Understanding the changes in spatial fairness of urban greenery using time-series remote sensing images: A case study of Guangdong-Hong Kong-Macao Greater Bay

Urban greenery is essential to the living environment of humans. Objectively assessing the rationality of the spatial distribution of green space resources will contribute to regional greening plans, thereby reducing social injustice. However, it is difficult to propose a reasonable greening policy aimed at the coordinated development of an urban agglomeration due to a lack of baseline information. This study investigated the changes in spatial fairness of the greenery surrounding residents in Guangdong-Hong Kong-Macao Greater Bay by examining time-series remote sensing images from 1997 to 2017. With the substitution of impervious, artificial surfaces for universal areas of human activities, we quantified the amount of surrounding greenery from the perspective of human activities at the pixel level by utilizing a nested buffer. The Gini coefficient was further calculated for each city to quantify the spatial fairness of the surrounding greenery to people. The results indicated that areas with less greenery surrounding them decreased during 1997 and 2017 in Guangdong-Hong Kong-Macao Greater Bay. The spatial fairness did not tend to increase with the improvements in the overall greening level. The spatial fairness of 4 cities had an increasing trend, and the Gini coefficients of 5 cities were still over 0.6 in 2017. We further proposed different greening policy suggestions for different cities based on the amount of greenery surrounding people and the trend in fairness. The results and the conclusion of this research will help to improve future regional greening policies and to reduce environmental injustice. (C) 2020 Elsevier B.V. All rights reserved.