Detection and Diagnosis of Fire Areas in Golestan Forests Using Landsat Satellite Images
محورهای موضوعی : فصلنامه علمی پژوهشی سنجش از دور راداری و نوری و سیستم اطلاعات جغرافیایی
Ali Emadizadeh
1
(M.Sc. Remote Sensing and GIS, Science and Research Branch, Islamic Azad University, Tehran, Iran)
Zahra Azizi
2
(*. Assistant Professor, Department of Remote Sensing and GIS, Science and Research Branch, Islamic Azad University, Tehran, Iran)
کلید واژه: Regression, Fire, Forest, NDVI index, NBR index, dNBR index,
چکیده مقاله :
Fire is a major factor in the development of some plant communities, especially those exposed to lightning. Lightning is almost the main cause of natural fires in most plant communities. Fire is effective in the evolution of various species of forests, pastures, and shrubs in arid regions of the world's Mediterranean regions. Remote sensing and geographic information systems are appropriate in assessing the severity of burns. In this study, the intensity of the fire in Gorgan forests is evaluated and examined. The period of the study area was from 2013 to 2017 and Landsat 8 satellite imagery was used. First, the fire points were identified within an area of 500 meters by the IDW method. Then, by using NDVI, NBR, and dNBR indicators, fire points were evaluated and fire points were marked with red pixels which is clear in the two pictures before and after the fire. Finally, it was concluded that the NBR and dNBR index are the most accurate indicators with an accuracy of more than 74%.
Fire is a major factor in the development of some plant communities, especially those exposed to lightning. Lightning is almost the main cause of natural fires in most plant communities. Fire is effective in the evolution of various species of forests, pastures, and shrubs in arid regions of the world's Mediterranean regions. Remote sensing and geographic information systems are appropriate in assessing the severity of burns. In this study, the intensity of the fire in Gorgan forests is evaluated and examined. The period of the study area was from 2013 to 2017 and Landsat 8 satellite imagery was used. First, the fire points were identified within an area of 500 meters by the IDW method. Then, by using NDVI, NBR, and dNBR indicators, fire points were evaluated and fire points were marked with red pixels which is clear in the two pictures before and after the fire. Finally, it was concluded that the NBR and dNBR index are the most accurate indicators with an accuracy of more than 74%.
