Monitoring Influential Variables to the Cooling Capacity of Green Infrastructure to Mitigate Diurnal Urban Heat Island Effect with Landsat Imagery

Abstract Submission: With Landsat 7 imagery, the current study investigated how reducing surface urban heat island (SUHI) by green infrastructure (GI) can link to influential variables such as physical variables of GI, environmental variables of the streets, and meteorological variables. All areas within 780 meters of large water bodies were excluded to isolate the cooling of GI. Assuming an influential radius of 180 meters, the area affected by more than one GI was excluded too. Pairs of reference (i.e., unaffected by any GI) and experimental (i.e., affected by only one GI) area were selected to calculate the reduction of SUHI. The reduction of SUHI was linked to the variables by multiple regression, and the relative importance of each selected variable was computed. The results: First, the distance to GI is the most prevalent and essential variable, implying that the number of GI is more important than the size of individual GI. Second, street ventilation is vital for the cooling capacity of GI. Third, GI maintenance can be extremely important. Fourth, the average cooling capacity of GI tends to be low if the street pattern is complex; however, the overall cooling capacity can still be optimized by careful planning.

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