用大模型生成中国342城高精度城中村地图，助力城市治理与可持续发展。
A high-resolution nationwide urban village mapping product for 342 Chinese cities based on foundation models
- 基于多源地理数据和大模型框架，实现全国城中村精准定位。
- 平均城中村占建成区8%，集中分布于中国中部和南部地区。
- 数据开源可查，适合城市规划、社会研究及可持续发展目标评估。
城中村（UVs）是中国快速城市化进程中特有的高密度非正规住区形式。准确识别城中村对城市治理、更新改造和可持续发展至关重要。但由于中国地域广阔，城中村在形态上存在显著异质性，缺乏一致可靠的全国性数据集。本文提出GeoLink-UV，一个基于多源地理空间数据（包括光学遥感影像和地理矢量数据）的高分辨率全国城中村制图产品，覆盖342个中国城市。该数据通过大模型驱动的制图框架生成，有效解决泛化问题并提升产品质量。基于28个城市的独立样本进行地理分层评估，验证了数据在不同城市背景下的可靠性和科学可信度。结果显示，全国城中村平均占建成区面积的8%，在中南部地区高度集聚；建筑级分析进一步确认了城中村普遍呈现低层高密度特征，并揭示区域间形态差异。该数据集为城市研究、非正规住区监测和基于证据的城市更新规划提供开放、系统验证的地理基础，直接支持与可持续发展目标11的大规模评估。数据已公开，获取地址：https://doi.org/10.5281/zenodo.18688062。
原文摘要 · Abstract (English)
Urban Villages (UVs) represent a distinctive form of high-density informal settlement embedded within China's rapidly urbanizing cities. Accurate identification of UVs is critical for urban governance, renewal, and sustainable development. But due to the pronounced heterogeneity and diversity of UVs across China's vast territory, a consistent and reliable nationwide dataset has been lacking. In this work, we present GeoLink-UV, a high-resolution nationwide UV mapping product that clearly delineates the locations and boundaries of UVs in 342 Chinese cities. The dataset is derived from multisource geospatial data, including optical remote sensing images and geo-vector data, and is generated through a foundation model-driven mapping framework designed to address the generalization issues and improve the product quality. A geographically stratified accuracy assessment based on independent samples from 28 cities confirms the reliability and scientific credibility of the nationwide dataset across heterogeneous urban contexts. Based on this nationwide product, we reveal substantial interregional disparities in UV prevalence and spatial configuration. On average, UV areas account for 8 % of built-up land, with marked clustering in central and south China. Building-level analysis further confirms a consistent low-rise, high-density development pattern of UVs nationwide, while highlighting regionally differentiated morphological characteristics. The GeoLink-UV dataset provides an open and systematically validated geospatial foundation for urban studies, informal settlement monitoring, and evidence-based urban renewal planning, and contributes directly to large-scale assessments aligned with Sustainable Development Goal 11. The GeoLink-UV dataset introduced in this article is freely available at https://doi.org/10.5281/zenodo.18688062.
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