Investigating the Relationship between Thermal Islands and Green Space Areas and Detecting its Changes (Case Study: Kerman City)

This study was conducted to investigate the effect of vegetation in the city in the form of green space on Land Surface Temperature (LST) and also to identify the thermal islands of the Kerman city. LST was calculated by inverse method Planck function using Landsat 8 in Google Earth engine. The calculated LST was calculated as the average of two images in the middle months of the four seasons of 2014, 2017 and 2020. Landsat Science Notebook and a split window were used In order to evaluate the efficiency of the method used in calculating the LST. The relationship and the effect of vegetation on the calculated LST for Kerman city have been done using correlation and selection of ring buffer at intervals of 50, 100, 150 and 200 meters. Finally, their seasonal changes were examined using Moran's I autocorrelation index and its position changes were analyzed both as a season-to-season trend and as a general trend. The results showed that the Planck function method and the Landsat Science Notebook method had more accurate results than the Split window method. There is a relationship between the area of the park and its temperature, and the lowest calculated temperatures for green spaces are related to the parks with the largest area. Correlation test analysis showed that in all seasons of the year, LST is inversely related to vegetation density index. Also, the amount and intensity of this negative correlation vary depending on different seasons. The highest negative correlation value of -0.48 was recorded for the summer in 2014. Quantifying the effect of green space on the ambient temperature fluctuation showed that, on average distance 200 meters from vegetated areas, the temperature has increased by 3 degrees resulting from increasing distance from the identified cores as green space; it is clear evidence indicating the effect of green space on the amount of measured temperature. The results of this study showed that the calculation of earth surface temperature provides reliable results in the management of urban space that can be useful in future urban decisions.