Detection of land use changes and its influencing factors using Artificial Neural Network (Case study: Talesh County)

Preparation and evaluation of land use maps and identify potential areas is important source of information for policy principles and the formulation of development programs. The aim of this study, detection and identification of factors affecting land use changes in the Talesh County with use of the Landsat ETM+ for 2003 and Landsat OLI sensors for 2017. After necessary preprocessing, to raise the spatial resolution of both images, IHS method was integrated to fusion of panchromatic and multispectral bands. Classification of images was integrated with supervised method on fused images that have 15 meter spatial resolution with Artificial Neural Network. The results showed that forest and agricultural land use in the Talesh County in period of 14 years, efforts have decreased and vice versa for human use on the rise. Due to the increasing population of the County and people need more space to live, lead to physical development in their peripheral direction has been suggested that the exploitation of agricultural land and forests. So to preserve natural areas, consolidation and legalization of land use will be on the agenda by experts and officials.