Assessing Urban Green Space distribution in a compact megacity by landscape metrics

Abstract

The pattern and structure of urban green space (UGS) plays a significant role in the landscape and ecological quality (LEQ) of UGS, especially in a compact city with limited space. Based on landscape metrics, this study proposes an innovative method to quantify the effects of UGS pattern and structure on LEQ. Taking Shanghai, China as the study area, we calculated all landscape-level spatial metrics in FRAGSTATS, used correlation analysis in SPSS for data reduction, and adopted factor analysis and cluster analysis to statistically analyze the metrics and assesse the LEQ of UGS. These methods bridge the research gap of UGS distribution assessment for LEQ value by landscape metrics. Results showed that new districts usually have higher LEQ of UGS than old towns. Of the 17 districts in Shanghai, Chongming has the highest LEQ of UGS and Hongkou has the lowest. For the UGS pattern and structure, the eight old towns are similar, in contrast to the new districts of Chongming and Pudong, which are more dissimilar than the other districts for LEQ of UGS. The findings could help compact cities having limited UGS to develop and achieve better LEQ.