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There are two important factors to improve the accuracy of the support vector machine(SVM) classifier. First, selected training samples should uniquely represent each class. Second, SVM training parameters which are pre-defined by the user should be suitable for training samples to obtain satisfied results of the SVM classifier. The proposed method of this paper presents a technique to adjust the...
Information on the spatio-temporal dynamics of inland water bodies is of high value for many applications, for example in the context of water and land management or for ecosystem service assessments. In this study, different approaches to delineate inland water bodies from MODIS 250 m time series were compared. Here, the performance of different input bands and indices, of trainings pixel selection...
Most crop classification work use the ground reference data to training the classifier; but sometimes, the ground reference data cannot be obtained. In this paper, we tried to use the NDVI time series obtained during 2006 and 2013 to classify crop types in 2014 at 30 m spatial resolution. The experiment was conducted in Southeast Kansas, USA. Firstly, we extracted the NDVI time series using ground...
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