Modeling spatial pattern of deforestation using GIS and logistic regression: A case study of northern Ilam forests, Ilam province, Iran

Abstract

This study aimed to predict spatial distribution of deforestation and detects factors influencing forest degradation of Northern forests of Ilam province. For this purpose, effects of six factors including distance from road and settlement areas, forest fragmentation index, elevation, slope and distance from the forest edge on the forest deforestation were studied. In order to evaluate the changes in forest, images related to TM1988, ETM⁺2001 and ETM⁺2007 were processed and classified. There are two classes as, forest and non-forest in order to assess deforestation factors. The logistic regression method is used for modeling and estimating the spatial distribution of deforestation. The results show that about 19,294 ha from forest areas are deforested in the 19 years. Modeling results also indicate that more deforestation occurred in the fragmented forest cover and in the areas of proximity to forest/non forest edge. Furthermore, slope and distance from road and settlement areas had negative relationships with deforestation rates. Meanwhile, deforestation rate is decreased with increase in elevation. Finally, a simple spatial model is presented that is able to predict the location of deforestation by using logistic regression. The validation was also tested using ROC approach which was found to be 0.96.

Key words: Deforestation modeling, remote sensing, logistic regression, Zagros forests, Ilam province, Ilam.