Identification and Analysis of Potential Open-Sharing Subjects of Unit-Affiliated Green Spaces in Shanghai Based on POI Data

• Published in: Land (Basel) Vol. 12; no. 12; p. 2162
• Main Authors: Liu, Bo, Zheng, Sijun, Zhang, Lang, Liu, Jialin, Fu, Tingting, Hao, Ruijun, Yin, Ming
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.12.2023
• Subjects: China; Construction; Green infrastructure; identification of ownership; land; New towns; Open spaces; Pilot projects; Planning; POI data; potential open-sharing subjects; Property rights; Public spaces; R&D; Remote sensing; Research & development; Shanghai; unit-affiliated green spaces; Urban areas; Urban development; Urban planning; China
• ISSN: 2073-445X; 2073-445X
• DOI: 10.3390/land12122162

In the post-pandemic era, the need for accessible urban green open spaces has increased. There is an urgent need to accurately identify large-scale unit-affiliated green spaces and focus on the potential for open sharing. Therefore, using POI data from the Gaode map of Shanghai obtained via web crawler, combined with remote sensing image data and the current green space data, the subjects of unit-affiliated green spaces in the main urban area and five new towns of Shanghai were identified in 2021. On this basis, in-depth explorations were carried out in terms of the type and number of subjects, the overall layout, and the grading of potential open sharing. A new application path for identifying subjects of unit-affiliated green spaces based on the POI data was established. The analysis of the potential openness of the subjects strongly supports the open sharing of unit-affiliated green spaces; the open sharing of unit-affiliated green spaces can compensate for the deficiencies in the fairness and efficiency of urban green spaces.