多源数据支持下城市绿地可达公平性的测度技术与优化模拟

Urban green spaces have attracted much attention as a means to attenuate the environmental problem in the world's cities which are becoming increasingly congested and polluted. However, green spaces in a city are not always equitable in their accessibility owing to differences in income and other aspects. This inequity in accessibility of urban green space is regarded as one of the most important environmental justice issues. At present, there is considerable amount of literature on the accessibility of urban green space in China, but few on accessibility justice. Therefore this project, taking the urban central area of Beijing as an example, mainly focuses on measurement technology and optimization simulation of urban green space according to the idea of “pre-measurement and post-optimization”, specifically including: (1) evaluating urban green space comprehensive service capability based on multi-source data; (2) developing Floating Catchment Area Model which contains green space service capability and street green view; (3) discriminating accessibility justice of urban green space from multi-scale; (4) the multi-scenario optimized simulation of urban green space planning, and (5) the urban green space renewal decision-making. This project intends to adopt new data (breaking the limits of scale), new technologies (improving the accuracy of measurement models) and new ideas (optimizing strategies for green space planning and design) to form a method system for urban green space accessibility justice that is "multi-scale, multi-model and multi- scenario". The results could guide urban green space planning and design practice.

伴随全球城市化进程，城市绿地在应对日益凸显的城市环境问题方面受到广泛关注。然而城市绿地可达性经常因社会经济因素而高度分异，其不公平性被公认为是最重要的环境正义问题之一。当前我国关于城市绿地可达性的研究较多，而可达公平性研究尚属起步阶段。因此，本课题以北京市中心城区为例，按照“先测度——后优化”的思路，重点研究绿地可达公平性的测度技术与优化模拟两部分，具体包括：基于多源数据城市绿地综合服务能力的评估、兼顾绿地服务能力与街景绿视的“搜寻区”模型的构建、多尺度城市绿地可达公平性的判别、城市绿地布局优化的多目标模拟和更新改造多情景决策实施方案。本课题拟采用新数据（突破研究尺度的限制）、新技术（改进测度模型的精度）和新思路（优化绿地规划的策略），形成“多尺度、多模型和多情景”的城市绿地可达公平性研究方法体系，指导城市绿地规划与设计实践工作。

伴随全球城市化进程，城市环境问题日益受到世界范围内的广泛关注。城市绿地不仅支持了城市生态系统的完整性，还有助于改善城市居民生活品质，促进城市公共健康。然而，城市绿地分布并不总是公平的，绿地可达性经常因收入等社会经济因素而高度分异。本项目围绕两个科学问题：1）城市绿地可达公平性在新数据环境、多测度尺度下有着怎样不同的表征？2）如何通过城市绿地布局优化和更新改造解决（改善）社会不公平的现象？采用城市时空大数据与机器学习方法，展开理论和实证研究。首先，制定了新数据环境下城市绿地综合服务能力评估的理论框架及测度方法，完成研究区内城市绿地尺度的服务能力评估，得到城市绿地综合服务能力的可视化结果。其次，构建了新的城市绿地可达公平性测度模型，改善了原有测度模型的不足，并评估了研究区城市绿地可达公平性。最后，多情景模拟可达公平性目标下的城市绿地规划，开发城市绿地布局优化与更新改造决策支持系统，应用于北京中心城区示范区，构建了有利于促进城市绿地可达公平性的规划与设计策略。研究延伸了绿地可达性研究的内涵，有效地解决当前城市绿地可达公平性研究在数据精度、测度技术和优化模拟等方面面临的局限和困境，推动多源地理大数据环境下城市绿地的研究范式转变，为促进绿色、公平和高效的新型城镇化建设提供依据。