دورية أكاديمية
DETECTION OF BURNED AREAS WITH SENTINEL-2 MSI AND LANDSAT-9 OLI SATELLITE IMAGES: 2022 MUĞLA/MARMARİS FOREST FIRE ; SENTINEL-2 MSI VE LANDSAT-9 OLI UYDU GÖRÜNTÜLERİYLE YANMIŞ ALANLARIN TESPİTİ: 2022 MUĞLA/MARMARİS ORMAN YANGINI
| العنوان: | DETECTION OF BURNED AREAS WITH SENTINEL-2 MSI AND LANDSAT-9 OLI SATELLITE IMAGES: 2022 MUĞLA/MARMARİS FOREST FIRE ; SENTINEL-2 MSI VE LANDSAT-9 OLI UYDU GÖRÜNTÜLERİYLE YANMIŞ ALANLARIN TESPİTİ: 2022 MUĞLA/MARMARİS ORMAN YANGINI |
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| المؤلفون: | YÜCER, Emre |
| المصدر: | Volume: 26, Issue: 4 866-880 ; 1309-1751 ; Kahramanmaras Sutcu Imam University Journal of Engineering Sciences ; Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi |
| بيانات النشر: | Kahramanmaraş Sütçü İmam Üniversitesi Kahramanmaras Sutcu Imam University |
| سنة النشر: | 2023 |
| المجموعة: | DergiPark Akademik (E-Journals) |
| مصطلحات موضوعية: | Landsat-9 OLI, forest fire, Sentinel-2 MSI, remote sensing indices, orman yangını, uzaktan algılama indeksleri, Geological Sciences and Engineering (Other), Yer Bilimleri ve Jeoloji Mühendisliği (Diğer) |
| الوصف: | Forest fires damage living creatures and vegetation, as well as cause air pollution. Therefore, the fight against forest fires is an important issue. Today, thanks to the developing technology, it is possible to detect the burned areas by using image processing algorithms, indexes used in remote sensing and satellite images. In this study, the forest fire that occurred on June 21, 2022 in Muğla province, Marmaris district, Küfre bay and Hisarönü neighborhood was analyzed with Sentinel-2 MSI and Landsat-9 OLI satellite images. For this purpose, the Normalized Difference Vegetation Index (NDVI), Normalized Moisture Index (NDMI), Normalized Burn Ratio Index (NBRI) and Burned Area Index (BAI) were calculated from the satellite data before and after the fire. As a result of the analysis, the burned areas were compared with the data of the General Directorate of Forestry. As a result of this comparison, it was determined that the closest results to the General Directorate of Forestry values were NDMI in the Landsat-9 OLI image and NDVI indices in the Sentinel-2 MSI image. The error matrix was calculated to evaluate the classification results. According to general accuracy and Kappa values, Sentinel-2 MSI image has higher values than Landsat-9 OLI image. The NBRI index obtained the highest values with 0,99 overall accuracy and 0,98 Kappa value in Sentinel-2 MSI image. ; Orman yangınları canlılara ve bitki örtüsüne zarar vermekte, bunun yanında hava kirliliğine de neden olmaktadır. Bu nedenle orman yangınlarıyla mücadele önemli bir durum olarak karşımıza çıkmaktadır. Günümüzde gelişen teknoloji sayesinde görüntü işleme algoritmaları ve uzaktan algılamadaki farklı indeksler kullanılarak uydu görüntülerinden yanan alanların tespiti yapılabilmektedir. Bu çalışmada 21 Haziran 2022 tarihinde Muğla ili Marmaris ilçesinin Küfre koyu ve Hisarönü mahallesinde meydana gelen orman yangını Sentinel-2 MSI ve Landsat-9 OLI uydu görüntüleriyle analiz edilmiştir. Bu amaçla çalışma alanına ait yangın öncesi ve sonrasında ait uydu ... |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | Turkish |
| العلاقة: | https://dergipark.org.tr/tr/download/article-file/3168500Test; https://dergipark.org.tr/tr/pub/ksujes/issue/81055/1303299Test |
| الإتاحة: | https://dergipark.org.tr/tr/pub/ksujes/issue/81055/1303299Test |
| رقم الانضمام: | edsbas.34E1EAED |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |