Detection of Heat Islands over Arak City Based on Spatial Autocorrelation Analysis

The assessment of urban heat islands is considered as a key variable in the studies of environmental sciences because modeling the interactions of the land surface flux can best respond to many urban problems of modern societies.This study aimed to detect heat islands over Arak city and their clustering was done.For this purpose, the satellite images of Landsat 8 (OLI and TIRS) related to August for three consecutive years of 2013, 2014 and 2015 were taken from the United States Geological Survey (USGS) Site.For the extraction of Urban Heat Islands (UHI) values of Land Surface Temperatures (LST), Moran's autocorrelation functions and hot spot analyses by MATLAB and Arc GIS capabilities were used.After land surface temperature (LST) calculation, hot and cold clusters of heat islands over Arak were extracted using the hot spot analysis index. To evaluate the factors affecting the formation and clustering of heat islands in Arak NDVI and NDBI indices were used. The results showed that there is a high correlation between the two parameters, vegetation and urban built areas with land surface temperature so that the vegetation index has moderated and urban built areas has exacerbated the heat islands over Arak city. Comparative assessment of urban heat islands led to the detection of two types of heat islands over Arak: Focal heat islands and the linear heat islands. Moran's spatial autocorrelation analysis revealed that the land surface temperature has spatial structure in Arak; in other words, land surface temperature is distributed in clusters in Arak. Finally, analysis of hot spots is a clear confirmation on focus and clustering of heat islands over Arak by increasing the time period.