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An inverse planned oil release validation method for estimating oil slick thickness from thermal contrast remote sensing by in-scene calibration

This study demonstrates a method to estimate floating oil slick thickness based on remote sensing of thermal infrared contrast. The approach was demonstrated for thick oil slicks from natural seeps in the Coal Oil Point seep field, offshore southern California. Airborne thermal infrared and visible...

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Detalles Bibliográficos
Autores principales: Leifer, Ira, Melton, Christopher, Daniel, William J., Kim, Jae Deok, Marston, Charlotte
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9253405/
https://www.ncbi.nlm.nih.gov/pubmed/35800982
http://dx.doi.org/10.1016/j.mex.2022.101756
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author Leifer, Ira
Melton, Christopher
Daniel, William J.
Kim, Jae Deok
Marston, Charlotte
author_facet Leifer, Ira
Melton, Christopher
Daniel, William J.
Kim, Jae Deok
Marston, Charlotte
author_sort Leifer, Ira
collection PubMed
description This study demonstrates a method to estimate floating oil slick thickness based on remote sensing of thermal infrared contrast. The approach was demonstrated for thick oil slicks from natural seeps in the Coal Oil Point seep field, offshore southern California. Airborne thermal infrared and visible spectrum remote sensing imagery were acquired along with position and orientation data by the SeaSpires™ science package. Remote sensing data were acquired in the cross-slick direction of oil slick segments that were targeted for collection, termed “collects.” A collect consisted of booming, skimming, and offloading the oil slick segment into buckets for analysis at the laboratory. Each collect provided an in-scene calibration point of oil thickness versus brightness temperature contrast, ΔT(B), where T(B) is the sensor-reported temperature based on the emitted thermal radiation and differs from the true temperature due to the oil's emissivity. ΔT(B) is the T(B) difference between the oil and oil-free sea surface. Thus, this study is a reverse planned oil-release experiment that demonstrates the value of natural seeps for oil spill science. • Novel approach to quantify floating oil thickness • Custom modified weir skimmer used with added floor and structural strengthening
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spelling pubmed-92534052022-07-06 An inverse planned oil release validation method for estimating oil slick thickness from thermal contrast remote sensing by in-scene calibration Leifer, Ira Melton, Christopher Daniel, William J. Kim, Jae Deok Marston, Charlotte MethodsX Method Article This study demonstrates a method to estimate floating oil slick thickness based on remote sensing of thermal infrared contrast. The approach was demonstrated for thick oil slicks from natural seeps in the Coal Oil Point seep field, offshore southern California. Airborne thermal infrared and visible spectrum remote sensing imagery were acquired along with position and orientation data by the SeaSpires™ science package. Remote sensing data were acquired in the cross-slick direction of oil slick segments that were targeted for collection, termed “collects.” A collect consisted of booming, skimming, and offloading the oil slick segment into buckets for analysis at the laboratory. Each collect provided an in-scene calibration point of oil thickness versus brightness temperature contrast, ΔT(B), where T(B) is the sensor-reported temperature based on the emitted thermal radiation and differs from the true temperature due to the oil's emissivity. ΔT(B) is the T(B) difference between the oil and oil-free sea surface. Thus, this study is a reverse planned oil-release experiment that demonstrates the value of natural seeps for oil spill science. • Novel approach to quantify floating oil thickness • Custom modified weir skimmer used with added floor and structural strengthening Elsevier 2022-06-16 /pmc/articles/PMC9253405/ /pubmed/35800982 http://dx.doi.org/10.1016/j.mex.2022.101756 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Method Article
Leifer, Ira
Melton, Christopher
Daniel, William J.
Kim, Jae Deok
Marston, Charlotte
An inverse planned oil release validation method for estimating oil slick thickness from thermal contrast remote sensing by in-scene calibration
title An inverse planned oil release validation method for estimating oil slick thickness from thermal contrast remote sensing by in-scene calibration
title_full An inverse planned oil release validation method for estimating oil slick thickness from thermal contrast remote sensing by in-scene calibration
title_fullStr An inverse planned oil release validation method for estimating oil slick thickness from thermal contrast remote sensing by in-scene calibration
title_full_unstemmed An inverse planned oil release validation method for estimating oil slick thickness from thermal contrast remote sensing by in-scene calibration
title_short An inverse planned oil release validation method for estimating oil slick thickness from thermal contrast remote sensing by in-scene calibration
title_sort inverse planned oil release validation method for estimating oil slick thickness from thermal contrast remote sensing by in-scene calibration
topic Method Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9253405/
https://www.ncbi.nlm.nih.gov/pubmed/35800982
http://dx.doi.org/10.1016/j.mex.2022.101756
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