基于基础模型的中国342个城市高分辨率全国性城乡村制图产品
A high-resolution nationwide urban village mapping product for 342 Chinese cities based on foundation models
AI总结：
本文提出基于基础模型的GeoLink-UV数据集，用于中国342个城市高分辨率城乡村制图，揭示区域差异及空间分布特征，支持可持续城市发展。
摘要：
城乡村（UVs）代表一种嵌入在中国快速城市化城市中的高密度非正式居住区。准确识别UVs对于城市治理、更新和可持续发展至关重要。但鉴于UVs在中国广阔领土上的显著异质性和多样性，缺乏一致且可靠的全国性数据集。在本工作中，我们提出了GeoLink-UV，一种高分辨率的全国性UV制图产品，能够清晰界定342个中国城市的UV位置和边界。该数据集源自多源地理空间数据，包括光学遥感图像和地理矢量数据，并通过一种基于基础模型的制图框架生成，旨在解决泛化问题并提高产品质量。基于28个城市独立样本的地理分层精度评估证实了该全国性数据集在异质城市环境中的可靠性和科学性。基于该全国性产品，我们揭示了UVs在区域间的显著差异性及其空间配置。平均而言，UV面积占建成用地的8%，在中南部地区表现出明显的聚集趋势。按建筑物层面的分析进一步证实了UVs在全国范围内一致的低层、高密度发展模式，同时突显了地区性差异化的形态特征。GeoLink-UV数据集为城市研究、非正式居住区监测和基于证据的城市更新规划提供了开放且系统验证的地理空间基础，并直接贡献于与可持续发展目标11相一致的大规模评估。本文介绍的GeoLink-UV数据集可在https://doi.org/10.5281/zenodo.18688062免费获取。
英文摘要：
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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