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Mapping Urban Villages in China: Progress and Challenges

Rui Cao, Wei Tu, Dongsheng Chen, Wenyu Zhang

TL;DR

This article addresses the lack of geospatial data for urban villages in China by conducting the first systematic review of mapping progress, data sources, and methodologies. It synthesizes 28 studies up to May 2024, highlighting a strong bias toward a few megacities, reliance on VHR imagery and online maps, and a shift from traditional feature engineering to deep learning for boundary delineation. The authors identify key challenges—conceptual fuzziness, fragmented boundaries, data availability, scalability, transferability, and ethical concerns—and propose directions including unified standards, multisource data fusion, public benchmarks, and crowdsourcing. The work advances understanding of urban village mapping in China and provides knowledge to support global informal settlements mapping and SDG 11 goals.

Abstract

The shift toward high-quality urbanization has brought increased attention to the issue of "urban villages", which has become a prominent social problem in China. However, there is a lack of available geospatial data on urban villages, making it crucial to prioritize urban village mapping. In order to assess the current progress in urban village mapping and identify challenges and future directions, we have conducted a comprehensive review, which to the best of our knowledge is the first of its kind in this field. Our review begins by providing a clear context for urban villages and elaborating the method for literature review, then summarizes the study areas, data sources, and approaches used for urban village mapping in China. We also address the challenges and future directions for further research. Through thorough investigation, we find that current studies only cover very limited study areas and periods and lack sufficient investigation into the scalability, transferability, and interpretability of identification approaches due to the challenges in concept fuzziness and variances, spatial heterogeneity and variances of urban villages, and data availability. Future research can complement and further the current research in the following potential directions in order to achieve large-area mapping across the whole nation...

Mapping Urban Villages in China: Progress and Challenges

TL;DR

This article addresses the lack of geospatial data for urban villages in China by conducting the first systematic review of mapping progress, data sources, and methodologies. It synthesizes 28 studies up to May 2024, highlighting a strong bias toward a few megacities, reliance on VHR imagery and online maps, and a shift from traditional feature engineering to deep learning for boundary delineation. The authors identify key challenges—conceptual fuzziness, fragmented boundaries, data availability, scalability, transferability, and ethical concerns—and propose directions including unified standards, multisource data fusion, public benchmarks, and crowdsourcing. The work advances understanding of urban village mapping in China and provides knowledge to support global informal settlements mapping and SDG 11 goals.

Abstract

The shift toward high-quality urbanization has brought increased attention to the issue of "urban villages", which has become a prominent social problem in China. However, there is a lack of available geospatial data on urban villages, making it crucial to prioritize urban village mapping. In order to assess the current progress in urban village mapping and identify challenges and future directions, we have conducted a comprehensive review, which to the best of our knowledge is the first of its kind in this field. Our review begins by providing a clear context for urban villages and elaborating the method for literature review, then summarizes the study areas, data sources, and approaches used for urban village mapping in China. We also address the challenges and future directions for further research. Through thorough investigation, we find that current studies only cover very limited study areas and periods and lack sufficient investigation into the scalability, transferability, and interpretability of identification approaches due to the challenges in concept fuzziness and variances, spatial heterogeneity and variances of urban villages, and data availability. Future research can complement and further the current research in the following potential directions in order to achieve large-area mapping across the whole nation...

Paper Structure

This paper contains 26 sections, 4 equations, 3 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Terminology and context of "urban villages"
  3. Review Methodology
  4. Study areas and data for urban village mapping
  5. Studied cities
  6. Data sources
  7. Ground-truth data
  8. Approaches for urban village mapping
  9. Remote sensing-based approaches
  10. Classification-oriented approaches
  11. Segmentation-oriented approaches
  12. Summary
  13. Multisource data-based approaches
  14. Classification-oriented approaches
  15. Segmentation-oriented approaches
  16. ...and 11 more sections

Figures (3)

  • Figure 1: Typical examples of urban villages in four mega-cities in China. Both the satellite and street view images are sourced from Baidu Maps (2023). Boundaries of the urban villages in these cities, identified based on government documents and field surveys, are marked with red dashed lines in the satellite images.
  • Figure 2: Number of publications per year related to urban village mapping in China. The publication venues have been categorized into four classes according to research fields, i.e., Urban Studies, GIS and Remote Sensing, AI and Big Data, and Agricultural Studies. (The annual number of publications reflects data collected up to May 2024.)
  • Figure 3: Statistics of publications from geographic perspective. (a) Spatial distribution of studied cities and top 20 most populous mega-cities in China. (Note: Mega-cities are divided according to the resident population of urban areas, and the data comes from the 2022 Urban Construction Statistics Yearbook of the Ministry of Housing and Urban-Rural Development in China). (b) Number of publications for studied cities. (Note: Research may encompass either entire cities or specific areas within cities.)