Prediction of forest cover changes for Boyer-Ahmad region using Geomod model

Monitoring of land use changes in forest areas provides acceptable information for better planning and management on forest resources. In this study, to assess the changes of the forest cover in the central part of Boyer-Ahmad County in Kohgiluyeh and Boyer-Ahmad Province in southwest of Iran, satellite imageries of two different Landsat time series including Landsat 5, TM satellite data (30.6.1987), and Landsat 8, OLI-TIRS data (23.7.2013) were used. Supervised classification was carried out by applying the Maximum Likelihood Algorithm and LMM model (Matrix Multiplication pictures). Moreover, Logistic regression and Geomod model were used to provide validation map and prediction of forest cover changes in 2039, respectively. Land cover maps achieved from the study area showed that there is a reduction of about 8395 hectares in the forest area during the past 26 years (1987-2013). Moreover, it is predicted that the forest area will decrease around 9938 hectares during the coming 26 years. The results showed that the kappa coefficient obtained from the supervised classification on the satellite imageries in 1987 and 2013 were 0.89 and 0.88, respectively. Moreover, the results of Logistic regression with pseudo R2 and ROC were 0.24 and 0.73, respectively, which indicate that the obtained model is relatively adapted to the real changes and there is an appropriate ability for the model to estimate the forest changes in the last 26 years. Results of simulation of the forest cover changes in 2013 reveal that the Geomod model is a good tool for forecasting the forest cover changes. The accuracy and precision of the obtained forest cover maps is about 90 percent.