A simple, robust, and automatic approach to extract water body from Landsat images (case study: Lake Urmia, Iran)
Lake Urmia is one of the largest saline lakes in the world, and has a great effect on its surrounding ecosystems as well as the economic, social, and even cultural condition of its basin inhabitants. Hence, continuous monitoring of lake area changes is necessary and unavoidable for better land manag...
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2021
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oai:doaj.org-article:385bbb8f7b7b479ab4a6fefde7b44dac2021-11-05T18:41:05ZA simple, robust, and automatic approach to extract water body from Landsat images (case study: Lake Urmia, Iran)2040-22442408-935410.2166/wcc.2019.078https://doaj.org/article/385bbb8f7b7b479ab4a6fefde7b44dac2021-02-01T00:00:00Zhttp://jwcc.iwaponline.com/content/12/1/238https://doaj.org/toc/2040-2244https://doaj.org/toc/2408-9354Lake Urmia is one of the largest saline lakes in the world, and has a great effect on its surrounding ecosystems as well as the economic, social, and even cultural condition of its basin inhabitants. Hence, continuous monitoring of lake area changes is necessary and unavoidable for better land management and prevention of its degradation. In this study, by using Landsat 8 images and by preforming some essential pre-processing tasks, the area of the lake was estimated using the number of traditional spectral indices and a new one and the automatic Otsu's thresholding method for 5 years (2013–2017). The results showed that this index shows more accurate results than other indices when estimating the area of the lake and can separate water class from land one with an average overall accuracy of 96%.Hadiseh BabaeiMilad JanalipourNadia Abbaszadeh TehraniIWA Publishingarticlelandsatotsu's thresholding methodremote sensingsaline lakespectral indiceswssiEnvironmental technology. Sanitary engineeringTD1-1066Environmental sciencesGE1-350ENJournal of Water and Climate Change, Vol 12, Iss 1, Pp 238-249 (2021) |
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landsat otsu's thresholding method remote sensing saline lake spectral indices wssi Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 |
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landsat otsu's thresholding method remote sensing saline lake spectral indices wssi Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Hadiseh Babaei Milad Janalipour Nadia Abbaszadeh Tehrani A simple, robust, and automatic approach to extract water body from Landsat images (case study: Lake Urmia, Iran) |
description |
Lake Urmia is one of the largest saline lakes in the world, and has a great effect on its surrounding ecosystems as well as the economic, social, and even cultural condition of its basin inhabitants. Hence, continuous monitoring of lake area changes is necessary and unavoidable for better land management and prevention of its degradation. In this study, by using Landsat 8 images and by preforming some essential pre-processing tasks, the area of the lake was estimated using the number of traditional spectral indices and a new one and the automatic Otsu's thresholding method for 5 years (2013–2017). The results showed that this index shows more accurate results than other indices when estimating the area of the lake and can separate water class from land one with an average overall accuracy of 96%. |
format |
article |
author |
Hadiseh Babaei Milad Janalipour Nadia Abbaszadeh Tehrani |
author_facet |
Hadiseh Babaei Milad Janalipour Nadia Abbaszadeh Tehrani |
author_sort |
Hadiseh Babaei |
title |
A simple, robust, and automatic approach to extract water body from Landsat images (case study: Lake Urmia, Iran) |
title_short |
A simple, robust, and automatic approach to extract water body from Landsat images (case study: Lake Urmia, Iran) |
title_full |
A simple, robust, and automatic approach to extract water body from Landsat images (case study: Lake Urmia, Iran) |
title_fullStr |
A simple, robust, and automatic approach to extract water body from Landsat images (case study: Lake Urmia, Iran) |
title_full_unstemmed |
A simple, robust, and automatic approach to extract water body from Landsat images (case study: Lake Urmia, Iran) |
title_sort |
simple, robust, and automatic approach to extract water body from landsat images (case study: lake urmia, iran) |
publisher |
IWA Publishing |
publishDate |
2021 |
url |
https://doaj.org/article/385bbb8f7b7b479ab4a6fefde7b44dac |
work_keys_str_mv |
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