Integrating Spatial Autocorrelation and Greenest Images for Dynamic Analysis Urban Heat Islands Based on Google Earth Engine

Dandan Yan (), Yuqing Zhang, Peng Song, Xiaofang Zhang, Yu Wang, Wenyan Zhu and Qinghui Du
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Dandan Yan: College of Horticulture and Plant Protection, Henan University of Science and Technology, Luoyang 471000, China
Yuqing Zhang: College of Horticulture and Plant Protection, Henan University of Science and Technology, Luoyang 471000, China
Peng Song: College of Agriculture, Henan University of Science and Technology, Luoyang 471000, China
Xiaofang Zhang: College of Horticulture and Plant Protection, Henan University of Science and Technology, Luoyang 471000, China
Yu Wang: College of Horticulture and Plant Protection, Henan University of Science and Technology, Luoyang 471000, China
Wenyan Zhu: College of Horticulture and Plant Protection, Henan University of Science and Technology, Luoyang 471000, China
Qinghui Du: College of Horticulture and Plant Protection, Henan University of Science and Technology, Luoyang 471000, China

Sustainability, 2025, vol. 17, issue 15, 1-20

Abstract: With rapid global urbanization development, impermeable surface increase, urban population growth, building area expansion, and rising energy consumption, the urban heat island (UHI) effect is becoming increasingly serious. However, the spatial distribution of the UHI cannot be accurately extracted. Therefore, we focused on Luoyang City as the research area and combined the Getis-Ord-Gi* statistic and the greenest image to extract the UHI based on the Google Earth Engine using land surface temperature–spatial autocorrelation characteristics and seasonal changes in vegetation. As bare land considerably influenced the UHI extraction results, we combined the greenest image with the initial extraction results and applied the maximum normalized difference vegetation index threshold method to remove this effect on UHI distribution extraction, thereby achieving improved UHI extraction accuracy. Our results showed that the UHI of Luoyang continuously expanded outward, increasing from 361.69 km 2 in 2000 to 912.58 km 2 in 2023, with a continuous expansion rate of 22.95 km 2 /year. Furthermore, the urban area had a higher UHI area growth rate than the county area. Analysis indicates that the UHI effect in Luoyang has increased in parallel with the expansion of the building area. Intensive urban construction is a primary driver of this growth, directly exacerbating the UHI effect. Additionally, rising temperatures, population growth, and gross domestic product accumulation have collectively contributed to the ongoing expansion of this phenomenon. This study provides scientific guidance for future urban planning through the accurate extraction of the UHI effect, which promotes the development of sustainable human settlements.

Keywords: urban heat island; Google Earth Engine; Getis-Ord-Gi*; greenest image; driving factors (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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