A Multi-source Data Based Analysis Framework for Urban Greenway Safety

Abstract

As a green lining open space, greenways are closely related to the life of urban residents. At present, reports of crimes occurring in greenways are emerging in an endless stream. In order to explore the factors affecting greenway safety, this study, under the guidance of CPTED theory, conducts research by means of big geodata. Three representative greenways in Beijing urban area—the Northwest Tucheng greenway, Second Ring Road greenway and the Three Mountains and Five Gardens greenway—are taken as the research objects. Through the utilization of big geodata information from each platform, including street view analysis, POI analysis, and sports activity data analysis, four factors including space boundary, maintenance, public surveillance and activity support are considered comprehensively, and important influencing factors are selected to construct the analysis framework for urban greenway safety. The results showed that the greenway with high safety has the characteristics of low density of arbor shrubs, low enclosure degree of walls, low distribution density of various buildings, high traffic flow and high frequency of use. The feasibility of the analysis framework is verified by the current situation of greenway safety, so as to provide scientific and reasonable technical support for the construction of safe urban greenways.

Keywords

• big geodata
• data analysis
• greenway safety
• urban greenway