Extraction of Crop Information from Reconstructed Landsat Data in Himalayan Foothills Region

Remotely sensed data have been used to extract relevant information on various natural resources and environment. Satellite derived information may be contaminated by a variety of factors. A robust approach for the reconstruction of the temporal profile of NDVI is proposed in this study. The proposed approach consider the crop growth pattern in the Himalayan foothills region so as to make the road map for optimized information extraction. The data mining and the decision tree classification approach has been used to discriminate the crops in the study area. The study has been focused on to extract the information related to crops such as discrimination of different crops at various levels of classification, estimation of the crop yield and monitoring the growth of the crops. A classification model with a good accuracy has been obtained. The results revealed the potential of reconstruction, data mining and decision tree techniques to analyze remote sensing data.