Deforestation probable area predicted by logistic regression in Pathro river basin: a tributary of Ajay river

Deforestation threatens biodiversity in remaining forest in India. Today majority of populated areas are facing huge anthropogenic deforestation and it is one of the greatest problems in our country. For the sustainable management of forest there is a need of prediction about the probability of deforestation, i.e. which areas are most susceptibility to deforestation. This study reveals a methodology for predicting the areas of deforestation based on cultural and natural landscape. Geographical information system and logistic regression have been used to predict the greatest propensity for the deforestation of Pathro river basin. The logistic regression model has proven that the deforestation is an integrated function of altitude, slope, slope aspect, distance from road, settlement, river and forest edge. The independent variables are strongly correlated with deforestation. Finally, the receiver operating characteristic curve has been drawn for the validation of deforestation probability map and the area under the curve (AUC) is commuted for verification and measurement of level of accuracy. The AUC for the logistic regression model has shown 76.6% prediction accuracy. The result reveals that the performance logistic regression is good enough in simulation of deforestation process. This model also predicted the areas with high potential for future deforestation.

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