Monitoring of morphological variation of energetic plants
Authors: Frederico martins, Francisco Pinto, SÚrgio Motoike, Igor Assis, Daniel Queiroz
The canopy morphology of energetic plants was monitored using aerial images. It was used and tested the Maximum Likelihood and Isocluster classifiers within a GIS environment. The Kappa index, estimated from 100 random classified image points, was used to access the classifier performance. Once the best classifier was chosen, the number of canopy pixels for each plant set was used to estimate the its development. Thus, it was possible to remotely infer about the crop development.