上海城市规划Issue(3)：9-16,8.
见物见人--时空大数据支持下的存量规划方法论
City Sensing：An Inventory Planning Tool Based on Spatial-temporal Big Data
段冰若 1王鹏 1郝新华 1蔡玉蘅 1石淼1
作者信息
- 1. 北京清华同衡规划设计研究院有限公司技术创新中心
- 折叠
摘要
Abstract
Compared to the traditional incremental planning in China, inventory planning is different in the perspective of property, time and space. Thus, a higher demand for the depiction of existing space is needed in the inventory planning process. However, the depiction method used in incremental planning such as land use analysis map cannot fulifll this demand. With the prevalence of internet LBS (Location-Based Service) data, planners see a new opportunity to make a more detailed depiction of the existing space. This paper intends to use an LBS data of population density by hour, together with POI (Place of Interest) from Baidu. With the help of unsupervised learning algorithm, a detailed depiction of land use and population activity pattern will be presented, showing more opportunities for big data analysis in the current urban planning research.关键词
存量规划/机器学习/用地分类/LBS数据Key words
Inventory planning/Machine learning/Land use clustering/LBS data分类
建筑与水利引用本文复制引用
段冰若,王鹏,郝新华,蔡玉蘅,石淼..见物见人--时空大数据支持下的存量规划方法论[J].上海城市规划,2016,(3):9-16,8.
