Published in Scientific Papers. Series "Journal of Young Scientist", Vol. 6
Written by Olguţa MORARIU, Florina BURESCU
Remote sensing is of great interest for the study and characterization of the vegetation and of the agricultural crops, in order to monitor them and to develop predictable patterns regarding the evolution of the crops and also for the purpose of the decision making process in real time. This paper aims to perform a qualitative and quantitative analysis between the supervised and unsupervised methods of classification of satellite imagery. In this context, a Rapid Eye satellite image was used at a 5m resolution taken from the www.planet.com platform from May 2016, which underwent complex preprocessing and processing operations to retrieve useful information about to the vegetal cover. The studied area is within the Experimental Didactic Station of BUSAMV Timisoara. Supervised classification was based on the Maximum Likelihood algorithm and the unsupervised was based on the ISO DATA algorithm. The Rapid Eye scene was process with ArcGIS v. 10.5 software.
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