Using Wi-Fi probe and location data to analyze the human distribution characteristics of green spaces: A case study of the Yanfu Greenland Park, China

Abstract

Public open space constitutes a significant part of the sustainable urban environment. Urban green space—which includes parks, sports fields, and wetlands—is a crucial type of public open space in a healthy urban ecosystem. Most studies on urban green spaces comprise large-scale objective evaluations, with relatively few related theoretical studies from the perspective of human behavior. This is predominantly due to the technical constraints involved in obtaining small-scale public open space population activity data. To address this issue, this study examines the crowd activities of an urban green space by combining Wi-Fi probe and location data to discern population distribution characteristics. This study uses Yanfu Greenland Park, a green space in a central area of Shanghai—a typical high-density city—as a case study. This study proposes a technical method for measuring population distribution in a small-scale public space, demonstrating its applicability through an analysis of the population density distribution and activity trajectory in an urban green space. The methodology demonstrated in this study can help urban planning designers and managers create more successful public open spaces. This technical method may also assist urban planning and related research on different scales.