Forest fires,whether caused naturally or by human activity can have disastrous effects on the environment.Turkey,located in the Mediterranean climate zone,experiences hundreds of forest fires every year.Over the past two decades,these fires have destroyed approximately 308000 ha of forest area,threatening the sustainability of its ecosystem.This study analyzes the forest fire that occurred in the Menderes region of Izmir on July 1,2017,by using pre-and post-fire Sentinel 2 (10 m and 20 m) and Landsat 8 (30 m) satellite images,MODIS and VIIRS fire radiative power (FRP) data (1000 m and 375 m,respectively),and reference data obtained from a field study.Hence,image processing techniques integrated with the Geographic Information System (GIS) database were applied to a satellite image data set to monitor,analyze,and map the effects of the forest fire.The results show that the land surface temperature (LST) of the bumed forest area increased from 1 to 11 ℃.A high correlation (R=0.81) between LST and b severity was also determined.The bed areas were calculated using two different classification methods,and their accuracy was compared with the reference data.According to the accuracy assessment,the Sentinel (10 m) image classification gave the best result (96.43％ for Maximum Likelihood,and 99.56％ for Support Vector Machine).The relationship between topographical/forest parameters,b severity and disturbance index was evaluated for spatial patt distribution.According to the results,the areas having canopy closure between 71％-100％ and slope above 35％ had the highest b incidence.As a final step,a spatial correlation analysis was performed to evaluate the effectiveness of MODIS and VIIRS FRP data in the postfire analysis.A high correlation was found between FRP-slope,and FRP-b severity (0.96 and 0.88,respectively).