Volume 20, Issue 58 (9-2020)                   jgs 2020, 20(58): 53-70 | Back to browse issues page


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asghari S, jalilyan R, pirozineghad N, madadi A, yadeghari M. (2020). Evaluation of Water Extraction Indices Using Landsat Satellite Images (Case Study: Gamasiab River of Kermanshah). jgs. 20(58), 53-70. doi:10.29252/jgs.20.58.53
URL: http://jgs.khu.ac.ir/article-1-3041-en.html
1- mohaghegh ardabili, mohaghegh ardabili , s.asghari@uma.ac.ir
2- mohaghegh ardabili, mohaghegh ardabili
3- Tabriz University, Tabriz University
4- Islamic Azad University Science & Research, Islamic Azad University Science & Research
Abstract:   (8805 Views)
Water is one of most important human needs for life. According to importance of subject, discussion of management and utilization of water resources has become one of the most important global issues. Remote sensing data are often used in water body extraction studies and type of remote sensing data used plays an important role in water body extraction. In this study, ability of Landsat satellite with application of water indices, to extraction of Gamasiab River in Kermanshah and comparing these indices have been investigated. Specific feature of Low width and shallow rivers has increased the complexity of studies of such rivers using available data. Water body extraction from remote sensing images has been over the past two decades. Water indices were first developed using Landsat TM and Landsat ETM. But its better performance in Landsat 8 is well documented by the researchers. In this study, NDWI, MNDWI, AWEI_nsh, AWEI_sh and WRI indices were used. With extracting optimal threshold from histogram of indices and applying this threshold, the study area was classified into two classes of water and non-water. Then overall accuracy and kappa coefficient values were taken from each of the indices. Finally, AWEI index with overall accuracy of 99.09% and a Kappa coefficient of 0.98 was the best response among the indices in the study area. The results this study showed that approach can easily extract water from satellite imagery.
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Type of Study: Research | Subject: Rs

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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Creative Commons License
This work is licensed under a Creative Commons — Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)