High spectral resolution in hyperspectral images and their ability of imaging in narrow bands, make them highly capable in investigating and monitoring vegetation and crops. Due to the high number of bands in the hyperspectral images, selection of optimum bands for monitoring a specific parameter is indispensable. For this, absorption bands of different materials and the relevant defined indices can be deployed. In this research, regarding the absorption bands of the substances under consideration, 17 optimum bands were selected. Then, using these bands, different vegetation indices were defined and implemented on the images. The results of each index on the image were investigated and the outcoming results divided into different regions. To get access to applicable results, Decision Tree classification method was applied in the second stage. The resultant output of this method of classification revealed that this method can be used in the relative determination of the plant stress and as a whole, the health and vigour of the vegetation under study in the region, resulting in their classification in this respect. Also this research revealed that, by using these images, one can investigate and monitor the green vegetation, the parameters affecting their vigour as well as discover the stresses which cannot often and otherwise through naked be detected eyes.