Detecting of Arasbaran forest changes applying image processing procedures and GIS techniques

Nowadays, based on remote sensing procedure, satellite multi- temporal and multi- sensor images for change detection purposes are considered very important issues in optimal management of environmental and ecological resources. In the current study, some different image processing techniques have been accordingly applied in order to determine the rate of forest alterations in Arasbaran protected area. The study area is located in the Northwest of Iran and has been announced to be a component biosphere resource because of its unique fauna and flora by UNISCO organization in 1976. To achieve the main purpose of the study, all existing series of multi-satellite images, observed in years 1987, 1998, 2001, and 2005, have been steadily evaluated using ERDAS Imagine software to model the trend of forest changes in the region. According to the initial results, about 6146.9 hectares of the study area have been deforested throughout the past 18 years. Therefore, a logistic regression model was established among different environmental parameters (such as: distance to settlements, aspect, slope, rainfall, and elevation) to find the main causes of deforestation in the region. Different digital maps, which were created in a GIS setting, reveal that all above mentioned physiographic factors could affect the rate of deforestation in the area, but the distance from the settlements must be regarded as the most effective one. At the final stage, to predict the future trend of deforestation, an endangered map was produced, classifying the existing forests into three major categories such as: extra critical, critical, and vulnerable areas. All valuable results found by the current research could be documented in preventing procedure of the Arasbaran threatened woodlands in future environmental informatics management strategy.