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Urban construction sites (UCSs)\u2014barometers of urban spatial expansion and renewal\u2014offer 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\u2013texture dual-branch segmentation network with 94.3% overall accuracy identifies 541\u2009177 UCSs (including 10-m\u00b2 micro-sites) across 372 cities. K-means clustering partitions cities into four typologies, uncovering a dual-track parallel pattern (incremental expansion\u00a0+\u00a0stock optimization) vs the classical \u2018growth\u2013decline\u2013renewal\u2019 trajectory. Spatial analysis shows that UCS construction correlates with annual PM\u2082.\u2085 concentrations; green dust-proof net coverage (&amp;lt;10%) fails to curb pollution. The framework serves as a \u2018microscope\u2019 for evaluating new-type urbanization and supports sustainable planning.<\/jats:p>","DOI":"10.1093\/nsr\/nwag141","type":"journal-article","created":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T18:42:33Z","timestamp":1773168153000},"source":"Crossref","is-referenced-by-count":2,"title":["Deep-learning-based sub-meter urban construction-site mapping reveals China\u2019s dual-track urban renewal"],"prefix":"10.1093","volume":"13","author":[{"given":"Jiayi","family":"Li","sequence":"first","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University , Wuhan 430079 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenrui","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University , Wuhan 430079 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