Author:
Shen Xiwei,Chen Mingze,Li Xiaowei,Gao Shu,Yang Qiuyi,Wen Yuhan,Sun Qingqing
Abstract
AbstractUrban and community forestry is a specialized discipline focused on the meticulous management of trees and forests within urban, suburban, and town environments. This field often entails extensive civic involvement and collaborative partnerships with institutions. Its overarching objectives span a spectrum from preserving water quality, habitat, and biodiversity to mitigating the Urban Heat Island (UHI) effect. The UHI phenomenon, characterized by notably higher temperatures in urban areas compared to rural counterparts due to heat absorption by urban infrastructure and limited urban forest coverage, serves as a focal point in this study. The study focuses on developing a methodological framework that integrates Geographically Weighted Regression (GWR), Random Forest (RF), and Suitability Analysis to assess the Urban Heat Island (UHI) effect across different urban zones, aiming to identify areas with varying levels of UHI impact. The framework is designed to assist urban planners and designers in understanding the spatial distribution of UHI and identifying areas where urban forestry initiatives can be strategically implemented to mitigate its effect. Conducted in various London areas, the research provides a comprehensive analysis of the intricate relationship between urban and community forestry and UHI. By mapping the spatial variability of UHI, the framework offers a novel approach to enhancing urban environmental design and advancing urban forestry studies. The study’s findings are expected to provide valuable insights for urban planners and policymakers, aiding in creating healthier and more livable urban environments through informed decision-making in urban forestry management.
Publisher
Springer Science and Business Media LLC