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Fire scar detection using object-oriented classification of Landsat images (Case study: Manshet and Kalarang protected area)
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Sadr Allah Darabi *   1, Vahid Rahmatinia |
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Abstract: (133 Views) |
The plant and animal reserve of Zagros vegetation area has always been threatened and destroyed by fire in dry seasons. The lack of advanced surveying facilities has caused the location and extent of fire destruction to be recorded, as well as their impact on plant and animal species. Fire records are a good source of information in terms of reproducibility, fire-prone species, and the extent of restoration of damage caused by fires to be used in fire risk zoning and fire range expansion modeling. In this research, the methodology of discovering the traces of old fires has been discussed. This process has been done using Landsat 8 images. Various object-oriented algorithms and fuzzy membership functions have been used in image classification to detect fire damage. The accuracy of the classification is evaluated with the new QADI index. The introduction of the combined use of the near-infrared change percentage index and the NBRI47 burn index along with the use of Large, MS-Large fuzzy functions as the best classification method is one of the findings of this research. Kappa value in this method was calculated as 0.96, overall accuracy as 0.98, and Cadi value as 0.01. The area of the map resulting from the best classification showed the occurrence of a fire with an area of 62.75 hectares, which was confirmed by NASA fire detection systems and ground data. The methodology and results of this research, in addition to the possibility of being used in the scientific community of remote sensing, are also important for experts and planners of natural resources and the environment. |
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| Keywords: Validity assessment, fire scar, object-oriented classification, fuzzy membership, Manshet and Qalarang, Ilam province. |
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Type of Study: Research |
Subject:
Special
Received: 2022/08/29 | Accepted: 2023/04/9
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