Improving classification accuracy of spectrally similar land covers in the rangeland and plateau areas with a combination of WorldView-2 and UAV images

Akar A., Gokalp E., Akar O., Yilmaz V.

GEOCARTO INTERNATIONAL, cilt.32, sa.9, ss.990-1003, 2017 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 32 Sayı: 9
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1080/10106049.2016.1178816
  • Dergi Adı: GEOCARTO INTERNATIONAL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.990-1003
  • Anahtar Kelimeler: Rangelands, WorldView-2, unmanned aerial vehicle, support vector machines, object based classification, OBJECT-BASED CLASSIFICATION
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

This study aims to increase the accuracy of the object based classification approach to differentiate the spectrally similar land cover types to create thematic maps depicting the current land use status in rangeland. Firstly, the multispectral and panchromatic bands of a WorldView-2 MS and Pan images are fused. The fused WV-2 image is then classified with object based approach using Support Vector Machines (SVMs) classifier (Method 1). The overall classification accuracy for Method 1 is found to be 88.6%. Secondly, UAV ortho-image is utilised for segmentation process, which is required for the object based SVM classification of the WV-2 MS image (Method 2). The overall classification accuracy for Method 2 is obtained as 92.4%. It is realised that the Method 2 increases the object based classification accuracy by 4%, compared to Method 1. This result reveals that the object based classification of the UAV and WV-2 MS images makes significant contribution to the classification accuracy.