Detection of Burned Areas by Remote Sensing Techniques: İzmir Seferihisar Forest fire case study
The cause of damage to the environment, forest fires have a significant role in order to give way to natural disasters in the world. Forest fires not only affect ecosystems negatively, but also cause serious problems in economic and social life. As a result of forest fires that occurred between the...
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Artvin Coruh University
2019-07-01
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| Series: | Doğal Afetler ve Çevre Dergisi |
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| Online Access: | http://dacd.artvin.edu.tr/tr/download/article-file/693238 |
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| author | Aslı Sabuncu Haluk Özener |
| author_facet | Aslı Sabuncu Haluk Özener |
| author_sort | Aslı Sabuncu |
| collection | DOAJ |
| description | The cause of damage to the environment, forest fires have a significant role in order to give way to natural disasters in the world. Forest fires not only affect ecosystems negatively, but also cause serious problems in economic and social life. As a result of forest fires that occurred between the years of 1937-2016 in Turkey 1,661,506 hectares of forest area was burnt. It is sometimes difficult and impossible to collect data from forests after forest fires. In addition, remote sensing techniques and algorithms are frequently used in determining the burning areas considering the long duration and the cost will be high. Different satellite images (Landsat, MODIS, SPOT, etc.) in various properties are important data sets of remote sensing technology which is frequently used in recent years to map fire intensity, fire damage and burnt zones. In this study, forest fire that occurred and continued 4 days in Seferihisar district of İzmir province on August 9, 2009 was analyzed by remote sensing techniques using Landsat 5 satellite images. Two Landsat images acquired in July 2009 as pre fire and in August 2009 as post-fire. In this study, the capacity of Normalized Burn Ratio (NBR) and Normalized Difference Vegetation Index (NDVI) indices and differenced Normalized Difference Vegetation Index (dNDVI) derived from Landsat 5 images have been analyzed in order to assess the fire severity. Besides NDVI and NBR indices results, maximum likelihood algorithm which is supervised classification method was applied to pre and post fire satellite images. The burnt area after forest fire was calculated as 711 ha with dNDVI, 695 ha with dNBR and 665 ha with maximum likelihood algorithm of pixel based supervised classification method. Based on the three different methods of results are compatible, rational and consistent with the results of the General Directorate of Forestry. |
| format | Article |
| id | doaj-art-83a296bfe6394a83a3c7b51ec58b0f6e |
| institution | Kabale University |
| issn | 2528-9640 2528-9640 |
| language | English |
| publishDate | 2019-07-01 |
| publisher | Artvin Coruh University |
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| series | Doğal Afetler ve Çevre Dergisi |
| spelling | doaj-art-83a296bfe6394a83a3c7b51ec58b0f6e2025-02-02T04:55:52ZengArtvin Coruh UniversityDoğal Afetler ve Çevre Dergisi2528-96402528-96402019-07-015231732610.21324/dacd.511688Detection of Burned Areas by Remote Sensing Techniques: İzmir Seferihisar Forest fire case studyAslı Sabuncu0Haluk Özener1Boğaziçi Üniversitesi Kandilli Rasathanesi ve Deprem Araştırma Enstitüsü Jeodezi Anabilim Dalı Üsküdar 34684, İstanbulBoğaziçi Üniversitesi Kandilli Rasathanesi ve Deprem Araştırma Enstitüsü Jeodezi Anabilim Dalı Üsküdar 34684, İstanbulThe cause of damage to the environment, forest fires have a significant role in order to give way to natural disasters in the world. Forest fires not only affect ecosystems negatively, but also cause serious problems in economic and social life. As a result of forest fires that occurred between the years of 1937-2016 in Turkey 1,661,506 hectares of forest area was burnt. It is sometimes difficult and impossible to collect data from forests after forest fires. In addition, remote sensing techniques and algorithms are frequently used in determining the burning areas considering the long duration and the cost will be high. Different satellite images (Landsat, MODIS, SPOT, etc.) in various properties are important data sets of remote sensing technology which is frequently used in recent years to map fire intensity, fire damage and burnt zones. In this study, forest fire that occurred and continued 4 days in Seferihisar district of İzmir province on August 9, 2009 was analyzed by remote sensing techniques using Landsat 5 satellite images. Two Landsat images acquired in July 2009 as pre fire and in August 2009 as post-fire. In this study, the capacity of Normalized Burn Ratio (NBR) and Normalized Difference Vegetation Index (NDVI) indices and differenced Normalized Difference Vegetation Index (dNDVI) derived from Landsat 5 images have been analyzed in order to assess the fire severity. Besides NDVI and NBR indices results, maximum likelihood algorithm which is supervised classification method was applied to pre and post fire satellite images. The burnt area after forest fire was calculated as 711 ha with dNDVI, 695 ha with dNBR and 665 ha with maximum likelihood algorithm of pixel based supervised classification method. Based on the three different methods of results are compatible, rational and consistent with the results of the General Directorate of Forestry.http://dacd.artvin.edu.tr/tr/download/article-file/693238pixel based image analysisizmir-seferihisar forest fireremote sensingnbr-dnbrndvi |
| spellingShingle | Aslı Sabuncu Haluk Özener Detection of Burned Areas by Remote Sensing Techniques: İzmir Seferihisar Forest fire case study Doğal Afetler ve Çevre Dergisi pixel based image analysis izmir-seferihisar forest fire remote sensing nbr-dnbr ndvi |
| title | Detection of Burned Areas by Remote Sensing Techniques: İzmir Seferihisar Forest fire case study |
| title_full | Detection of Burned Areas by Remote Sensing Techniques: İzmir Seferihisar Forest fire case study |
| title_fullStr | Detection of Burned Areas by Remote Sensing Techniques: İzmir Seferihisar Forest fire case study |
| title_full_unstemmed | Detection of Burned Areas by Remote Sensing Techniques: İzmir Seferihisar Forest fire case study |
| title_short | Detection of Burned Areas by Remote Sensing Techniques: İzmir Seferihisar Forest fire case study |
| title_sort | detection of burned areas by remote sensing techniques izmir seferihisar forest fire case study |
| topic | pixel based image analysis izmir-seferihisar forest fire remote sensing nbr-dnbr ndvi |
| url | http://dacd.artvin.edu.tr/tr/download/article-file/693238 |
| work_keys_str_mv | AT aslısabuncu detectionofburnedareasbyremotesensingtechniquesizmirseferihisarforestfirecasestudy AT halukozener detectionofburnedareasbyremotesensingtechniquesizmirseferihisarforestfirecasestudy |