城市边界，社会壁垒：用于绘制封闭社区及其公平性影响的基准与以视觉为中心的框架
Urban Boundaries, Social Barriers: A Benchmark and Vision-Centric Framework for Mapping Gated Communities and Equity Implications
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中文总结 AI 辅助
本文针对中国封闭社区研究的不足，构建了大湾区封闭/开放社区识别的多模态基准GBA-GCs，提出以视觉为中心的多模态框架MCGC，其性能优于基线模型，可用于大都市级绘制并揭示相关公平性问题。
中文摘要 AI 辅助
社区是塑造城市形态与社会生活的基本空间单元，住宅院落的空间开放或封闭状态会影响人员流动、公共服务获取及公平性，但针对中国封闭社区（fengbi xiaoqu）的研究多为定性或小规模，限制了可复现的城市级分析。为填补这一空白，本文推出GBA-GCs——中国大湾区的大都市级多模态基准，用于本地化封闭/开放社区识别，涵盖37444个住宅院落，配有对齐的边界多边形、高分辨率卫星影像、中文元数据、结构化属性，以及专家验证的标签、标注者间可靠性数据和官方划分的评估集。基于该基准，本文提出封闭社区多模态分类器（MCGC），这是一种基于DINOv3-SAT的以视觉为中心的多模态框架，通过模态感知交叉注意力与自适应门控融合影像、文本和结构化线索，以缓解模态不平衡问题。MCGC的性能始终优于强大的单模态和多模态基线模型。最后，本文将经过验证的模型应用于大都市级绘制，并报告了面向公平性的发现，包括封闭社区（GCs）的空间聚类、私有化绿地以及行人连通性降低。该基准、代码和发布文档可在指定URL获取。
英文摘要
Communities are fundamental spatial units that shape urban form and social life. Whether a residential compound is spatially open or enclosed affects mobility, access to public services, and equity, yet studies of Chinese fengbi xiaoqu remain largely qualitative or small-scale, limiting reproducible city-scale analysis. We address this gap by introducing GBA-GCs, a metropolitan-scale multimodal benchmark for locally grounded gated/open community recognition in China's Greater Bay Area, covering 37,444 residential compounds with aligned boundary polygons, high-resolution satellite imagery, Chinese metadata, and structured attributes, together with expert-verified labels, inter-annotator reliability, and official evaluation splits. Built on this benchmark, we present Multimodal Classifier for Gated Community (MCGC), a vision-centric multimodal framework based on DINOv3-SAT that fuses imagery, text, and structured cues via modality-aware cross-attention and adaptive gating to mitigate modality imbalance. MCGC consistently outperforms strong unimodal and multimodal baselines. Finally, we apply the validated model to metropolitan-scale mapping and report equity-oriented findings including spatial clustering of GCs, privatized green space, and reduced pedestrian connectivity. The benchmark, code, and release documentation are available at https://github.com/MinweiZhao/GBA-GCs.
发表机构
- The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））
- School of Public Administration and Policy, Renmin University of China（中国人民大学公共管理学院）
- Sony AI（索尼人工智能）
- University of South China（南华大学）
机构由 AI 辅助整理，请以论文原文为准。
