An assessment of oil spill detection using Sentinel 1 SAR-C images

Chaturvedi, Sudhir Kumar; Banerjee, Saikat; Lele, Shashank

doi:10.1016/j.joes.2019.09.004

Cited by 69 publications

(36 citation statements)

References 31 publications

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“…The first step of the process was downloading the data for the specified location and date. The next step was pre-processing, that included radiometric and geometric corrections that were 1 Sentinel-1 SAR Images downloaded from https://copernicus.eu adopted from (Chaturvedi et al 2019; Filipponi 2019) (Figure 2). Further information about these processes is accessible through website 1 .…”

Section: Datasetmentioning

confidence: 99%

“…It was also stated that clean-up and other measures to respond to the incident were done. It is crucial to monitor the progress of clean-up actions taken after an oil spill incident, and one of the advanced methods for it is using remote sensing (Brekke & Solberg 2005;Chaturvedi et al 2019;Filipponi 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Prastyani and Basith (2018) explored the data by using an automatic and semi-automatic process to evaluate the oil spreads in Balikpapan Bay (Prastyani & Basith 2018). Chaturvedi et al (2019) mentioned that SAR Sentinel-1 and other SAR data that have high resolution could be used to detect oil spills in different marine locations (Chaturvedi et al 2019). Furthermore, Suneel et al (2019) explored satellite data to identify oil leaks in the Arabian Sea and their correlation with the oceanographic conditions in the area (Suneel et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Fig.2. Workflow for the pre-processing of Sentinel 1 data, adopted from(Chaturvedi et al 2019; Filipponi 2019) …”

mentioning

confidence: 99%

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Reconstruction Of Oil Spill Trajectory In The Java Sea, Indonesia Using Sar Imagery

Abimanyu

Pranowo

Faizal

et al. 2021

GES

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Oil spill phenomena in the ocean possess a very serious threat to ocean health. On the ocean surface, oil slicks immediately start to spread and mostly end up in the ecosystem. Furthermore, it could threaten the organisms living in the ocean or impact nearby coastal area. The aim of this research was to investigate the trajectories of oil spill based on a real accident in the Java Sea. Tracking oil spills using satellite images is an efficient method that provides valuable information about trajectories, locations and the spread intensity. The objective of this study was to periodically track the trajectory of the oil spill from the Karawang incident using Sentinel-1 Synthetic Aperture Radar (SAR) images. Pre-processing of the images consisted of radiometric and geometric corrections. After the corrections, SAR images were mapped and plotted accordingly. To understand the oil spill trajectories in relation to the oceanic processes, the ocean current pattern map and surface wind roses were also analysed. The processed images from July to October 2019 show a trajectory dominated by the oil spill layers movement towards the west to northwest from the original location along with a decrease in the detected oil spill area over time. The identified trajectories of the oil spill followed the ocean current pattern and surface winds. Thus, these two parameters were considered to be the main factors responsible for the oil spill drift.

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Section: Datasetmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Fig.2. Workflow for the pre-processing of Sentinel 1 data, adopted from(Chaturvedi et al 2019; Filipponi 2019) …”

mentioning

confidence: 99%

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Reconstruction Of Oil Spill Trajectory In The Java Sea, Indonesia Using Sar Imagery

Abimanyu

Pranowo

Faizal

et al. 2021

GES

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“…In particular, SAR image systems are useful to detect oil spills due to reducing the electromagnetic backscattering signal relative to the surrounding area resulting in a darker zone in the SAR image (Chaturvedi, Banerjee, & Lele, 2019). However, there are dark appearances in the SAR image called "oil spill-look alike" results from upwelling phenomena, low winds, natural surface phenomenon induced by plankton or fish, etc.…”

mentioning

confidence: 99%

Determination of Sentinel-2 spectral reflectance to detect oil spill on the sea surface

Afgatiani

Putri²,

Suhadha³

et al. 2020

SJES

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Oil spill is one of the most common marine environmental problems. Oil spills can be caused by leakage at oil refineries at sea or disposal of vessel waste. This event has an impact on various sectors, such as fisheries, tourism, and marine ecosystems. This study aims to determine the spectral reflectance of Sentinel-2 response to detecting oil spill on the sea. Oil identification in the sea can be made visually by looking at colored patterns at sea level. Sentinel-2 image reflectance was obtained by processing the image using the Google Earth Engine platform. The results were clipped according to the area of interest and divided to get a value between 0 and 1. Bands combination is possible to identify the oil spill visually. The silvery pattern saw in the red-green-blue combination, but it is arduous to estimate its distribution because of the silvery pattern seen for thick oil. The combination of SWIR-NIR-red bands proved effective in showing the distribution of oil with a deep black pattern. Spectral measurements in the field were undertaken by taking samples in the areas of oil spills and clean water bodies. The oil layer had a lower reflectance than the clean water body. The blue band gave a high response, but the red band gave less response. In the NIR and SWIR bands, the reflectance of oil was lower than the water body. In conclusion, the SWIR - NIR - RED band combination is better used to determine oil spills due to it shows the characteristics of oil generally, either thin or thick oil.

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Change Detection Analysis Using Sentinel-1 Satellite Data with SNAP and GEE Regarding Oil Spill in Venezuela

Caporusso

Gallo

Tarantino

2022

Lecture Notes in Computer Science

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An assessment of oil spill detection using Sentinel 1 SAR-C images

Cited by 69 publications

References 31 publications

Reconstruction Of Oil Spill Trajectory In The Java Sea, Indonesia Using Sar Imagery

Reconstruction Of Oil Spill Trajectory In The Java Sea, Indonesia Using Sar Imagery

Determination of Sentinel-2 spectral reflectance to detect oil spill on the sea surface

Change Detection Analysis Using Sentinel-1 Satellite Data with SNAP and GEE Regarding Oil Spill in Venezuela

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