ArticleNational science review2026
Deep-learning-based sub-meter urban construction-site mapping reveals China's dual-track urban renewal.
Article in National science review, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
China's New-Type Urbanization Plan since 2015-the world's largest urbanization endeavor-reshapes the nation's socioeconomic landscape but lacks high-precision, fine-scale progress monitoring. Urban construction sites (UCSs)-barometers of urban spatial expansion and renewal-offer a detailed observational window. A sub-meter-resolution deep-learning framework for nationwide UCS mapping is proposed. Using a Segment Anything Model-enabled weakly supervised method for pixel-level UCS annotation, a spectral-texture dual-branch segmentation network with 94.3% overall accuracy identifies 541 177 UCSs (including 10-m² micro-sites) across 372 cities. K-means clustering partitions cities into four typologies, uncovering a dual-track parallel pattern (incremental expansion + stock optimization) vs the classical 'growth-decline-renewal' trajectory. Spatial analysis shows that UCS construction correlates with annual PM₂.₅ concentrations; green dust-proof net coverage (<10%) fails to curb pollution. The framework serves as a 'microscope' for evaluating new-type urbanization and supports sustainable planning.
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