:: Volume 17, Issue 60 (3-2018) ::
جغرافیایی 2018, 17(60): 101-116 Back to browse issues page
Land use/cover change detection using Landsat and IRS imagery: A case study, Khalkhal County
Amir Mirzaei mossivand * 1, Ardavan Ghorbani2 , Farshad Keivan Behjou2
1- university mohaghegh ardabili
2- Faculty of Agricultural Technology and Natural Resources, University of Mohagegh
Abstract:   (5929 Views)

Landuse maps of Khalkhal County using Landsat and IRS imagery by considering geometric and radiometric corrections based on supervised classification with Maximum Likelihood algorithm for 1987, 2002 and 2008 were produced. The accuracy of the produced maps using overall accuracy and Kappa statistic were calculated and results of comparison for the maps of 1987 with 2002 show that, dry farming land has increased from 18.37 to 25.22% and irrigated farming has also increased from 5.77 to 7.30%. On the other hand, forest area has decreased from 2 to 0.38% and rangelands have also reduced from 38.44 to 31.61%. Moreover, the results of map comparison from 2002 and 2008 show that, rangelands and residential areas with 0.23 and 0.06% have increased respectively, and dry farming with 1.58% has the most decreased areas. Statistical analyses in the level of 1 and 5% showed that the rock on the 1988 landuse map were 89 and 91%, and meadow 62 and 65% as the lowest and highest significance. Results of significance for the landuse map of 2005 were 91 and 94% for dry farming, and 67 and 69% for forest as the lowest and highest and for the landuse map of 2008 significance were 86 and 89% for rock, and 67 and 69% for forest as the lowest and highest. By considering accuracy assessment and the significance of the results for the produced maps, the results were acceptable.

Keywords: Landuse/ Cover Change, Satellite Images, Landsat, IRS, Supervised Classification, Khalkhal County, Ardabil Province.
Full-Text [PDF 715 kb]   (2528 Downloads)    
Type of Study: Research | Subject: Special
Received: 2015/05/11 | Accepted: 2016/05/17 | Published: 2018/03/7

XML   Persian Abstract   Print

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 17, Issue 60 (3-2018) Back to browse issues page