Monitoring burned areas using multispectral satellite imagery is easily achievable. To distinguish healthy vegetation from damaged areas, several indices have been designed and proposed. To reduce errors and improve the accuracy of results, the normalized burn ratio +NBR index was introduced, considering the reflective properties of Sentinel-2 sensor bands. The effectiveness of this index was validated by comparison with four other indices in an area of 55 square kilometers in the Kuh-e-Dil Protected Area, located in the northern part of Gachsaran County, Kohgiluyeh and Boyer-Ahmad Province. To achieve this, both single-date and multi-date approaches were employed. For distinguishing pixels corresponding to burned areas from non-burned areas, the difference method was used between images taken before and after the fire, on May 12, 2020, and June 11, 2020. Additionally, confusion matrices were prepared to assess the performance of the indices and were compared. The +NBR index provided more accurate results by eliminating cloud masses and water bodies, which were incorrectly classified in other indices. Pearson correlation values showed that the NBR and NDSWIR indices, with a correlation of 0.92, had the highest correlation with the +NBR index, while the MIRBI index had the lowest correlation with a value of 0.37. Furthermore, the +NBR index demonstrated high effectiveness in identifying fire-impacted areas, achieving the highest Kappa coefficient of 0.90.