Spatial-Temporal Analysis of Urban Green Space and the Impact on Land Surface Temperature of Beijing, China

Abstract

Urban green space (UGS) is crucial for both urban nature and human beings, and numerous studies have demonstrated the potential of UGS in lessening the effects of the urban heat island (UHI). The possible connection between the equitable distribution of UGS across pixels and UHI, however, has primarily gone unnoticed. To ascertain the potential influence, this work utilizes the land surface temperature (LST) and the equitable distribution of UGS across pixels as indicators of UHI and UGS spatial distribution in Beijing, China, from 2000 to 2018 years, respectively. Specifically, the study generates a comprehensive UGS distribution map using UGS coverage fraction data and calculates the Gini coefficient to determine the grid-scale equitable distribution of UGS. The study also derives an LST map using Landsat data, surface emissivity, and atmospheric data through the Statistical Mono-Window (SMW) algorithm. Finally, the indicator system of UGS and LST is established, including spatial distribution and grid-scale inequity for UGS, spatial distribution, and grid-scale statistical indicators (mean and median) for LST. Based on the proposed indicator system, a spatial-temporal analytical method is presented to reveal spatial-temporal patterns in the effect of UGS on urban LST. The results of our study show that: (1) total coverage and equity of UGS significantly increase, and UGS in Beijing is extremely unbalanced; (2) LST has increased rapidly in recent years, and the proportions of areas with increased temperature have developed; and (3) expanding UGS and ensuring an equitable distribution of UGS can lower urban LST.