Evaluating the Long-Term Spatio-Temporal Equity of Urban Green Space: A Case Study of Hangzhou, China

• Published in: 2023 11th International Conference on Agro-Geoinformatics (Agro-Geoinformatics) pp. 1 - 5
• Main Authors: Tang, Wei-Yang, Yao, Yi-Xuan, Yu, Wang-Ye, Lu, Li-Zhen
• Format: Conference Proceeding
• Language: English
• Published: IEEE 25.07.2023
• Subjects: Artificial satellites; Earth; Equity of Urban green space (EUGS); Hangzhou; Random forest; Remote sensing image; Spatial-temporal pattern; Statistical analysis; Transportation; Urban areas; Vegetation mapping
• DOI: 10.1109/Agro-Geoinformatics59224.2023.10233297

Urban green space is mostly important for the urban ecosystem. Its equity involves the reasonable distribution of natural resources, and also reflects the allocation fairness of urban green spaces (UGSs). Early relevant researches focused on investigating the spatial equity of urban green spaces (EUGSs) in a certain time, and paid less attention to the spatio-temporal changes of EUGSs. This paper, taking the Second Ring Road of Hangzhou city as the study area, aims to exploring the spatiotemporal characteristics of EUGSs over the past 40 years. Firstly, the random forest classification method was applied to detect land use from Landsat images in the selected five summers in 1984, 1994, 2004, 2014 and 2022. Secondly, several spatial statistic methods were utilized to retrieve the normalized values of green space (vegetation) at pixel-scale, and the green coverage rates (GCRs) and their hot spots at block-scale. Thirdly, the Gini coefficients of EUGSs of the entire study area in the selected five years were calculated, and were adopted to further measure the change of EUGSs. The research results show that: 1) The overall water bodies and baresoil lands have changed little, but there are clear trends of urban expansion and reduction in green spaces, which have slowed down in recent years. 2) The green spaces have a sharply decreased trend over the past 40 years, and exhibit a distribution pattern of more in the west and south, and less in the east and north. 3) The spatio-temporal distribution patterns of block-scale green spaces do not significantly change, while the block-scale GCRs have spatially varied in each of the selected five years. 4) The Gini coefficients of UGSs remain at a relatively low level, while show a general upward trend of EUGSs from 1984 to 2014, and a downward trend of EUGSs from 2014 to 2022.