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There has been an increasing concern of rising temperatures as cities continue to expand and intensify. Urban warming is having significant impacts on the environment that are far beyond city limits. Understanding the development pattern of the urban heat island (UHI) effect is crucial for making action plans to mitigate urban warming. In this study, we combine multitemporal satellite imagery, spatial autocorrelation indices, and statistical analysis into a spatiotemporal study of the surface UHI effect in the Boise-Meridian metropolitan area. A continuous landscape modeling perspective was taken to quantitatively depict the abundance and spatial configuration of green vegetation and built-up areas at a landscape scale. We aim to (1) evaluate the variations in the land surface temperatures (LST) along the urban–rural gradients of Boise for multiple years, (2) identify the relationships of the LST variations with the land cover variables quantified using the spatial autocorrelation indices, and (3) analyze the changing climate in Boise in conjunction with its urbanization pattern over the last two decades. Results show that the region experienced a significant increase in the LST along with a great expansion of urban areas at the cost of agriculture. The warming effect of built-up areas was greater than the cooling effect of green vegetation, suggesting an urgent need for increasing greenspace in the city. Statistical analyses show that clustered vegetation and dispersed built-up features are beneficial for reducing the LST. Our study presents a spatiotemporal framework for analyzing the surface UHI effect from multiple angles. Scientific findings from this study can help make informed policies against urban warming via optimal planning of urban land cover.

Spatiotemporal Characterization of Land Cover Impacts on Urban Warming: A Spatial Autocorrelation Approach