Prediction of land-change using machine learning for the deforestation in Paraguay

Max Muller, Shweta Vincent, Om Prakash Kumar


Northwestern Paraguay is being deforested at a very rapid rate. This article studies the rate of deforestation that has happened in this area using satellite images of LandSAT5 and LandSAT7. The rate of the deforestation is detected from 1986 to 2011, graphically using which future prediction is made. The images of LandSAT8 are used to validate the prediction made until 2018. An extrapolation of the graph shows that the process of deforestation is already 3 years ahead of its forecast. An overall accuracy of 98% has been achieved using this technique. The root mean square error (RMSE) is around 0.011.


Coefficient of correlation; Regression; RMSE; Vegetation ratio

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