文章编号： 1672-5328（2021）03-0103-09

张海林
(广州市城市规划勘测设计研究院，广东广州510060)

摘要： 百度热力图是一种能动态反映城市人口聚集特征的互联网开源数据，用于交通规划设计能有 效降低数据分析成本，弥补传统人口数据时效性和动态性不足的问题。提出一种百度热力图人口活 动数量提取方法：根据研究尺度对热力图范围进行网格划分，构建人口聚集密度重分类函数，计算 网格内人口活动总数并转换为点要素。对参数进行敏感性分析，发现网格大小影响数据的颗粒度， 而地图缩放级别影响人口活动总数。以广州市环城高速公路以内的区域为例进行不同方法的对比分 析，表明该方法适用于规划设计的横向比较研究。最后，以广州市临江大道景观带为例，将数据应 用于公共停车场规划选址。

关键词： 规划设计；互联网大数据；百度热力图；人口活动数量；地图缩放级别

中图分类号： U491.1+2

文献标识码：A

Extracting Active Population Data Based on Baidu Heat Maps for Transportation Planning Applications

Zhang Hailin
(Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou Guangdong 510060, China)

Abstract： The Baidu heat map provides the open-source data on Internet, which can dynamically display the characteristics of urban population aggregation. Utilizing such open-source information effectively reduce the cost of data analysis and make up for the lack of timeliness and dynamics of traditional population data in transportation planning and design. This paper proposes a method of extracting active population data through the Baidu heat maps to construct a population aggregation reclassification function that can be used to calculate the total number of activities of the population in the grid defined by scope of research, which leads to the key activity points. The parameters' sensitivity analysis reveals that the grid size affects the data resolution, while the map zooming level affects the total number of population activities. The results of a comparative analysis with Guangzhou Ring Expressway demonstrates the suitability of this method for horizontal comparative study of planning and design. Finally, taking the Riverside Avenue landscape belt in Guangzhou as an example, this paper applies the data to the public parking lot planning and site selection.

Keywords： planning and design; Internet big data; Baidu heat map; active population data; map zooming level