Modelling of forest cover change to identify suitable areas for REDD+ projects‏ ‏‎(case ‎study: Lordegan county)‎

Document Type : Scientific article

Authors

1 PhD Student of Forestry, Department of Forestry, Faculty of Natural Resources, Lorestan University, ‎Khoramabad, I.R. Iran‎

2 Associate Prof., Department of Forestry, Faculty of Natural Resources, Lorestan University, Khoramabad, I.R. ‎Iran‎

3 Assistant Prof., Department of Forestry, Faculty of Natural Resources, Lorestan University, Khoramabad, I.R. ‎Iran‎

Abstract

In recent decades, there has been a significant reduction in the Zagros forest. In this regard, in the present study, the forest cover changes of Lordegan county located in Chaharmahal Bakhtiari province were examined using forest cover maps produced by Landsat 5 and 8 satellites belonging to 1988, 2008 and 2018. Then, transition potential modeling from forest to non-forest was performed using two models of artificial neural network and logistic regression, and for validation the ROC and figure of merit were applied. Finally, using overlapping the maps of deforestation probability and carbon resources, the suitable areas for REDD+ projects were identified. The results of change detection showed that during 1988-2008 and 2008-2018, 17,256 ha and 20,553 ha of forest cover were degraded, respectively. The validation results showed that the logistic regression gained the ROC equal to 0.95 and the figure of merit equal to 19.01%, and had a better performance than the artificial neural network. Also, based on overlap map of carbon resources and deforestation probability, areas with high deforestation probability and carbon content above 70 tons per hectare were proposed for REDD+. The findings of this study show that using the presented methodology can be identified the areas with deforestation and can be prevented the release of greenhouse gas into the atmosphere‎.

Keywords

References

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Forest Research and Development
Volume 7, Issue 4
February 2022
Pages 577-594

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