基于社会感知的城市功能区人居环境愉悦度时空分析

人居环境愉悦度是特定环境下人类感受的定量表征指标，对优化城市人居环境有重要的指导意义。当前研究多使用社交媒体数据分析城市的发展和变化，忽略了城市环境和地理场所带来的居民心理感受影响。收集基于位置服务的微博数据和城市功能区数据，采用地理空间分析和数据挖掘方法，评价了北京市中心城区不同功能区的工作日和节假日人居环境愉悦度(2021年10月1日至24日)。主要结论：(1)人居环境愉悦度的时间趋势存在逐小时和假期-周末-工作日的规律变化。国家法定节假日和周末愉悦度最高，工作日明显降低；(2)人居环境愉悦度的空间分布存在差异，愉悦度高值区和低值区在空间上的分布离散，在工作日的表现更显著；(3)不同功能区之间人居环境愉悦度的时间分布存在差异。高密度商业区和休闲商务区多数时刻具有较高的愉悦度，文旅区和经济开发区在周末人居环境愉悦度较高，工作日中央商务区和自然景观区拥有较低的人居环境愉悦度。研究结果表明社交媒体数据在城市人居环境愉悦度研究中具有很大应用潜力，长时间序列和大空间范围数据挖掘是未来城市研究的发展趋势，对城市景观规划设计和人居环境优化具有重要的指导意义。

Spatiotemporal analysis of residential happiness in urban functional zones based on social sensing

Residential happiness is a quantitative indicator of human feelings which is useful for optimizing urban residential environment. Most studies used social media data to analyze the changes of residential feelings in a whole city. However, few studies focused on the impact of the urban environment and geographic locations on residential feelings. Here, we collected the location-based Weibo data and urban functional zones data in the central areas of Beijing from October 1 to 24, 2021. The spatiotemporal distribution of residential happiness was investigated by using geospatial analysis and data mining methods. Results show that: (1) the residential happiness exhibits the periodical changes associated with holiday-weekend-weekday pattern. The value of residential happiness is the highest on the national holidays and weekends while it decreases significantly on weekdays. (2) The spatial distribution of residential happiness differs significantly. The high and low values of happiness are located in a scattered pattern. (3) The time-trend of residential happiness varies across urban functional zones. The zones of high-density commercial and business and recreational districts have a high level of residential happiness at all time. In contrast, the cultural and tourism zones and economic zones have a high level of happiness on weekends, central business districts and natural landscape districts have a low level of residential happiness on weekdays. The results indicate that social media data has great application potentials in relation to urban residential happiness. The research conclusions have important guiding implications for urban landscape planning and residential environment optimization.