    School of Geographic Sciences, East China Normal University, Shanghai 200241, China
    Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities (Ministry of Natural Resources), Shanghai 200241, China)

  • Haibin Xia

    (Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
    School of Geographic Sciences, East China Normal University, Shanghai 200241, China
    Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities (Ministry of Natural Resources), Shanghai 200241, China)

Abstract

Global urbanization has brought about a significant transition to rural areas. With the development of remote sensing technologies, land use/land cover (LULC) datasets allow users to analyze the changes in global rural settlements. However, few studies have examined the performances of the LULC datasets in mapping rural settlements. Taking China as the study area, this research selected eight of the latest LULC datasets (ESRI Land Cover, WSF, ESA WorldCover, GHS-BUILT-S2, GISD30, GISA2.0, GLC30, and GAIA) to compare their accuracy for rural settlement detection. Spatial stratified sampling was used for collecting and sampling rural settlements. We conducted omission tests, area comparison, and pixel-based accuracy tests for comparison. The results show that: (1) the performances of the 10 m resolution datasets are better than those of the 30 m resolution datasets in almost all scenarios. (2) the mapping of villages in Western China is a challenge for all datasets. (3) GHS-BUILT-S2 performs the best in almost every scenario, and can allow users to adjust the threshold value for determining a proper range of rural settlement size; ESRI outperforms any other dataset in detecting the existence of rural settlements, but it dramatically overestimates the area of rural settlements. (4) GISD30 is the best among the 30 m resolution datasets, notably in the Pearl River Delta. Finally, we provide useful suggestions on ideal map selection in various regions and scenarios.

Suggested Citation

  • Ningcheng Wang & Xinyi Zhang & Shenjun Yao & Jianping Wu & Haibin Xia, 2022. "How Good Are Global Layers for Mapping Rural Settlements? Evidence from China," Land, MDPI, vol. 11(8), pages 1-21, August.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:8:p:1308-:d:887744
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    References listed on IDEAS

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    1. Kairui Guo & Yong Huang & Dan Chen, 2022. "Analysis of the Expansion Characteristics of Rural Settlements Based on Scale Growth Function in Himalayan Region," Land, MDPI, vol. 11(3), pages 1-17, March.
    2. Elena Gorbenkova & Elena Shcherbina, 2020. "Historical-Genetic Features in Rural Settlement System: A Case Study from Mogilev District (Mogilev Oblast, Belarus)," Land, MDPI, vol. 9(5), pages 1-17, May.
    3. Tian, Guangjin & Qiao, Zhi & Zhang, Yaoqi, 2012. "The investigation of relationship between rural settlement density, size, spatial distribution and its geophysical parameters of China using Landsat TM images," Ecological Modelling, Elsevier, vol. 231(C), pages 25-36.
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    5. R. Dunn & A. R. Harrison, 1993. "Two‐Dimensional Systematic Sampling of Land Use," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 42(4), pages 585-601, December.
    6. Lynne Seymour, 2005. "Spatial Data Analysis: Theory and Practice. Robert Haining," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 353-354, March.
    7. Chen Jun & Yifang Ban & Songnian Li, 2014. "Open access to Earth land-cover map," Nature, Nature, vol. 514(7523), pages 434-434, October.
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    1. Andreas Braun & Gebhard Warth & Felix Bachofer & Michael Schultz & Volker Hochschild, 2023. "Mapping Urban Structure Types Based on Remote Sensing Data—A Universal and Adaptable Framework for Spatial Analyses of Cities," Land, MDPI, vol. 12(10), pages 1-41, October.

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