Analysis and comparison of land use/land cover changes using artificial neural network (Case study: lands of Taft and Mehriz)

The areas of natural resources and vegetation in the Taft and Mehriz townships in recent decades have undergone changes due to its close proximity to the capital of Yazd province. The purpose of this study is to assess the extent and direction and prediction of land and vegetation changes in these two cities. In this study, Landsat 5 (1998, 2004 and 2008) and Landsat 8 (2017) satellite images in the period from May to June was used. Modeling land use/land cover changes were carried out based on supervised classification. The process of changes was analyzed using land change modeling and perceptron neural network method. The results showed that 3% (558.8 ha) of land and vegetation cover of Taft to Bayer and 1.3% (209.9 ha) were added to the urban lands and reduced from the lands of gardens by 4.3% (559.2 ha), this is the highest rating. The amount of 2.8% (678.8 ha) of land and vegetation in Mehriz Bayer and 1.7% (184 ha) has been changed to urban residential land. In terms of urban expansion, Mehriz has had the highest amount of reducing vegetation. The results show that land use and land cover changes in Taft city where more than Mehriz city so that most of these changes were related to gardens, but in terms of area of land use and land use conversion in Mehriz city has the highest value More intense.