The Application of Satellite Image Analysis in Oil Spill Detection

In recent years, there has been an increasing use of satellite sensors to detect and track oil spills. The satellite bands, namely visible, short, medium infrared, and microwave radar bands, are used for this purpose. The use of satellite images is extremely valuable for oil spill analysis. With sat...

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Published in:Applied Sciences
Main Authors: Paweł Tysiąc, Tatiana Strelets, Weronika Tuszyńska
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2022
Subjects:
Online Access:https://doi.org/10.3390/app12084016
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spelling ftmdpi:oai:mdpi.com:/2076-3417/12/8/4016/ 2023-08-20T04:08:07+02:00 The Application of Satellite Image Analysis in Oil Spill Detection Paweł Tysiąc Tatiana Strelets Weronika Tuszyńska agris 2022-04-15 application/pdf https://doi.org/10.3390/app12084016 EN eng Multidisciplinary Digital Publishing Institute Civil Engineering https://dx.doi.org/10.3390/app12084016 https://creativecommons.org/licenses/by/4.0/ Applied Sciences; Volume 12; Issue 8; Pages: 4016 oil spill detection satellite imagery spatial data environmental analysis Text 2022 ftmdpi https://doi.org/10.3390/app12084016 2023-08-01T04:46:23Z In recent years, there has been an increasing use of satellite sensors to detect and track oil spills. The satellite bands, namely visible, short, medium infrared, and microwave radar bands, are used for this purpose. The use of satellite images is extremely valuable for oil spill analysis. With satellite images, we can identify the source of leakage and assess the extent of potential damage. However, it is not yet clear how to approach a specific leakage case methodologically. The aim of this study is the remote sensing analysis of environmental changes with the development of oil spill detection processing methods. Innovative elements of the work, in addition to methodological proposals, include the long-term analysis of surface water changes. This is very important because oil is very likely to enter the soil when water levels change. The classification result was satisfactory and accurate by 85%. The study was carried out using images from Landsat 5, Landsat 7, Landsat 8, Sentinel-1, and Sentinel-2 satellites. The results of the classification of the oil stains in active and passive technologies differ. This difference affects the methodology for selecting processing methods in similar fields. In the case of this article, the oil spill that occurred on 29 May 2020 in Norilsk was investigated and compared with data from other years to determine the extent of biodegradation. Due to the tank failure that occurred at the Nornickel power plant on that day, a large amount of crude oil leaked into the environment, contaminating the waters and soil of local areas. Research shows that oil spills may be caused by human error or may be the effect of climate change, particularly global warming. Text norilsk MDPI Open Access Publishing Norilsk ENVELOPE(88.203,88.203,69.354,69.354) Applied Sciences 12 8 4016
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic oil spill detection
satellite imagery
spatial data
environmental analysis
spellingShingle oil spill detection
satellite imagery
spatial data
environmental analysis
Paweł Tysiąc
Tatiana Strelets
Weronika Tuszyńska
The Application of Satellite Image Analysis in Oil Spill Detection
topic_facet oil spill detection
satellite imagery
spatial data
environmental analysis
description In recent years, there has been an increasing use of satellite sensors to detect and track oil spills. The satellite bands, namely visible, short, medium infrared, and microwave radar bands, are used for this purpose. The use of satellite images is extremely valuable for oil spill analysis. With satellite images, we can identify the source of leakage and assess the extent of potential damage. However, it is not yet clear how to approach a specific leakage case methodologically. The aim of this study is the remote sensing analysis of environmental changes with the development of oil spill detection processing methods. Innovative elements of the work, in addition to methodological proposals, include the long-term analysis of surface water changes. This is very important because oil is very likely to enter the soil when water levels change. The classification result was satisfactory and accurate by 85%. The study was carried out using images from Landsat 5, Landsat 7, Landsat 8, Sentinel-1, and Sentinel-2 satellites. The results of the classification of the oil stains in active and passive technologies differ. This difference affects the methodology for selecting processing methods in similar fields. In the case of this article, the oil spill that occurred on 29 May 2020 in Norilsk was investigated and compared with data from other years to determine the extent of biodegradation. Due to the tank failure that occurred at the Nornickel power plant on that day, a large amount of crude oil leaked into the environment, contaminating the waters and soil of local areas. Research shows that oil spills may be caused by human error or may be the effect of climate change, particularly global warming.
format Text
author Paweł Tysiąc
Tatiana Strelets
Weronika Tuszyńska
author_facet Paweł Tysiąc
Tatiana Strelets
Weronika Tuszyńska
author_sort Paweł Tysiąc
title The Application of Satellite Image Analysis in Oil Spill Detection
title_short The Application of Satellite Image Analysis in Oil Spill Detection
title_full The Application of Satellite Image Analysis in Oil Spill Detection
title_fullStr The Application of Satellite Image Analysis in Oil Spill Detection
title_full_unstemmed The Application of Satellite Image Analysis in Oil Spill Detection
title_sort application of satellite image analysis in oil spill detection
publisher Multidisciplinary Digital Publishing Institute
publishDate 2022
url https://doi.org/10.3390/app12084016
op_coverage agris
long_lat ENVELOPE(88.203,88.203,69.354,69.354)
geographic Norilsk
geographic_facet Norilsk
genre norilsk
genre_facet norilsk
op_source Applied Sciences; Volume 12; Issue 8; Pages: 4016
op_relation Civil Engineering
https://dx.doi.org/10.3390/app12084016
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/app12084016
container_title Applied Sciences
container_volume 12
container_issue 8
container_start_page 4016
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