Abstract

Urban green space equity relates to the efficient allocation of natural resources and the equalization of public service facilities. Street (road) greenery provides substantial ecological, social and cultural benefits. Thus, in this study, a subdistrict-level evaluation framework for the fairness of the spatial distribution of street greenery was proposed, taking a case study within the Third Ring Road of Fuzhou City in Fujian, China. Street view images may capture the green information in a vertical dimension for the indirect representation of people’s perspective on the ground. The green view index, which was estimated based on Baidu Street View images, was employed to represent the urban street greenery, and the results were combined using deep learning technology. The Gini coefficient, share index and location entropy were used as evaluation indicators for the fairness of the spatial distribution of the street green view index. Furthermore, this framework combined socioeconomic data and population census data to explore the correlation among socioeconomic status, age, and evaluation index at the subdistrict level. In addition, we analyzed street greenery distribution inequalities from the perspective of socioecological justice. The results showed that in Fuzhou, there is a significant correlation among the Gini coefficient, green view index and socioeconomic status. In addition, subdistricts with a lower green view index have a less equitable street greenery distribution, people with low socioeconomic status may suffer from green injustice, and seniors have a lower accessibility to street green space than people with the average social status. Our analytical approach is applicable for other cities, and the findings are useful for greenery spatial planning processes and evaluating construction effects.

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