Investigating the process of land use agriculture changes in Dashte –e- Akbar region via artificial neural network and satellite images

The map of land use and coverage in which the spatial type and model, also the way of land using have been clarified, is one of the important devices in outcoming landuse plannings. Nowadays, the satellite images and remote sensing techniques, due to delivering in time data and their high capability of analysis, have plenty of applications in many fields specially agriculturing, natural resources and in providing landuse maps as the base maps in land planning. In the present study, there has been used Landsat satellite images dated back to years 1985, 2000 and 2013. After geometric & radiometric corrections and final processing, was prepared the classifying map in five classes via the classifying method of art map fuzzy artificial neural network. The results obtaind in this study show that in this period of 22 years, the area of farmlands has been developed with the rate of %28.5 while the area of ranges has been decreased with the rate of %21.55. Also, the accuracy of plant coverage maps resulted from satellite data classification via algorithm neural network has been equal to %91, %92 & %89 respectively for Landsat images 1985, 2000 and 2013. This indicates the high accuracy of this algorithm in satellite data classification.

Agriculture, Landsat, art map fuzzy, Dashte –e- Akbar, Dehloran