Miryaghoubzadeh, M., Khosravi, S. (2022). Land use change detection in Barandouzchay Watershed from Lake Urmia River Basin using remotely sensed Landsat5 and Sentinel imagery. , 14(4), 481-493. doi: 10.22092/ijwmse.2022.352550.1854
Mirhassan Miryaghoubzadeh; Seyed-Amin Khosravi. "Land use change detection in Barandouzchay Watershed from Lake Urmia River Basin using remotely sensed Landsat5 and Sentinel imagery". , 14, 4, 2022, 481-493. doi: 10.22092/ijwmse.2022.352550.1854
Miryaghoubzadeh, M., Khosravi, S. (2022). 'Land use change detection in Barandouzchay Watershed from Lake Urmia River Basin using remotely sensed Landsat5 and Sentinel imagery', , 14(4), pp. 481-493. doi: 10.22092/ijwmse.2022.352550.1854
Miryaghoubzadeh, M., Khosravi, S. Land use change detection in Barandouzchay Watershed from Lake Urmia River Basin using remotely sensed Landsat5 and Sentinel imagery. , 2022; 14(4): 481-493. doi: 10.22092/ijwmse.2022.352550.1854

Land use change detection in Barandouzchay Watershed from Lake Urmia River Basin using remotely sensed Landsat5 and Sentinel imagery

مهندسی و مدیریت آبخیز
Article 5, Volume 14, Issue 4, December 2023, Pages 481-493    PDF (701.52 K)
Document Type: Research Paper
DOI: 10.22092/ijwmse.2022.352550.1854
Authors
Mirhassan Miryaghoubzadeh* 1; Seyed-Amin Khosravi2
1Assistant Professor, Department of Watershed Management Engineering, Faculty of Natural Resources, Urmia University, Iran
2Ph.D Student, Faculty of Natural Resources, Urmia University, Iran
Abstract
Nowadays remote sensing is known as practical method for studying Land Use (LU)/Land Cover (LC) changes. Due to the vast area of agricultural lands, Barandouzchay Basin is one of the important watersheds among all of watersheds in Lake Urmia River Basin. In this study, in order to evaluate LU/LC change, Landsat-5 TM and Sentinel-2A satellite images were used from 2005 to 2016. The maximum likelihood classification method was used to prepare LU/LC maps. The results of overall accuracy and Kappa coefficient showed high accuracy of maximum likelihood classification method. In order to extract the change detection maps, image difference method was used. Results showed that orchard and nonproductive trees have been increased during 2010-2016 years in Barandouzchay Basin. In the years before 2010, trees were relocated by young trees in Barandouzchay Basin. Drylands and bare lands are classified in the 2005-2010 years which has been increased. The most land use change was related to urban and lowest change was related to rainfed area from 2005 to 2010 and the most land use change is related to bare lands and lowest rate is related to nonproductive tree area from 2010 to 2016.
Keywords
Image difference; Kappa coefficient; Maximum likelihood; Remote sensing; Young trees
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