基于三维供需测度视角的绿色开放空间供需匹配精准识别与治理响应——广州珠江新城高密度街区的实证研究

Green Open Space Supply–Demand Mismatches: Precise Identification and Governance Responses Based on a Three-Dimensional Measurement Approach: A Case Study on the High-Density District of Zhujiang New Town, Guangzhou

摘要:

在城市发展转向存量提质增效为主的背景下，高密度中心城区的扩绿治理工作面临空间不足的严峻挑战，而精准识别绿色空间供需匹配度是扩绿治理的关键基础。以广州珠江新城核心区为例，采用3D-GIS 可达性分析与网络文本分析方法，结合网络平台和手机信令等多源大数据，分析绿色开放空间的供需匹配情况及其使用特征。研究表明：公共开放空间的供需匹配度显著低于附属开放空间，供需匹配度受空间可达性和地块实时人流量的共同影响，其中实时人流量的影响力显著高于可达性因素；建筑高度对附属开放空间供需匹配度的影响更显著。基于此，提出推动附属开放空间公共化与立体联通、完善休憩设施、推动基于大数据的分时功能共享管理等优化策略。

Abstract:

In the context of urban development shifting toward a stock-oriented model that prioritizes quality and efficiency, greening in high-density central districts faces acute spatial constraints; precise identification of green-space supply–demand matching is therefore crucial. Using the core area of Guangzhou's Zhujiang New Town as a case, this study integrates 3D GIS–based accessibility analysis with web-based text analytics and multisource big data (online platforms and mobile signaling data) to examine matching patterns and use characteristics of green open spaces. Results indicate that public open spaces exhibit significantly lower matching than ancillary (building-affiliated) spaces; matching is jointly driven by spatial accessibility and parcel-level real-time pedestrian flow, with the latter having the stronger effect; and building height significantly shapes matching for ancillary spaces. Accordingly, optimization strategies are proposed, including promoting the public accessibility and three-dimensional connectivity of ancillary open spaces, enhancing recreational amenities, and implementing big data–informed time-sharing management.