Abstract: Green space is a kind of resource welfare. The evaluation of green space equity based on green view index (GVI) is important to ensure the equitable distribution of green resources. Taking the central urban area of Wuhan as the research object, based on multi-source data such as Baidu Street View Map, Baidu Thermal Map, and satellite remote sensing images, we evaluated the equity of spatial distribution of GVI in Wuhan by using the locational entropy, Gini coefficient and Lorenz curve. The results showed that 87.6% of the points in the central urban area of Wuhan were below the level of poor green vision, which mainly concentrated in Wuhan Iron and Steel Industrial Base of Qingshan District and south of Yandong Lake. The number of points reaching an excellent level was the least (0.4%), mainly concentrated around the East Lake. The overall Gini coefficient of GVI in the central urban area of Wuhan was 0.49, which indicated that the distribution of GVI was heterogeneous. The Gini coefficient of Hongshan District was the largest at 0.64, indicating a huge gap in the distribution of GVI, while the Gini coefficient of Jianghan District was the smallest at 0.47, with a large gap in the distribution. The central urban area of Wuhan had the most low-entropy areas for 29.7% and the least high-entropy areas for 15.4%. There were two-level differences in entropy distribution within Hongshan District, Qingshan District, and Wuchang District. The nature of land use and the role of linear greenery were the main factors affecting the equity of green space in the study area. Our results could provide theoretical basis and planning reference for optimizing urban green space layout.

Key words: green view index, equity, urban green quantity, image recognition, Wuhan