Study on classification for vegetation spectral feature extraction method based on decision tree algorithm

Vegetation classification methods of spectral data are very important for remote sensing fields. We can get essential information from remote data by classification. This paper proposes a method for vegetation classification, which uses a decision tree algorithm for this target. First, we analyze spectral characteristics of extracted features of vegetation spectral data. Then, we use a decision tree algorithm that chooses three characteristics as candidate attributes for classification. Finally, we show some experimental results for the method. Experimental results indicate the effectiveness of the proposed method.