THE INFLUENCE OF URBAN HEAT ISLAND EFFECT AND ITS RELATIONSHIP WITH LAND COVER, SCALE, AND SEASONALITY IN A LOW-DENSITY URBAN CENTER

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Authors
Burnett, Michael
Keyword
Urban Heat Island , Land Surface Temperature , Air Temperature , Landsat 7 Enhanced Thematic Mapper , MODIS , Urban Heat Island Footprint , Surface Urban Heat Island , NDVI , Moisture , Scale , Low Density Urban Center , Milton , Southern Ontario
Abstract
Land surface temperature (LST) and air temperature (Tair) are the primary metrics applied to measure and analyze urban heat island (UHI) effects, a thermal phenomenon caused by urbanization. This thesis aims to study the UHI effect of a rapidly expanding low-density urban center using two satellite based LST products. Milton, Ontario, Canada was selected as the study site due to its rapid urban development from 2000 to 2019. Two LST products extracted from Landsat 7 Enhanced Thematic Mapper (ETM+) through Google Earth Engine at 30 m resolution and Moderate Resolution Imaging Spectroradiometer (MODIS) at 1 km resolution were compared. The influence of the spatial resolution, land cover, vegetated surfaces and seasonality on the relationship between LST and in situ Tair were examined. UHI footprint (UHIFP) and the surface UHI (SUHI) models were compared to measure the local UHI impact on rural vegetation based on the time series LST data from Landsat 7. The UHI impact on surrounding land in the suburban and rural environment from 2000 to 2019 was analyzed. Results show that MODIS LST from Terra had stronger relationships with Landsat 7 LST than those from Aqua. Tair demonstrated weaker correlations with Landsat LST than with MODIS LST in sparsely vegetated and urban areas during the summer. Due to the winter’s ability to smooth heterogenous surfaces, both LST and Tair showed stronger relationships in winter than summer over every land cover, except with coarse spatial resolutions on forested surfaces. The UHI footprint of the studied low-density suburban center is about 1.4 times larger than the urban center. All vegetated land covers experienced their maximum cooling effects well before reaching the UHIFP perimeter while urban surfaces only begin to diverge from the SUHI Gaussian model outside of the UHIFP. The similar results from both methods indicate a strong urban cover influence overpowering the dominantly distributed agricultural surfaces throughout the growing season. Moisture index was shown as the dominant variable, above vegetation health, correlating with the UHI residuals within every land cover throughout the growing season. This research has helped us better understand the UHI effects of small communities with varied vegetation phonology based on the distribution of built-up pervious and impervious surfaces within the neighborhood structure.
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