Comparison of the performances of different topographic correction methods applied to Landsat-8 satellite image in forest areas

Öz

In order to extract information from satellite images, removing the effects caused by topographic variability with topographic correction methods is one of the most important image preprocessing steps. In this study, the performances of topographic correction methods in forest areas with different topographic characteristics were compared. For this purpose, 3 different forest areas with rugged topography on the European Side of Istanbul were selected as the test area, where the dominant stand species are oak (Quercus), hornbeam (Carpinus), and beech (Fagus). Six different topographic correction methods were applied to the Landsat-8 OLI images containing the test areas, and the results were evaluated visually and statistically. As a result of the evaluations, it was determined that Cosine, Sun Canopy Sensor (SCS), Path Length Correction (PLC) and Minnaert+SCS methods did not provide high enough accuracy in rugged forest areas. The Minnaert and Pixel Based Minnaert methods (PBM) provided the highest accuracy in all 3 test areas.

Anahtar Kelimeler

• Landsat-8
• Topographic correction
• Digital elevation model
• Image preprocessing
• Minnaert correction

Landsat-8 uydu görüntüsüne uygulanan farklı topografik düzeltme yöntemlerinin performanslarının orman alanlarında karşılaştırılması

Öz

Uydu görüntülerinden bilgi çıkartılmasında, yeryüzündeki topografik değişkenliklerden kaynaklanan olumsuz etkilerin topografik düzeltme yöntemleri ile giderilmesi en önemli ön işleme adımlarından biridir. Bu çalışmada, uydu görüntülerine uygulanan farklı topografik düzeltme yöntemlerinin orman alanlarında gösterdikleri performanslar karşılaştırılmıştır. Bu amaçla İstanbul Avrupa Yakası’nda engebeli topografyaya sahip ve hâkim meşcere türlerinin meşe (Quercus), gürgen (Carpinus) ve kayın (Fagus) olduğu 3 farklı test alanı seçilmiştir. Test alanlarına ait Landsat-8 OLI görüntülerine altı farklı topografik düzeltme yöntemi uygulanmış sonuçlar görsel ve istatistiksel olarak değerlendirilmiştir. Yapılan değerlendirmeler sonucunda, Cosine, Sun Canopy Sensor (SCS), Path Length Correction (PLC) ve Minnaert+SCS yöntemlerinin engebeli orman alanlarında yeterince yüksek doğruluk sağlamadığı, her 3 test alanında da Minnaert ve Piksel Tabanlı Minnaert yöntemlerinin (PBM) en yüksek doğruluğu sağladığı görülmüştür.

Anahtar Kelimeler

• Landsat-8
• Topografik düzeltme
• Sayısal yükseklik modeli
• Görüntü ön işleme
• Minnaert düzeltmesi

Teşekkür

Bu çalışmaya katkı sağlayan “Orman Yangınlarında Uydu Tabanlı Duyarlılık/Etkilenebilirlik ve Risk Analizi: Antalya Örneği” Projesi’ne (MGA-2021-43241) teşekkür ederiz.

Kaynakça

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