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ÇOK TARİHLİ OPTİK VE MİKRODALGA GÖRÜNTÜLERİ KULLANILARAK TARIM ALANLARINDA YETİŞTİRİLEN ÜRÜNLERİN BÖLÜT TABANLI SINIFLANDIRILMASI ÜZERİNE BİR YAKLAŞIM

A SEGMENT-BASED APPROACH TO CLASSIFY CROP TYPES IN AGRICULTURAL LANDS BY USING MULTI-TEMPORAL OPTICAL AND MICROWAVE IMAGES

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Abstract (2. Language): 
An automatic classification approach is performed to classify major crop types cultivated in Karacabey Plain, Bursa, through multi-temporal Kompsat-2 and Envisat ASAR data. First, the single-date pancromatic and multispectral Kompsat-2 images are fused with an appropriate image fusion method and 1m colour Kompsat-2 images are generated. Next, different parameter combinations are applied on the fused images in spatial and colour space to find out the optimum segmentation results. The optimum segments are then evaluated using multiple evaluation criteria. Two different classification approaches, pixel-based and segment-based, are tested in this study. First, Image classification are performed on the multispectral Kompsat-2 images. Then the Kompsat-2 images (4m) are classified with Envisat ASAR data. In this way contribution of the Envisat ASAR images to the classification accuracy are tested. Next, distance maps are produced for each thematic map to combine the information of multi-temporal images.The produced thematic maps are evaluated based on pixelbased and segment-based manner using confusion matrices. Results indicate that Envisat ASAR data improve the accuracy of thematic maps. The highest accuracies are obtained for the combined thematic maps of June- August and June-July-August (%88.71 overall accuracy and 0.86 kappa) computed for the segment-based approach.
Abstract (Original Language): 
Çalışmada, Bursa’nın Karacabey ovasında yetiştirilen başlıca tarım ürünleri, çok tarihli Kompsat-2 ve Envisat ASAR görüntüleri ile otomatik olarak sınıflandırılmıştır. İlk olarak, tek tarihli pankromatik ve renkli Kompsat-2 görüntüleri uygun bir yöntem kullanılarak keskinleştirilmiş ve 1m mekânsal çözünürlüğe sahip renkli görüntüler elde edilmiştir. Bu görüntüler üzerinde daha sonra ‘Ortalama Kaydırma’ yöntemi kullanılarak bölütleme işlemi uygulanmıştır. En uygun bölütleme sonucunu belirleyebilmek için her bir keskinleştirilmiş görüntü üzerinde mekân ve renk uzayında farklı parametre kombinasyonları denenmiştir. Elde edilen bölütler çeşitli istatistiksel yöntemler kullanılarak değerlendirilmiştir. Çalışmada piksel tabanlı ve bölüt tabanlı olmak üzere iki farklı sınıflandırma yaklaşımı test edilmiştir. Sınıflandırmalar ilk olarak tek tarihli renkli Kompsat-2 görüntüleri (4m) üzerinde uygulanmıştır. İkinci aşamada renkli Kompsat-2 görüntüleri, geri saçılım katsayıları hesaplanmış Envisat ASAR verileri ile birlikte sınıflandırılarak mikrodalga verilerinin görüntü sınıflamadaki katkısı incelenmiştir. Çok tarihli görüntülerin sınıflandırılması yoluyla elde edilen tematik haritalara ait bilgilerin birleştirilebilmesi amacıyla her bir tematik harita için uzaklık haritaları üretilmiştir. Bu yöntemle elde edilen piksel ve bölüt tabanlı haritalar, hata matrisleri yardımıyla değerlendirilmiştir. Sonuçlar, kullanılan Envisat ASAR verisinin sınıflandırma doğruluğunu arttırdığını göstermiştir. Hesaplamalar, en yüksek genel doğruluğun %88.71 ve 0.86 kappa değeri ile farklı tarihlerde çekilmiş Haziran-Ağustos ve Haziran-Temmuz-Ağustos aylarına ait görüntülerin birleşimi yoluyla elde edilen bölüt tabanlı sınıflandırma yaklaşımı için hesaplandığını ortaya koymuştur.

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