With the rapid growth in big data, classification is becoming a necessary tool for practitioners and decision-makers in many fields of research. Several classifications techniques have been developed in the area of machine-learning and pattern recognition. In this paper, we try to present the outline of the main stages through which a supervised classification under the support vector machine algorithm is processed. We utilize a method for applying SVM learning algorithm for data classification and regression purposes under a cloud computing platform. We also point out that we have taken benefit of the various advantages offered by the Google Earth Engine platform through which we have found that in addition to guaranteed saving of time and effort, this platform has produced perfect results of high precision. The latter can be shown in two precision indicators that we used and which yielded very satisfactory results.

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