Investigating Land Surface Temperature (LST) Change Using the LST Change Detection Technique (Gomishan District, Iran)

Monitoring variations in the spectral reflectance of thermal bands of Landsat data provide land surface temperature information of earth's surface features. This research tried to examine the variations of Land surface temperature (LST) from 1987 to 2017 at the Gomishan district and its soundings in Iran. Images preprocessing was conducted including the geo-shifting and atmospheric correction. NDVI and LST maps and their change map using a change detection technique were generated. Basic inferential statistics and spatial analysis were performed. The results show that LST mean reached approximately 42.5 degrees C with 9 degrees C increase, while it was 33.8 degrees C in 1987. However, comparing the statistical analysis of NDVI data did not show any differences between the two study dates. Land cover classes include water, urban, and rural covered areas had the lowest LST shifts between the two study periods. The LST of rangelands, wetlands, and bare lands with more than 10 degrees C increase have experienced considerable LST shifts between during the study periods. Interestingly, some parts of wetland areas had the highest increase approximately 13 degrees C from 1987 to 2017. This study emphasized that LST change detection approach and spatial analysis can be used successfully in LST monitoring investigations. The results can be used to identify regions that experienced LST shifts (change or no change) and also to identify the most critical and impacted areas. The obtained results can be used effectively in sustainable natural disastermanagement plans.