Evaluating trend Change Land Use / Cover Using Remote Sensing Technique and Object-Oriented Classification Algorithm (Case study: Bartash Plain in Dehloran, Ilam)

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Over the past decades, due to increased population and consequent increase in the need for food, we have seen extensive changes in land use, and in particular, the increase of agricultural lands. The aim of this study was to evaluate the changes in land use in the Bartash plain in Dehloran city of Ilam province during 26 years from 1988 to 2014 using the object-oriented approach. To accomplish this research, the necessary corrections were made after the acquisition of Landsat TM (1988), ETM + (2001) and Landsat 8 (2014) satellite images, and then, using the object-oriented method, the land use map was prepared for the three time periods. The results of the evaluation of the accuracy of the produced maps show that the highest accuracy and Kappa coefficient with the values of 90 and 95% correspond to the image of 2001, and the lowest them with the value of 80 and 90% was related to the image of 1988. Total accuracy and Kappa coefficient in the image of 2014 with 90% and 92%, respectively show a good accuracy. The results of land use change trend showed that the land use of the fair rangeland had the most changes with a decrease of more than 21 thousand hectares. Agricultural lands are in the next place, showing an increase of over 15,000 hectares (twofold) that could be due to the increase in population and the availability of adequate water resources in this area. The land use of poor rangelands also shows an increasing trend of 1.5 fold, indicating the degradation of fair rangelands. The saline lands initially show an increasing trend but then show a decreasing trend due to converting to agricultural lands. The overall accuracy (900-90) and kappa coefficient (95-90) indicate the high accuracy of this method in determining the land use.
Language:
Persian
Published:
Iranian Journal of Range and Desert Research, Volume:25 Issue: 4, 2019
Pages:
723 to 734
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