Capability of derived vegetation indices from remotely sensed data for burned area discrimination in semi-steppic rangeland (case study of CHB province, Iran)

Document Type : Research Paper


1 PhD Candidate of Range Management, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Iran

2 - Associate prof, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Iran

3 Associate prof, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Iran

4 Assistant prof, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Iran


Nowadays, using satellite imagery is one of the fastest and lowest-cost methods in rangeland assessment. Also, remote sensing-based vegetation indices are among the most widely used tools to assess and monitor vegetation changes, especially in the post-fire period, and to map the burned regions in rangelands. The present study was conducted considering the importance and extent of rangelands and the recently increased prevalence of fires in the semi-steppe rangelands of Iran, especially in Chaharmahal and Bakhtiari Province. The main objective of this study was to distinguish and identify the burned areas during 1-3 year and 3-5 year periods to adopt an appropriate post-fire management program in these areas using spectral indices. After calculating the spectral indices, the M statistical parameter was determined to designate the separation capability of the burned areas from the adjacent ones. According to the findings, using NBRT, NBR, and CSI indices is recommended to identify and distinguish the burned areas 1-3 years after the fire from the adjacent areas in semi-steppe rangeland regions of Iran. Overall, these indices are of high efficiency in separating these ranges. Moreover, T.C. Brightness and NBRT indices can efficiently identify and separate the burned areas 3-5 years after the fire. Among the studied indices for both periods of fire in the studied semi-steppe rangelands, the NBRT index showed a high potential for identifying the burned area from the adjacent areas.


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Volume 74, Issue 4
March 2022
Pages 837-850
  • Receive Date: 02 May 2021
  • Revise Date: 13 December 2021
  • Accept Date: 20 December 2021
  • First Publish Date: 20 February 2022