Analyzing land use types’ effects on LST using the GWR model and case studies in Beijing

    Zigang Yao Affiliation
    ; Liyan Liu Affiliation
    ; Wenmo Li Affiliation
    ; Abdol Aziz Shahraki   Affiliation
    ; Yan Pang Affiliation


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.

Keyword : landscape management, land use type, urban heat island, land surface temperature, remote sensing, captured images, geographically weighted regression

How to Cite
Yao, Z., Liu, L., Li, W., Shahraki, A. A., & Pang, Y. (2023). Analyzing land use types’ effects on LST using the GWR model and case studies in Beijing. Journal of Environmental Engineering and Landscape Management, 31(3), 196–205.
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Aug 8, 2023
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