Big Data-Based Evaluation of Urban Parks: A Chinese Case Study

Abstract

Urban parks play a key role in urban sustainable development. This paper proposes a method for the evaluation of public parks from the perspective of accessibility and quality. The method includes the data extraction of urban park locations and the delineation of urban built-up areas. The processing of urban park data not only involves the extraction from digital maps, but also the classification of urban parks using a semi-automated model in ArcGIS. The urban area is identified using the Point of Interest (POI) data in digital maps, taking economic and human activities into consideration. The service area and its overlapped time is included in the evaluation indicators. With a clear definition of park and urban built-up area, the evaluation result of urban parks is of great comparability. Taking China as an example, the quality of urban parks in 273 prefecture-level cities has been evaluated. The results show that the average service coverage of urban parks in Chinese cities is 64.8%, and that there are significant disparities between cities with different population sizes and locations. The results suggest the necessity to improve public parks in small-and-medium sized cities and inland areas to strengthen the coordination of urbanization and regional development.