Classification of crops using multitemporal hyperion images

In this study, multi-temporal Hyperion and Landsat 8 images from Eastern Turkey are used to classify wheat, alfalfa and sainfoin (Onobrychis). 9 Hyperion and 9 Landsat 8 images acquired at similar dates from year 2013 are used for both same and cross date classification of crops. Ministry of Agriculture, Food and Live Stock's farmer registration system (ÇKS, Çiftçi Kayıt Sistemi) records are used as ground truth after a refinement process. Preprocessing steps used for Hyperion data are presented. 100 samples from each class are input to the SVM and KNN classifiers. SVM classifier performs better than KNN. Landsat 8-launched in 2013- has better same date classification accuracy compared to Hyperion: 91.86% vs 88.94%. Cross date classification of crops with Hyperion and Landsat 8 images yielded lower cross date classification accuracy for both multispectral and hyperspectral images and only in certain periods such as harvest acceptable classification accuracies may be obtained.