Weakly supervised mapping of old and renewed urban areas in China during the recent two decades,International Journal of Applied Earth Observation and Geoinformation

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Weakly supervised mapping of old and renewed urban areas in China during the recent two decades
International Journal of Applied Earth Observation and Geoinformation ( IF 7.6 ) Pub Date : 2024-09-12 , DOI: 10.1016/j.jag.2024.104125
Hao Ni , Le Yu , Peng Gong

China has progressively elevated old city transformation and urban renewal to a policy priority, positioning them as new endogenous drivers of urban development. It raises the demand for real-time insight into the spatiotemporal distribution of old and renewed urban areas. We propose a weakly supervised mapping framework with adaptive adjustments city by city without relying on high-precision training samples. It is also convenient for variable spatial range and study period. We combined Landsat imagery during 2000–2021, LandTrendr change detection algorithm and Simple Non-Iterative Clustering image segmentation into a Threshold Voting approach. The overall accuracy and Kappa coefficient of our results are 78.37 % and 0.57, respectively, with interesting global and local patterns. Old urban areas cluster in the early developed city centers, accounting for 22.55 % nationwide, usually interspersed and surrounded with renewed urban areas (77.45 %). Our mapping framework provides an efficient and flexible scheme for ground history detection, and the related results can be applied as helpful references for urban renewal field work in China.

更新日期：2024-09-12

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