Akram Foroughifar; Soolmaz Dashti
Abstract
Today, the developing world is experiencing unprecedented growth that has a significant impact on land use intensification. Therefore, modeling and predicting growth patterns is crucial for natural resource planners and proponents to formulate a sustainable development strategy. The main purpose of modeling ...
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Today, the developing world is experiencing unprecedented growth that has a significant impact on land use intensification. Therefore, modeling and predicting growth patterns is crucial for natural resource planners and proponents to formulate a sustainable development strategy. The main purpose of modeling is to identify the factors and trends of future changes based on past changes. Monitoring the occurred changes in land units requires the use of rapid and appropriate methods to gather information and integrate layers of information. In the present study, based on image quality, the trend and rate of land use changes in Shush Township in a 30-year time series (1987, 2000 and 2017) have been investigated using Landsat satellite images and TM, OLI and MSS sensors. Different sections were processed and analyzed using ArcGIS, IDRISI and ENVI software. After classifying the images by the most similar supervised method, the classified maps were obtained with an average Kappa coefficient accuracy of 96.1%. The results of detection of changes showed that the largest decrease in area has occurred for uncovered land by 49078 hectares, and the highest increase was for agricultural land by 52691 hectares, which indicates the change of use of uncovered land in favore of agricultural land.
