Author(s) :

Maina, M.M., Shanono, N.J..

Volume/Issue :

Abstract :

This paper presents a state-of-the-art of hyperspectral remote sensing classification methods, image processing and application in decision making. Agricultural application in detecting, monitoring and classification of crops, vegetation and other vegetative features are becoming easier. Image classification methods vary and depend on the classification type. The overview exposes the reflective radiation of vegetation and the bands that are applicable to vegetation delineation. Different methods of classification under the supervised, unsupervised and decision tree types were discussed and presented. Hyperspectral images acquired either by airborne or hand held devices are useful and their application are limitless especially in agriculture. Hyperspectral images exposes information that could have been lost when using multiple band images.

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