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Their findings indicated that the maximum likelihood classification represented better result than two other classification techniques.
Based on the estimated statistics, the computer used a well-accepted technique called maximum likelihood classification (El-Magd and Tanton 2003) to assign a pixel with NDVI or componential data into one of the nine classes.
The Maximum Likelihood classification is based on the probability density function that is associated with a particular training site signature.