Monitoring of Thirty Years of Land Cover Changes using Remote Sensing and GIS (Case study: Qaresu watershed, Ardabil)

Subject Areas : GIS

Fereshteh Namdar ¹ ( Ph.D. student in Soil Science, Department of Soil Science, Science and Research Branch, Islamic Azad University, Tehran, Iran. )
Shahla Mahmoudi ² ( Professor of Soil Science, Faculty of Agriculture, University of Tehran, Tehran, Iran. * (Corresponding Author) )
Abazar Esmali Ouri ³ ( Associate Professor in Watershed Science & Engieering, Department of Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran. )
Ebrahim Pazira ⁴ ( Professor of Soil Science, Department of Soil Science, Science and Research Branch, Islamic Azad University, Tehran, Iran. )

Received: 2019-06-30 Accepted : 2019-12-18 Published : 2021-02-19

Keywords: satellite images, Qaresu Watershed, land cover changes, Remote sensing,

Abstract :

Background and Objective: Studying the extent of change and destruction in resources in previous can contribute to efficient planning and utilization of these resources and limiting similar adverse changes in the future. Since changes in resources occur over large expanses of land, remote sensing technology can serve as a essential and valuable tool for monitoring these changes. The purpose of this study was to monitor the land cover changes in Qaresu watershed in Ardabil province using the remote sensing technique. Methods: In this study land cover changes was consulted in 30 years from 1985 to 2015. Landsat images of the study area pertaining to July 1985, 2000 and 2015 were acquired. After geometric and elevation corrections, the images were classified by the supervised approach using the maximum likelihood method. The NDVI index, DEM, and slope layers were used to enhance the image classification accuracy. Classification accuracy was assessed with Kappa index and overall accuracy indexes. Findings: The results showed 20.43% change in the watershed’s land uses over the period from 1985 to 2000, 41.426% over the period from 2000 to 2015, and 27.99% over the period from 1985 to 2015. In all three periods, the greatest changes were in dry farming. Discussion and Conclusion: Results showed despite high capability of Landsat images in mapping land use, using additional layers like NDVI, elevation and slope percent can improve separation accuracy of land using.  

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