Analysis of spatial differentiation and air quality impact of green space landscape in Xi'an, China.

The overall ecological benefits of green space landscape mainly depend on the internal structure and spatial layout of green space. The study area is six urban districts in Xi'an, with the support of remote sensing technology and ArcGIS, which explored the scale effect and spatial differentiation of the green space landscape patterns and their synergistic influence on PM_2.5 and PM₁₀. In this paper, the principal component analysis was used to screen out the indices that can represent the green space landscape pattern in the study area, and on this basis, the landscape metrics weighted change model based on the entropy method was established for the spatial scale analysis of green space landscape. Then, the spatial differentiation characteristics of green space landscape patterns and their impacts on air quality were studied comprehensively using statistical analysis methods. The results show obvious gradient changes in the green space landscape pattern in Xi'an, and the constructed green space landscape pattern metrics can better explain the variation of atmospheric PM concentration. Moreover, we further found that increasing the number and area of green space patches and reducing their overall dispersion can effectively reduce PM concentration. This paper is the first to reveal the characteristic scales of green space landscape patterns in the main urban area of Xi'an. It provides a scientific basis for creating a reasonable spatial distribution pattern of urban green space, which plays an active role in improving the ecological benefits of urban green space. [ABSTRACT FROM AUTHOR]