文献类型：期刊文献

英文题名：ANALYZING LAND USE TYPES' EFFECTS ON LST USING THE GWR MODEL AND CASE STUDIES IN BEIJING

作者：Yao, Zigang[1];Liu, Liyan[2];Li, Wenmo[3];Shahraki, Abdol Aziz[4];Pang, Yan[2]

机构：[1]East China Univ Sci & Technol, Sch Art Design & Media, Shanghai, Peoples R China;[2]Shanghai Tongzeng Planning & Architectural Design, Shanghai, Peoples R China;[3]Shanghai Urban Construct Vocat Coll, Sch Architecture & Environm Arts, Shanghai, Peoples R China;[4]KTH, Royal Inst Technol, Sch Architecture & Built Environm, Stockholm, Sweden

年份：2023

卷号：31

期号：3

起止页码：196

外文期刊名：JOURNAL OF ENVIRONMENTAL ENGINEERING AND LANDSCAPE MANAGEMENT

收录：;EI(收录号：20233614668004);WOS:【SCI-EXPANDED(收录号:WOS:001048441000001)】；

基金：This study was supported by the below funds: 1. Study on the development strategy of the characteristic historical and cultural towns of the Grand Canal Cultural Belt (Lu, Su, and Zhe section) 20YJAZH121; 2. Study on the research, collation, and conservation of traditional village resources in Taiwan 21 & amp;ZD215; 3. Shanghai Summit Discipline in Design.

语种：英文

外文关键词：Atmospheric temperature - Land surface temperature - Land use - Landforms - Landsat - Regression analysis - Surface measurement - Surface properties

摘要：The development of urbanization and the transformation of green lands into impermeable land increase temperature and create urban heat islands (UHIs). Our observations with remote sensing instruments of Landsat platforms show considerable changes in land use types in Beijing city with the shrinking of green lands, expansion of built environments, and a slight increase in the temperature during the recent four decades. Using remote sensing instruments of Landsat platforms and registered data from two meteorological stations in Beijing, this study finds the relationship between land surface temperature (LST) and the increasing conversion of cultivated lands into built-up areas. This article presents innovative research that shows the mutual correlation well and recommends revisions in the land use policies for better weather. The geographically weighted regression model (GWR) with a Gaussian weighting kernel function analyzes the impact of various urban land use types on the LST and the increase UHIs. In Beijing city, green lands show fewer standard deviations (SD) in the average temperatures equal to 0.109, while the industrial spaces exhibit a high SD equal to 0.212. The outcomes of this paper contribute to finding optimal land use policies everywhere in the world with the increasing urbanization through simulating its model for a more comfortable life.