Abstract
The main objectives of this study are (i) to calculate Land Surface Temperature (LST) from Landsat imageries, (ii) to determine the UHI effects from Landsat 7 ETM+ (June 5, 2001) and Landsat 8 OLI (June 17, 2014) imageries, (iii) to examine the relationship between LST and different Land Use/Land Cover (LU/LC) types for the years 2001 and 2014. The study is implemented in the central districts of Antalya. Initially, the brightness temperatures are retrieved and the LST values are calculated from Landsat thermal images. Then, the LU/LC maps are created from Landsat pan-sharpened images using Random Forest (RF) classifier. Normalized Difference Vegetation Index (NDVI) image, ASTER Global Digital Elevation Model (GDEM) and DMSP_OLS nighttime lights data are used as auxiliary data during the classification procedure. Finally, UHI effect is determined and the LST values are compared with LU/LC classes. The overall accuracies of RF classification results were computed higher than 88 % for both Landsat images. During 13-year time interval, it was observed that the urban and industrial areas were increased significantly. Maximum LST values were detected for dry agriculture, urban, and bareland classes, while minimum LST values were detected for vegetation and irrigated agriculture classes. The UHI effect was computed as 5.6 °C for 2001 and 6.8 °C for 2014. The validity of the study results were assessed using MODIS/Terra LST and Emissivity data and it was found that there are high correlation between Landsat LST and MODIS LST data (r<sup>2</sup> = 0.7 and r<sup>2</sup> = 0.9 for 2001 and 2014, respectively).
Highlights
According to the United Nations Population Fund, more than fifty percent of the world's population lives in cities and this ratio projected to increase
The overall accuracy values for Landsat 7 ETM+ and Landsat 8 OLI/TIRS imageries are given in Table 3 and 4, respectively
When the obtained results are analysed, it can be stated that the Random Forest (RF) classifier provides quite accurate Land Use/Land Cover (LU/LC) results with computed overall accuracies over than 80% for almost all the data sets
Summary
According to the United Nations Population Fund, more than fifty percent of the world's population lives in cities and this ratio projected to increase. Urban Heat Island (UHI) effect causes an increase in the air and surface temperatures of cities and this effect is one of the factors affecting the urban climate. The UHI effect can be defined as higher urban temperature values when compared with surrounding rural areas (Oke, 1982). Urban Heat Island studies are important for urban climate, urban planning and the health and comfort of population living in the city. The UHI effect magnitude can vary depending on the LU/LC pattern, city structure, city size, seasonal variations, ecological context, urban geometry, topography and location of the study area (Effat and Hassan, 2014; Imhoff et al, 2010; Lo and Quattrochi, 2003; Oke, 1973; Singh et al, 2014). Water and vegetation surfaces have the lowest surface temperatures, while urban surfaces such as airport, residential area, industrial areas have the highest surface temperatures (Feizizadeh and Blaschke, 2013; Mallick et al, 2013)
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