TY - JOUR T1 - SENTINEL-2 MSI VE LANDSAT-9 OLI UYDU GÖRÜNTÜLERİYLE YANMIŞ ALANLARIN TESPİTİ: 2022 MUĞLA/MARMARİS ORMAN YANGINI TT - DETECTION OF BURNED AREAS WITH SENTINEL-2 MSI AND LANDSAT-9 OLI SATELLITE IMAGES: 2022 MUĞLA/MARMARİS FOREST FIRE AU - Yücer, Emre PY - 2023 DA - December DO - 10.17780/ksujes.1303299 JF - Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi JO - KSU J. Eng. Sci. PB - Kahramanmaras Sutcu Imam University WT - DergiPark SN - 1309-1751 SP - 866 EP - 880 VL - 26 IS - 4 LA - tr AB - 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 verilerinden Normalleştirilmiş Fark Bitki İndeksi (Normalized Difference Vegetation Index-NDVI), Normalize Edilmiş Nem İndeksi (Normalized Moisture Index-NDMI), Normalize Edilmiş Yanma Oranı İndeksi (Normalized Burn Ratio Index-NBRI) ve Yanmış Alan İndeksi (Burned Area Index-BAI) hesaplanmıştır. Analizler sonucunda elde edilen yanmış alanlar Orman Genel Müdürlüğü (OGM) verileri ile karşılaştırılmıştır. Bu karşılaştırma sonucunda OGM değerlerine en yakın sonuçların; Landsat-9 OLI görüntüsünde NDMI ve Sentinel-2 MSI görüntüsünde NDVI indekslerinin olduğu tespit edilmiştir. Sınıflandırma sonuçlarını değerlendirmek için hata matrisi hesaplanmıştır. Genel doğruluk ve Kappa değerlerine göre Sentinel-2 MSI görüntüsü, Landsat-9 OLI görüntüsüne göre daha yüksek değerlere sahip olduğu tespit edilmiştir. Sentinel-2 MSI görüntüsünde 0,99 genel doğruluk ve 0,98 Kappa değeri ile NBRI indeksi en yüksek değerleri elde etmiştir. KW - Landsat-9 OLI KW - orman yangını KW - Sentinel-2 MSI KW - uzaktan algılama indeksleri N2 - 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. CR - Botella-Martínez, M. A., & Fernández-Manso, A. (2017). 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Doğal Afetler ve Çevre Dergisi, 8 (1). https://doi.org/76-8. 10.21324/dacd.941456 UR - https://doi.org/10.17780/ksujes.1303299 L1 - https://dergipark.org.tr/en/download/article-file/3168500 ER -