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class="label">Mentions</p><p class="data">1</p></div></a><span><div class="stat-container"><p class="label"><span class="js-profile-total-view-text">Public Views</span></p><p class="data"><span class="js-profile-view-count"></span></p></div></span></div><div class="ri-section"><div class="ri-section-header"><span>Interests</span></div><div class="ri-tags-container"><a data-click-track="profile-user-info-expand-research-interests" data-has-card-for-ri-list="292391191" href="https://www.academia.edu/Documents/in/Ugaritic_Studies"><div id="js-react-on-rails-context" style="display:none" data-rails-context="{"inMailer":false,"i18nLocale":"en","i18nDefaultLocale":"en","href":"https://independent.academia.edu/WeidemannAlan","location":"/WeidemannAlan","scheme":"https","host":"independent.academia.edu","port":null,"pathname":"/WeidemannAlan","search":null,"httpAcceptLanguage":null,"serverSide":false}"></div> <div class="js-react-on-rails-component" style="display:none" 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profile--work_container" data-work-id="124857660"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/124857660/Boundary_Extraction_Method"><img alt="Research paper thumbnail of Boundary Extraction Method" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/124857660/Boundary_Extraction_Method">Boundary Extraction Method</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper 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window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=122203267]").text(description); $(".js-view-count[data-work-id=122203267]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 122203267; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='122203267']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 122203267, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=122203267]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":122203267,"title":"Boundary extraction 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src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/118287502/Long_Island_Sound_Coastal_Observatory_Assessment_of_above_water_radiometric_measurement_uncertainties_using_collocated_multi_and_hyperspectral_systems">Long Island Sound Coastal Observatory: Assessment of above-water radiometric measurement uncertainties using collocated multi and hyperspectral systems</a></div><div class="wp-workCard_item"><span>Applied optics</span><span>, Oct 14, 2011</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper 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During the same time period, in-situ profiles of temperature, salinity, inherent optical properties, and chlorophyll a fluorescence were measured using two surface vessels, two autonomous gliders, and an autonomous profiling mooring. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="118287497"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/118287497/Polarization_characteristics_of_coastal_waters_and_their_impact_on_in_water_visibility"><img alt="Research paper thumbnail of Polarization characteristics of coastal waters and their impact on in-water visibility" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/118287497/Polarization_characteristics_of_coastal_waters_and_their_impact_on_in_water_visibility">Polarization characteristics of coastal waters and their impact on in-water visibility</a></div><div class="wp-workCard_item"><span>Proceedings of SPIE</span><span>, May 1, 2009</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Abstract: Polarization characteristics of coastal waters were recently measured during a cruise o...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Abstract: Polarization characteristics of coastal waters were recently measured during a cruise on the R/V&amp;amp;amp;amp;quot; Connecticut&amp;amp;amp;amp;quot; in the areas of New York Harbor-Sandy Hook. NJ region using a new Stokes vector instrument developed by the Optical Remote Sensing ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287497"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287497"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287497; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287497]").text(description); $(".js-view-count[data-work-id=118287497]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287497; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287497']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287497, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=118287497]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287497,"title":"Polarization characteristics of coastal waters and their impact on in-water visibility","translated_title":"","metadata":{"abstract":"Abstract: Polarization characteristics of coastal waters were recently measured during a cruise on the R/V\u0026amp;amp;amp;amp;quot; Connecticut\u0026amp;amp;amp;amp;quot; in the areas of New York Harbor-Sandy Hook. 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NJ region using a new Stokes vector instrument developed by the Optical Remote Sensing ...","owner":{"id":292391191,"first_name":"Alan","middle_initials":null,"last_name":"Weidemann","page_name":"WeidemannAlan","domain_name":"independent","created_at":"2023-11-14T08:25:11.103-08:00","display_name":"Alan Weidemann","url":"https://independent.academia.edu/WeidemannAlan"},"attachments":[],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering"},{"id":498,"name":"Physics","url":"https://www.academia.edu/Documents/in/Physics"},{"id":516,"name":"Optics","url":"https://www.academia.edu/Documents/in/Optics"},{"id":4392,"name":"Monte Carlo Simulation","url":"https://www.academia.edu/Documents/in/Monte_Carlo_Simulation"},{"id":6974,"name":"Monte Carlo","url":"https://www.academia.edu/Documents/in/Monte_Carlo"},{"id":16691,"name":"Physical Oceanography","url":"https://www.academia.edu/Documents/in/Physical_Oceanography"},{"id":27497,"name":"Instrumentation","url":"https://www.academia.edu/Documents/in/Instrumentation"},{"id":31486,"name":"Coding","url":"https://www.academia.edu/Documents/in/Coding"},{"id":34019,"name":"Monte Carlo Methods","url":"https://www.academia.edu/Documents/in/Monte_Carlo_Methods"},{"id":75942,"name":"Atmosphere","url":"https://www.academia.edu/Documents/in/Atmosphere"},{"id":410497,"name":"Angles","url":"https://www.academia.edu/Documents/in/Angles"},{"id":542508,"name":"Optical Remote Sensing","url":"https://www.academia.edu/Documents/in/Optical_Remote_Sensing"},{"id":571946,"name":"Coastal waters","url":"https://www.academia.edu/Documents/in/Coastal_waters"},{"id":742038,"name":"Instrument Development","url":"https://www.academia.edu/Documents/in/Instrument_Development"},{"id":972674,"name":"Hyperspectral Imagery","url":"https://www.academia.edu/Documents/in/Hyperspectral_Imagery"},{"id":1112728,"name":"Point Spread Function","url":"https://www.academia.edu/Documents/in/Point_Spread_Function"},{"id":1228128,"name":"Point Spread Functions","url":"https://www.academia.edu/Documents/in/Point_Spread_Functions"},{"id":1333436,"name":"Monte Carlo Method","url":"https://www.academia.edu/Documents/in/Monte_Carlo_Method"},{"id":2236006,"name":"Degree of polarization","url":"https://www.academia.edu/Documents/in/Degree_of_polarization"},{"id":3122382,"name":"imaging system","url":"https://www.academia.edu/Documents/in/imaging_system"}],"urls":[{"id":41506885,"url":"https://doi.org/10.1117/12.820738"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="118287496"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/118287496/Defining_the_uncertainty_of_electro_optical_identification_system_performance_estimates_using_a_3D_optical_environment_derived_from_satellite"><img alt="Research paper thumbnail of Defining the uncertainty of electro-optical identification system performance estimates using a 3D optical environment derived from satellite" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/118287496/Defining_the_uncertainty_of_electro_optical_identification_system_performance_estimates_using_a_3D_optical_environment_derived_from_satellite">Defining the uncertainty of electro-optical identification system performance estimates using a 3D optical environment derived from satellite</a></div><div class="wp-workCard_item"><span>Proceedings of SPIE</span><span>, May 1, 2009</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Current United States Navy Mine-Counter-Measure (MCM) operations primarily use electro-optical id...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Current United States Navy Mine-Counter-Measure (MCM) operations primarily use electro-optical identification (EOID) sensors to identify underwater targets after detection via acoustic sensors. These EOID sensors which are based on laser underwater imaging by design work best in &quot;clear&quot; waters and are limited in coastal waters especially with strong optical layers. Optical properties and in particular scattering and absorption play an important role on systems performance. Surface optical properties alone from satellite are not adequate to determine how well a system will perform at depth due to the existence of optical layers. The spatial and temporal characteristics of the 3d optical variability of the coastal waters along with strength and location of subsurface optical layers maximize chances of identifying underwater targets by exploiting optimum sensor deployment. Advanced methods have been developed to fuse the optical measurements from gliders, optical properties from &quot;surface&quot; satellite snapshot and 3-D ocean circulation models to extend the two-dimensional (2-D) surface satellite optical image into a three-dimensional (3-D) optical volume with subsurface optical layers. Modifications were made to an EOID performance model to integrate a 3-D optical volume covering an entire region of interest as input and derive system performance field. These enhancements extend present capability based on glider optics and EOID sensor models to estimate the system&#x27;s &quot;image quality&quot;. This only yields system performance information for a single glider profile location in a very large operational region. Finally, we define the uncertainty of the system performance by coupling the EOID performance model with the 3-D optical volume uncertainties. Knowing the ensemble spread of EOID performance field provides a new and unique capability for tactical decision makers and Navy Operations.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287496"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287496"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287496; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287496]").text(description); $(".js-view-count[data-work-id=118287496]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287496; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287496']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287496, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=118287496]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287496,"title":"Defining the uncertainty of electro-optical identification system performance estimates using a 3D optical environment derived from satellite","translated_title":"","metadata":{"abstract":"Current United States Navy Mine-Counter-Measure (MCM) operations primarily use electro-optical identification (EOID) sensors to identify underwater targets after detection via acoustic sensors. These EOID sensors which are based on laser underwater imaging by design work best in \u0026quot;clear\u0026quot; waters and are limited in coastal waters especially with strong optical layers. Optical properties and in particular scattering and absorption play an important role on systems performance. Surface optical properties alone from satellite are not adequate to determine how well a system will perform at depth due to the existence of optical layers. The spatial and temporal characteristics of the 3d optical variability of the coastal waters along with strength and location of subsurface optical layers maximize chances of identifying underwater targets by exploiting optimum sensor deployment. Advanced methods have been developed to fuse the optical measurements from gliders, optical properties from \u0026quot;surface\u0026quot; satellite snapshot and 3-D ocean circulation models to extend the two-dimensional (2-D) surface satellite optical image into a three-dimensional (3-D) optical volume with subsurface optical layers. Modifications were made to an EOID performance model to integrate a 3-D optical volume covering an entire region of interest as input and derive system performance field. These enhancements extend present capability based on glider optics and EOID sensor models to estimate the system\u0026#x27;s \u0026quot;image quality\u0026quot;. This only yields system performance information for a single glider profile location in a very large operational region. Finally, we define the uncertainty of the system performance by coupling the EOID performance model with the 3-D optical volume uncertainties. Knowing the ensemble spread of EOID performance field provides a new and unique capability for tactical decision makers and Navy Operations.","publisher":"SPIE","publication_date":{"day":1,"month":5,"year":2009,"errors":{}},"publication_name":"Proceedings of SPIE"},"translated_abstract":"Current United States Navy Mine-Counter-Measure (MCM) operations primarily use electro-optical identification (EOID) sensors to identify underwater targets after detection via acoustic sensors. These EOID sensors which are based on laser underwater imaging by design work best in \u0026quot;clear\u0026quot; waters and are limited in coastal waters especially with strong optical layers. Optical properties and in particular scattering and absorption play an important role on systems performance. Surface optical properties alone from satellite are not adequate to determine how well a system will perform at depth due to the existence of optical layers. The spatial and temporal characteristics of the 3d optical variability of the coastal waters along with strength and location of subsurface optical layers maximize chances of identifying underwater targets by exploiting optimum sensor deployment. Advanced methods have been developed to fuse the optical measurements from gliders, optical properties from \u0026quot;surface\u0026quot; satellite snapshot and 3-D ocean circulation models to extend the two-dimensional (2-D) surface satellite optical image into a three-dimensional (3-D) optical volume with subsurface optical layers. Modifications were made to an EOID performance model to integrate a 3-D optical volume covering an entire region of interest as input and derive system performance field. These enhancements extend present capability based on glider optics and EOID sensor models to estimate the system\u0026#x27;s \u0026quot;image quality\u0026quot;. This only yields system performance information for a single glider profile location in a very large operational region. Finally, we define the uncertainty of the system performance by coupling the EOID performance model with the 3-D optical volume uncertainties. Knowing the ensemble spread of EOID performance field provides a new and unique capability for tactical decision makers and Navy Operations.","internal_url":"https://www.academia.edu/118287496/Defining_the_uncertainty_of_electro_optical_identification_system_performance_estimates_using_a_3D_optical_environment_derived_from_satellite","translated_internal_url":"","created_at":"2024-04-29T13:35:58.013-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":292391191,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Defining_the_uncertainty_of_electro_optical_identification_system_performance_estimates_using_a_3D_optical_environment_derived_from_satellite","translated_slug":"","page_count":null,"language":"en","content_type":"Work","summary":"Current United States Navy Mine-Counter-Measure (MCM) operations primarily use electro-optical identification (EOID) sensors to identify underwater targets after detection via acoustic sensors. These EOID sensors which are based on laser underwater imaging by design work best in \u0026quot;clear\u0026quot; waters and are limited in coastal waters especially with strong optical layers. Optical properties and in particular scattering and absorption play an important role on systems performance. Surface optical properties alone from satellite are not adequate to determine how well a system will perform at depth due to the existence of optical layers. The spatial and temporal characteristics of the 3d optical variability of the coastal waters along with strength and location of subsurface optical layers maximize chances of identifying underwater targets by exploiting optimum sensor deployment. Advanced methods have been developed to fuse the optical measurements from gliders, optical properties from \u0026quot;surface\u0026quot; satellite snapshot and 3-D ocean circulation models to extend the two-dimensional (2-D) surface satellite optical image into a three-dimensional (3-D) optical volume with subsurface optical layers. Modifications were made to an EOID performance model to integrate a 3-D optical volume covering an entire region of interest as input and derive system performance field. These enhancements extend present capability based on glider optics and EOID sensor models to estimate the system\u0026#x27;s \u0026quot;image quality\u0026quot;. This only yields system performance information for a single glider profile location in a very large operational region. Finally, we define the uncertainty of the system performance by coupling the EOID performance model with the 3-D optical volume uncertainties. Knowing the ensemble spread of EOID performance field provides a new and unique capability for tactical decision makers and Navy Operations.","owner":{"id":292391191,"first_name":"Alan","middle_initials":null,"last_name":"Weidemann","page_name":"WeidemannAlan","domain_name":"independent","created_at":"2023-11-14T08:25:11.103-08:00","display_name":"Alan Weidemann","url":"https://independent.academia.edu/WeidemannAlan"},"attachments":[],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering"},{"id":82,"name":"Optical Engineering","url":"https://www.academia.edu/Documents/in/Optical_Engineering"},{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science"},{"id":516,"name":"Optics","url":"https://www.academia.edu/Documents/in/Optics"},{"id":1252,"name":"Remote Sensing","url":"https://www.academia.edu/Documents/in/Remote_Sensing"},{"id":16691,"name":"Physical Oceanography","url":"https://www.academia.edu/Documents/in/Physical_Oceanography"},{"id":30415,"name":"Image Quality","url":"https://www.academia.edu/Documents/in/Image_Quality"},{"id":33302,"name":"Optical Imaging","url":"https://www.academia.edu/Documents/in/Optical_Imaging"},{"id":55405,"name":"Sensors","url":"https://www.academia.edu/Documents/in/Sensors"},{"id":113239,"name":"Ocean Circulation","url":"https://www.academia.edu/Documents/in/Ocean_Circulation"},{"id":113434,"name":"Performance Model","url":"https://www.academia.edu/Documents/in/Performance_Model"},{"id":162983,"name":"Absorption","url":"https://www.academia.edu/Documents/in/Absorption"},{"id":185380,"name":"Optical Properties","url":"https://www.academia.edu/Documents/in/Optical_Properties"},{"id":215106,"name":"Satellite","url":"https://www.academia.edu/Documents/in/Satellite"},{"id":441926,"name":"Scattering","url":"https://www.academia.edu/Documents/in/Scattering"},{"id":571946,"name":"Coastal waters","url":"https://www.academia.edu/Documents/in/Coastal_waters"},{"id":821516,"name":"Decision Maker","url":"https://www.academia.edu/Documents/in/Decision_Maker"},{"id":1372278,"name":"Region of Interest","url":"https://www.academia.edu/Documents/in/Region_of_Interest"},{"id":2504944,"name":"Sensor deployment","url":"https://www.academia.edu/Documents/in/Sensor_deployment"},{"id":3705880,"name":"Glider","url":"https://www.academia.edu/Documents/in/Glider"}],"urls":[{"id":41506884,"url":"https://doi.org/10.1117/12.821724"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="118287495"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/118287495/Measurements_of_turbulent_dissipation_during_the_Bahamas_Optical_Turbulence_Experiment"><img alt="Research paper thumbnail of Measurements of turbulent dissipation during the Bahamas Optical Turbulence Experiment" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/118287495/Measurements_of_turbulent_dissipation_during_the_Bahamas_Optical_Turbulence_Experiment">Measurements of turbulent dissipation during the Bahamas Optical Turbulence Experiment</a></div><div class="wp-workCard_item"><span>Proceedings of SPIE</span><span>, Jun 3, 2013</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT The Bahamas Optical Turbulence Experiment (BOTEX) was conducted in the summer of 2011 to...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">ABSTRACT The Bahamas Optical Turbulence Experiment (BOTEX) was conducted in the summer of 2011 to investigate the impact of turbulence on underwater optical imaging. Underwater optical properties can be affected by turbulence in the water, due to localized changes in the index of refraction. We discuss measurements of current velocity and temperature, made with a Nortek Vector Acoustic Doppler Velocimeter (ADV) and PME Conductivity- Temperature (CT) probe, as well as observations made with a Rockland Oceanographic Vertical Microstructure Profiler (VMP). The instruments were deployed in close proximity in the field and in the context of measurements of optical target clarity. Turbulent kinetic energy dissipation (TKED) and temperature dissipation (TD) rates are calculated from the ADV/CT measurements and compared to TKED and TD estimated from the data collected with the VMP. The results show reasonable agreement between the two methods; differences are attributed to turbulence patchiness and intermittence, as well as sampling challenges. The study also highlights the importance of collecting concurrent data on temperature, current velocity, and current shear to assess the turbulence impact on underwater optical properties.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287495"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287495"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287495; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287495]").text(description); $(".js-view-count[data-work-id=118287495]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287495; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287495']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287495, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=118287495]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287495,"title":"Measurements of turbulent dissipation during the Bahamas Optical Turbulence Experiment","translated_title":"","metadata":{"abstract":"ABSTRACT The Bahamas Optical Turbulence Experiment (BOTEX) was conducted in the summer of 2011 to investigate the impact of turbulence on underwater optical imaging. Underwater optical properties can be affected by turbulence in the water, due to localized changes in the index of refraction. We discuss measurements of current velocity and temperature, made with a Nortek Vector Acoustic Doppler Velocimeter (ADV) and PME Conductivity- Temperature (CT) probe, as well as observations made with a Rockland Oceanographic Vertical Microstructure Profiler (VMP). The instruments were deployed in close proximity in the field and in the context of measurements of optical target clarity. Turbulent kinetic energy dissipation (TKED) and temperature dissipation (TD) rates are calculated from the ADV/CT measurements and compared to TKED and TD estimated from the data collected with the VMP. The results show reasonable agreement between the two methods; differences are attributed to turbulence patchiness and intermittence, as well as sampling challenges. The study also highlights the importance of collecting concurrent data on temperature, current velocity, and current shear to assess the turbulence impact on underwater optical properties.","publisher":"SPIE","publication_date":{"day":3,"month":6,"year":2013,"errors":{}},"publication_name":"Proceedings of SPIE"},"translated_abstract":"ABSTRACT The Bahamas Optical Turbulence Experiment (BOTEX) was conducted in the summer of 2011 to investigate the impact of turbulence on underwater optical imaging. Underwater optical properties can be affected by turbulence in the water, due to localized changes in the index of refraction. We discuss measurements of current velocity and temperature, made with a Nortek Vector Acoustic Doppler Velocimeter (ADV) and PME Conductivity- Temperature (CT) probe, as well as observations made with a Rockland Oceanographic Vertical Microstructure Profiler (VMP). The instruments were deployed in close proximity in the field and in the context of measurements of optical target clarity. Turbulent kinetic energy dissipation (TKED) and temperature dissipation (TD) rates are calculated from the ADV/CT measurements and compared to TKED and TD estimated from the data collected with the VMP. The results show reasonable agreement between the two methods; differences are attributed to turbulence patchiness and intermittence, as well as sampling challenges. The study also highlights the importance of collecting concurrent data on temperature, current velocity, and current shear to assess the turbulence impact on underwater optical properties.","internal_url":"https://www.academia.edu/118287495/Measurements_of_turbulent_dissipation_during_the_Bahamas_Optical_Turbulence_Experiment","translated_internal_url":"","created_at":"2024-04-29T13:35:57.767-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":292391191,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Measurements_of_turbulent_dissipation_during_the_Bahamas_Optical_Turbulence_Experiment","translated_slug":"","page_count":null,"language":"en","content_type":"Work","summary":"ABSTRACT The Bahamas Optical Turbulence Experiment (BOTEX) was conducted in the summer of 2011 to investigate the impact of turbulence on underwater optical imaging. Underwater optical properties can be affected by turbulence in the water, due to localized changes in the index of refraction. We discuss measurements of current velocity and temperature, made with a Nortek Vector Acoustic Doppler Velocimeter (ADV) and PME Conductivity- Temperature (CT) probe, as well as observations made with a Rockland Oceanographic Vertical Microstructure Profiler (VMP). The instruments were deployed in close proximity in the field and in the context of measurements of optical target clarity. Turbulent kinetic energy dissipation (TKED) and temperature dissipation (TD) rates are calculated from the ADV/CT measurements and compared to TKED and TD estimated from the data collected with the VMP. The results show reasonable agreement between the two methods; differences are attributed to turbulence patchiness and intermittence, as well as sampling challenges. The study also highlights the importance of collecting concurrent data on temperature, current velocity, and current shear to assess the turbulence impact on underwater optical properties.","owner":{"id":292391191,"first_name":"Alan","middle_initials":null,"last_name":"Weidemann","page_name":"WeidemannAlan","domain_name":"independent","created_at":"2023-11-14T08:25:11.103-08:00","display_name":"Alan Weidemann","url":"https://independent.academia.edu/WeidemannAlan"},"attachments":[],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering"},{"id":498,"name":"Physics","url":"https://www.academia.edu/Documents/in/Physics"},{"id":2802,"name":"Turbulence","url":"https://www.academia.edu/Documents/in/Turbulence"},{"id":79704,"name":"Underwater","url":"https://www.academia.edu/Documents/in/Underwater"},{"id":222949,"name":"Dissipation","url":"https://www.academia.edu/Documents/in/Dissipation"},{"id":2467844,"name":"Turbulence kinetic energy","url":"https://www.academia.edu/Documents/in/Turbulence_kinetic_energy"}],"urls":[{"id":41506883,"url":"https://doi.org/10.1117/12.2018303"}]}, dispatcherData: dispatcherData }); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="118287492"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/118287492/Uncertainties_assessment_and_satellite_validation_over_2_years_time_series_of_multispectral_and_hyperspectral_measurements_in_coastal_waters_at_Long_Island_Sound_Coastal_Observatory"><img alt="Research paper thumbnail of Uncertainties assessment and satellite validation over 2 years time series of multispectral and hyperspectral measurements in coastal waters at Long Island Sound Coastal Observatory" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/118287492/Uncertainties_assessment_and_satellite_validation_over_2_years_time_series_of_multispectral_and_hyperspectral_measurements_in_coastal_waters_at_Long_Island_Sound_Coastal_Observatory">Uncertainties assessment and satellite validation over 2 years time series of multispectral and hyperspectral measurements in coastal waters at Long Island Sound Coastal Observatory</a></div><div class="wp-workCard_item"><span>Proceedings of SPIE</span><span>, Oct 6, 2011</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Optical remote sensing of coastal waters from space is a basic requirement for monitoring global ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Optical remote sensing of coastal waters from space is a basic requirement for monitoring global water quality and assessing anthropogenic impacts. However, this task remains highly challenging due to the optical complexity of the atmosphere-water system in coastal areas. In order to support present and future multi- and hyper-spectral calibration/validation activities for the Ocean Color Radiometry (OCR) satellites, as well</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287492"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287492"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287492; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287492]").text(description); $(".js-view-count[data-work-id=118287492]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287492; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287492']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287492, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=118287492]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287492,"title":"Uncertainties assessment and satellite validation over 2 years time series of multispectral and hyperspectral measurements in coastal waters at Long Island Sound Coastal Observatory","translated_title":"","metadata":{"abstract":"Optical remote sensing of coastal waters from space is a basic requirement for monitoring global water quality and assessing anthropogenic impacts. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="118287490"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/118287490/Megacollect_2004_hyperspectral_collection_experiment_over_the_waters_of_the_Rochester_Embayment"><img alt="Research paper thumbnail of Megacollect 2004: hyperspectral collection experiment over the waters of the Rochester Embayment" class="work-thumbnail" src="https://attachments.academia-assets.com/113950449/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/118287490/Megacollect_2004_hyperspectral_collection_experiment_over_the_waters_of_the_Rochester_Embayment">Megacollect 2004: hyperspectral collection experiment over the waters of the Rochester Embayment</a></div><div class="wp-workCard_item"><span>Proceedings of SPIE</span><span>, Jun 1, 2005</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This work describes the water collection experiment component of the Megacollect 2004 campaign. M...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This work describes the water collection experiment component of the Megacollect 2004 campaign. Megacollect was a collaborative campaign coordinated by RIT with several institutions to spectrally measure various target/background scenarios with airborne sensors and ground instruments. An extension to the terrestrial campaign was an effort to simultaneously measure water optical properties in different bodies of water in the Rochester Embayment. This collection updates a previous effort in which water surface measurements were made during an AVIRIS mission over the Rochester Embayment (May 1999). Megacollect 2004 builds on this through an expanded campaign that increased the number of stations sampled, extended the spectral range of measurements, and improved the spatial resolution of the imagery through the use of multiple sensors (COMPASS, SEBASS, MISI, WASP). A larger set of in-water instruments were deployed on several vessels to sample and measure water optical properties near the shores of Lake Ontario, the northern portions of Irondequoit Bay, and several smaller ponds and bays in the Rochester Embayment. This paper describes the different in-water instruments deployed, the measurements obtained and how they will be used for future modeling efforts and development of hyperspectral algorithms.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="2a7132c58993fa141c5c8962cd5aad34" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":113950449,"asset_id":118287490,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/113950449/download_file?st=MTczNDE3MDA2Niw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287490"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287490"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287490; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287490]").text(description); $(".js-view-count[data-work-id=118287490]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287490; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287490']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287490, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "2a7132c58993fa141c5c8962cd5aad34" } } $('.js-work-strip[data-work-id=118287490]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287490,"title":"Megacollect 2004: hyperspectral collection experiment over the waters of the Rochester Embayment","translated_title":"","metadata":{"publisher":"SPIE","grobid_abstract":"This work describes the water collection experiment component of the Megacollect 2004 campaign. 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Megacollect was a collaborative campaign coordinated by RIT with several institutions to spectrally measure various target/background scenarios with airborne sensors and ground instruments. An extension to the terrestrial campaign was an effort to simultaneously measure water optical properties in different bodies of water in the Rochester Embayment. This collection updates a previous effort in which water surface measurements were made during an AVIRIS mission over the Rochester Embayment (May 1999). Megacollect 2004 builds on this through an expanded campaign that increased the number of stations sampled, extended the spectral range of measurements, and improved the spatial resolution of the imagery through the use of multiple sensors (COMPASS, SEBASS, MISI, WASP). A larger set of in-water instruments were deployed on several vessels to sample and measure water optical properties near the shores of Lake Ontario, the northern portions of Irondequoit Bay, and several smaller ponds and bays in the Rochester Embayment. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="118287489"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/118287489/Bidirectional_reflectance_function_in_coastal_waters_modeling_and_validation"><img alt="Research paper thumbnail of Bidirectional reflectance function in coastal waters: modeling and validation" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/118287489/Bidirectional_reflectance_function_in_coastal_waters_modeling_and_validation">Bidirectional reflectance function in coastal waters: modeling and validation</a></div><div class="wp-workCard_item"><span>Proceedings of SPIE</span><span>, Oct 6, 2011</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The current operational algorithm for the correction of bidirectional effects from the satellite ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The current operational algorithm for the correction of bidirectional effects from the satellite ocean color data is optimized for typical oceanic waters. However, versions of bidirectional reflectance correction algorithms, specifically tuned for typical coastal waters and other case 2 conditions, are particularly needed to improve the overall quality of those data. In order to analyze the bidirectional reflectance distribution function</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287489"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287489"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287489; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287489]").text(description); $(".js-view-count[data-work-id=118287489]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287489; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287489']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287489, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=118287489]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287489,"title":"Bidirectional reflectance function in coastal waters: modeling and validation","translated_title":"","metadata":{"abstract":"The current operational algorithm for the correction of bidirectional effects from the satellite ocean color data is optimized for typical oceanic waters. 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LISCO has both multispectral and hyperspectral radiometers for ocean color measurements. LISCO offers the potential for improving the calibration and validation activities of current and future Ocean Color satellite missions, as well as for satellite intercomparisons and spectral characterization</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287488"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287488"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287488; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287488]").text(description); $(".js-view-count[data-work-id=118287488]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287488; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287488']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287488, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=118287488]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287488,"title":"Hyperspectral and multispectral above-water radiometric measurements to monitor satellite data quality over coastal area","translated_title":"","metadata":{"abstract":"The Long Island Sound Coastal Observational platform (LISCO) near Northport, New York, has been recently established to support satellite data validation. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="118287487"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/118287487/_title_Tidal_influences_on_optical_variability_in_shallow_water_title_"><img alt="Research paper thumbnail of <title>Tidal influences on optical variability in shallow water</title>" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/118287487/_title_Tidal_influences_on_optical_variability_in_shallow_water_title_"><title>Tidal influences on optical variability in shallow water</title></a></div><div class="wp-workCard_item"><span>Proceedings of SPIE</span><span>, Feb 6, 1997</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287487"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287487"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287487; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="118287486"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/118287486/_title_Modeling_of_elastic_and_inelastic_scattering_effects_in_oceanic_optics_title_"><img alt="Research paper thumbnail of <title>Modeling of elastic and inelastic scattering effects in oceanic optics</title>" class="work-thumbnail" src="https://attachments.academia-assets.com/113950436/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/118287486/_title_Modeling_of_elastic_and_inelastic_scattering_effects_in_oceanic_optics_title_"><title>Modeling of elastic and inelastic scattering effects in oceanic optics</title></a></div><div class="wp-workCard_item"><span>Proceedings of SPIE</span><span>, Feb 6, 1997</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The results of model calculations of apparent optical properties for realistic marine waters with...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The results of model calculations of apparent optical properties for realistic marine waters with inclusion of Raman scattering and fluorescence are presented. It is shown that the underwater light spectrum can be divided, by a threshold wavelength, into two regions with different behavior of apparent optical properties, and also that inelastic effects are significant and should be considered in ocean optics measurements.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="99071018f998a631264df4873c80149e" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":113950436,"asset_id":118287486,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/113950436/download_file?st=MTczNDE3MDA2Niw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287486"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287486"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287486; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287486]").text(description); $(".js-view-count[data-work-id=118287486]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287486; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287486']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287486, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "99071018f998a631264df4873c80149e" } } $('.js-work-strip[data-work-id=118287486]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287486,"title":"\u003ctitle\u003eModeling of elastic and inelastic scattering effects in oceanic optics\u003c/title\u003e","translated_title":"","metadata":{"publisher":"SPIE","grobid_abstract":"The results of model calculations of apparent optical properties for realistic marine waters with inclusion of Raman scattering and fluorescence are presented. 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Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing the burden, to the Department of Defense, Executive Services and Communications Directorate (0704-0188). Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="1ff8c5af84b991612fcf5d932a11ca7c" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":114203310,"asset_id":118287484,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/114203310/download_file?st=MTczNDE3MDA2Niw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287484"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287484"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287484; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287484]").text(description); $(".js-view-count[data-work-id=118287484]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287484; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287484']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287484, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "1ff8c5af84b991612fcf5d932a11ca7c" } } $('.js-work-strip[data-work-id=118287484]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287484,"title":"Diver visibility: Why one cannot see as far?","translated_title":"","metadata":{"publisher":"SPIE","grobid_abstract":"The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. 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Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number.","publication_date":{"day":1,"month":5,"year":2009,"errors":{}},"publication_name":"Proceedings of SPIE","grobid_abstract_attachment_id":114203310},"translated_abstract":null,"internal_url":"https://www.academia.edu/118287484/Diver_visibility_Why_one_cannot_see_as_far","translated_internal_url":"","created_at":"2024-04-29T13:35:52.876-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":292391191,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":114203310,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/114203310/thumbnails/1.jpg","file_name":"a503552.pdf","download_url":"https://www.academia.edu/attachments/114203310/download_file?st=MTczNDE3MDA2Niw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Diver_visibility_Why_one_cannot_see_as_f.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/114203310/a503552-libre.pdf?1714988520=\u0026response-content-disposition=attachment%3B+filename%3DDiver_visibility_Why_one_cannot_see_as_f.pdf\u0026Expires=1734173666\u0026Signature=dtz8qtQJU4bkGA2BwQU~JtOnPE9U~Sb3H01BnEq9CnCB~Kmi2QXMgpYzMlMWRyEIGNIxyv7aACpGT50SMdLDwGay~41Cg0Ofw6gKfp6PzVXw9G-bPR73ywrabQ9WuBHcbIPeWPe~vNva1F~IeMqxSyifgnR5xCiESSfBqY2G6iT6YCWiARxB0G0WRsWNdpdA9XBLAGCdqvhwGwP3CVNhb~LVVyd4oLC7~h~-O1H3T3k~CT8YQWZHlt0V85XMij5PF9gHu9X2UDr9QCtuOR2ieXy1sUpsWRfDyTyV2~be8UjdE1DuEGVL-82S1VmjTZ6KPOPNA2SEgX6i5xuEtDnomw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Diver_visibility_Why_one_cannot_see_as_far","translated_slug":"","page_count":8,"language":"en","content_type":"Work","summary":"The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. 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During the same time period, in-situ profiles of temperature, salinity, inherent optical properties, and chlorophyll a fluorescence were measured using two surface vessels, two autonomous gliders, and an autonomous profiling mooring. Water samples</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287500"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287500"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287500; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287500]").text(description); $(".js-view-count[data-work-id=118287500]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287500; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287500']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287500, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=118287500]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287500,"title":"Tracking the Progression of a Diatom Bloom with Airborne Lidar","translated_title":"","metadata":{"abstract":"Between 16 and 26 May 2009, the NOAA airborne lidar was used to monitor the progression of a single-species diatom bloom in East Sound, Orcas Island, Washington. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="118287497"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/118287497/Polarization_characteristics_of_coastal_waters_and_their_impact_on_in_water_visibility"><img alt="Research paper thumbnail of Polarization characteristics of coastal waters and their impact on in-water visibility" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/118287497/Polarization_characteristics_of_coastal_waters_and_their_impact_on_in_water_visibility">Polarization characteristics of coastal waters and their impact on in-water visibility</a></div><div class="wp-workCard_item"><span>Proceedings of SPIE</span><span>, May 1, 2009</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Abstract: Polarization characteristics of coastal waters were recently measured during a cruise o...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Abstract: Polarization characteristics of coastal waters were recently measured during a cruise on the R/V&amp;amp;amp;amp;quot; Connecticut&amp;amp;amp;amp;quot; in the areas of New York Harbor-Sandy Hook. NJ region using a new Stokes vector instrument developed by the Optical Remote Sensing ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287497"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287497"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287497; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287497]").text(description); $(".js-view-count[data-work-id=118287497]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287497; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287497']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287497, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=118287497]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287497,"title":"Polarization characteristics of coastal waters and their impact on in-water visibility","translated_title":"","metadata":{"abstract":"Abstract: Polarization characteristics of coastal waters were recently measured during a cruise on the R/V\u0026amp;amp;amp;amp;quot; Connecticut\u0026amp;amp;amp;amp;quot; in the areas of New York Harbor-Sandy Hook. NJ region using a new Stokes vector instrument developed by the Optical Remote Sensing ...","publisher":"SPIE","publication_date":{"day":1,"month":5,"year":2009,"errors":{}},"publication_name":"Proceedings of SPIE"},"translated_abstract":"Abstract: Polarization characteristics of coastal waters were recently measured during a cruise on the R/V\u0026amp;amp;amp;amp;quot; Connecticut\u0026amp;amp;amp;amp;quot; in the areas of New York Harbor-Sandy Hook. 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NJ region using a new Stokes vector instrument developed by the Optical Remote Sensing ...","owner":{"id":292391191,"first_name":"Alan","middle_initials":null,"last_name":"Weidemann","page_name":"WeidemannAlan","domain_name":"independent","created_at":"2023-11-14T08:25:11.103-08:00","display_name":"Alan Weidemann","url":"https://independent.academia.edu/WeidemannAlan"},"attachments":[],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering"},{"id":498,"name":"Physics","url":"https://www.academia.edu/Documents/in/Physics"},{"id":516,"name":"Optics","url":"https://www.academia.edu/Documents/in/Optics"},{"id":4392,"name":"Monte Carlo Simulation","url":"https://www.academia.edu/Documents/in/Monte_Carlo_Simulation"},{"id":6974,"name":"Monte Carlo","url":"https://www.academia.edu/Documents/in/Monte_Carlo"},{"id":16691,"name":"Physical Oceanography","url":"https://www.academia.edu/Documents/in/Physical_Oceanography"},{"id":27497,"name":"Instrumentation","url":"https://www.academia.edu/Documents/in/Instrumentation"},{"id":31486,"name":"Coding","url":"https://www.academia.edu/Documents/in/Coding"},{"id":34019,"name":"Monte Carlo Methods","url":"https://www.academia.edu/Documents/in/Monte_Carlo_Methods"},{"id":75942,"name":"Atmosphere","url":"https://www.academia.edu/Documents/in/Atmosphere"},{"id":410497,"name":"Angles","url":"https://www.academia.edu/Documents/in/Angles"},{"id":542508,"name":"Optical Remote Sensing","url":"https://www.academia.edu/Documents/in/Optical_Remote_Sensing"},{"id":571946,"name":"Coastal waters","url":"https://www.academia.edu/Documents/in/Coastal_waters"},{"id":742038,"name":"Instrument Development","url":"https://www.academia.edu/Documents/in/Instrument_Development"},{"id":972674,"name":"Hyperspectral Imagery","url":"https://www.academia.edu/Documents/in/Hyperspectral_Imagery"},{"id":1112728,"name":"Point Spread Function","url":"https://www.academia.edu/Documents/in/Point_Spread_Function"},{"id":1228128,"name":"Point Spread Functions","url":"https://www.academia.edu/Documents/in/Point_Spread_Functions"},{"id":1333436,"name":"Monte Carlo Method","url":"https://www.academia.edu/Documents/in/Monte_Carlo_Method"},{"id":2236006,"name":"Degree of polarization","url":"https://www.academia.edu/Documents/in/Degree_of_polarization"},{"id":3122382,"name":"imaging system","url":"https://www.academia.edu/Documents/in/imaging_system"}],"urls":[{"id":41506885,"url":"https://doi.org/10.1117/12.820738"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="118287496"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/118287496/Defining_the_uncertainty_of_electro_optical_identification_system_performance_estimates_using_a_3D_optical_environment_derived_from_satellite"><img alt="Research paper thumbnail of Defining the uncertainty of electro-optical identification system performance estimates using a 3D optical environment derived from satellite" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/118287496/Defining_the_uncertainty_of_electro_optical_identification_system_performance_estimates_using_a_3D_optical_environment_derived_from_satellite">Defining the uncertainty of electro-optical identification system performance estimates using a 3D optical environment derived from satellite</a></div><div class="wp-workCard_item"><span>Proceedings of SPIE</span><span>, May 1, 2009</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Current United States Navy Mine-Counter-Measure (MCM) operations primarily use electro-optical id...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Current United States Navy Mine-Counter-Measure (MCM) operations primarily use electro-optical identification (EOID) sensors to identify underwater targets after detection via acoustic sensors. These EOID sensors which are based on laser underwater imaging by design work best in &quot;clear&quot; waters and are limited in coastal waters especially with strong optical layers. Optical properties and in particular scattering and absorption play an important role on systems performance. Surface optical properties alone from satellite are not adequate to determine how well a system will perform at depth due to the existence of optical layers. The spatial and temporal characteristics of the 3d optical variability of the coastal waters along with strength and location of subsurface optical layers maximize chances of identifying underwater targets by exploiting optimum sensor deployment. Advanced methods have been developed to fuse the optical measurements from gliders, optical properties from &quot;surface&quot; satellite snapshot and 3-D ocean circulation models to extend the two-dimensional (2-D) surface satellite optical image into a three-dimensional (3-D) optical volume with subsurface optical layers. Modifications were made to an EOID performance model to integrate a 3-D optical volume covering an entire region of interest as input and derive system performance field. These enhancements extend present capability based on glider optics and EOID sensor models to estimate the system&#x27;s &quot;image quality&quot;. This only yields system performance information for a single glider profile location in a very large operational region. Finally, we define the uncertainty of the system performance by coupling the EOID performance model with the 3-D optical volume uncertainties. Knowing the ensemble spread of EOID performance field provides a new and unique capability for tactical decision makers and Navy Operations.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287496"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287496"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287496; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287496]").text(description); $(".js-view-count[data-work-id=118287496]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287496; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287496']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287496, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=118287496]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287496,"title":"Defining the uncertainty of electro-optical identification system performance estimates using a 3D optical environment derived from satellite","translated_title":"","metadata":{"abstract":"Current United States Navy Mine-Counter-Measure (MCM) operations primarily use electro-optical identification (EOID) sensors to identify underwater targets after detection via acoustic sensors. These EOID sensors which are based on laser underwater imaging by design work best in \u0026quot;clear\u0026quot; waters and are limited in coastal waters especially with strong optical layers. Optical properties and in particular scattering and absorption play an important role on systems performance. Surface optical properties alone from satellite are not adequate to determine how well a system will perform at depth due to the existence of optical layers. The spatial and temporal characteristics of the 3d optical variability of the coastal waters along with strength and location of subsurface optical layers maximize chances of identifying underwater targets by exploiting optimum sensor deployment. Advanced methods have been developed to fuse the optical measurements from gliders, optical properties from \u0026quot;surface\u0026quot; satellite snapshot and 3-D ocean circulation models to extend the two-dimensional (2-D) surface satellite optical image into a three-dimensional (3-D) optical volume with subsurface optical layers. Modifications were made to an EOID performance model to integrate a 3-D optical volume covering an entire region of interest as input and derive system performance field. These enhancements extend present capability based on glider optics and EOID sensor models to estimate the system\u0026#x27;s \u0026quot;image quality\u0026quot;. This only yields system performance information for a single glider profile location in a very large operational region. Finally, we define the uncertainty of the system performance by coupling the EOID performance model with the 3-D optical volume uncertainties. Knowing the ensemble spread of EOID performance field provides a new and unique capability for tactical decision makers and Navy Operations.","publisher":"SPIE","publication_date":{"day":1,"month":5,"year":2009,"errors":{}},"publication_name":"Proceedings of SPIE"},"translated_abstract":"Current United States Navy Mine-Counter-Measure (MCM) operations primarily use electro-optical identification (EOID) sensors to identify underwater targets after detection via acoustic sensors. These EOID sensors which are based on laser underwater imaging by design work best in \u0026quot;clear\u0026quot; waters and are limited in coastal waters especially with strong optical layers. Optical properties and in particular scattering and absorption play an important role on systems performance. Surface optical properties alone from satellite are not adequate to determine how well a system will perform at depth due to the existence of optical layers. The spatial and temporal characteristics of the 3d optical variability of the coastal waters along with strength and location of subsurface optical layers maximize chances of identifying underwater targets by exploiting optimum sensor deployment. Advanced methods have been developed to fuse the optical measurements from gliders, optical properties from \u0026quot;surface\u0026quot; satellite snapshot and 3-D ocean circulation models to extend the two-dimensional (2-D) surface satellite optical image into a three-dimensional (3-D) optical volume with subsurface optical layers. Modifications were made to an EOID performance model to integrate a 3-D optical volume covering an entire region of interest as input and derive system performance field. These enhancements extend present capability based on glider optics and EOID sensor models to estimate the system\u0026#x27;s \u0026quot;image quality\u0026quot;. This only yields system performance information for a single glider profile location in a very large operational region. Finally, we define the uncertainty of the system performance by coupling the EOID performance model with the 3-D optical volume uncertainties. Knowing the ensemble spread of EOID performance field provides a new and unique capability for tactical decision makers and Navy Operations.","internal_url":"https://www.academia.edu/118287496/Defining_the_uncertainty_of_electro_optical_identification_system_performance_estimates_using_a_3D_optical_environment_derived_from_satellite","translated_internal_url":"","created_at":"2024-04-29T13:35:58.013-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":292391191,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Defining_the_uncertainty_of_electro_optical_identification_system_performance_estimates_using_a_3D_optical_environment_derived_from_satellite","translated_slug":"","page_count":null,"language":"en","content_type":"Work","summary":"Current United States Navy Mine-Counter-Measure (MCM) operations primarily use electro-optical identification (EOID) sensors to identify underwater targets after detection via acoustic sensors. These EOID sensors which are based on laser underwater imaging by design work best in \u0026quot;clear\u0026quot; waters and are limited in coastal waters especially with strong optical layers. Optical properties and in particular scattering and absorption play an important role on systems performance. Surface optical properties alone from satellite are not adequate to determine how well a system will perform at depth due to the existence of optical layers. The spatial and temporal characteristics of the 3d optical variability of the coastal waters along with strength and location of subsurface optical layers maximize chances of identifying underwater targets by exploiting optimum sensor deployment. Advanced methods have been developed to fuse the optical measurements from gliders, optical properties from \u0026quot;surface\u0026quot; satellite snapshot and 3-D ocean circulation models to extend the two-dimensional (2-D) surface satellite optical image into a three-dimensional (3-D) optical volume with subsurface optical layers. Modifications were made to an EOID performance model to integrate a 3-D optical volume covering an entire region of interest as input and derive system performance field. These enhancements extend present capability based on glider optics and EOID sensor models to estimate the system\u0026#x27;s \u0026quot;image quality\u0026quot;. This only yields system performance information for a single glider profile location in a very large operational region. Finally, we define the uncertainty of the system performance by coupling the EOID performance model with the 3-D optical volume uncertainties. Knowing the ensemble spread of EOID performance field provides a new and unique capability for tactical decision makers and Navy Operations.","owner":{"id":292391191,"first_name":"Alan","middle_initials":null,"last_name":"Weidemann","page_name":"WeidemannAlan","domain_name":"independent","created_at":"2023-11-14T08:25:11.103-08:00","display_name":"Alan Weidemann","url":"https://independent.academia.edu/WeidemannAlan"},"attachments":[],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering"},{"id":82,"name":"Optical Engineering","url":"https://www.academia.edu/Documents/in/Optical_Engineering"},{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science"},{"id":516,"name":"Optics","url":"https://www.academia.edu/Documents/in/Optics"},{"id":1252,"name":"Remote Sensing","url":"https://www.academia.edu/Documents/in/Remote_Sensing"},{"id":16691,"name":"Physical Oceanography","url":"https://www.academia.edu/Documents/in/Physical_Oceanography"},{"id":30415,"name":"Image Quality","url":"https://www.academia.edu/Documents/in/Image_Quality"},{"id":33302,"name":"Optical Imaging","url":"https://www.academia.edu/Documents/in/Optical_Imaging"},{"id":55405,"name":"Sensors","url":"https://www.academia.edu/Documents/in/Sensors"},{"id":113239,"name":"Ocean Circulation","url":"https://www.academia.edu/Documents/in/Ocean_Circulation"},{"id":113434,"name":"Performance Model","url":"https://www.academia.edu/Documents/in/Performance_Model"},{"id":162983,"name":"Absorption","url":"https://www.academia.edu/Documents/in/Absorption"},{"id":185380,"name":"Optical Properties","url":"https://www.academia.edu/Documents/in/Optical_Properties"},{"id":215106,"name":"Satellite","url":"https://www.academia.edu/Documents/in/Satellite"},{"id":441926,"name":"Scattering","url":"https://www.academia.edu/Documents/in/Scattering"},{"id":571946,"name":"Coastal waters","url":"https://www.academia.edu/Documents/in/Coastal_waters"},{"id":821516,"name":"Decision Maker","url":"https://www.academia.edu/Documents/in/Decision_Maker"},{"id":1372278,"name":"Region of Interest","url":"https://www.academia.edu/Documents/in/Region_of_Interest"},{"id":2504944,"name":"Sensor deployment","url":"https://www.academia.edu/Documents/in/Sensor_deployment"},{"id":3705880,"name":"Glider","url":"https://www.academia.edu/Documents/in/Glider"}],"urls":[{"id":41506884,"url":"https://doi.org/10.1117/12.821724"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="118287495"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/118287495/Measurements_of_turbulent_dissipation_during_the_Bahamas_Optical_Turbulence_Experiment"><img alt="Research paper thumbnail of Measurements of turbulent dissipation during the Bahamas Optical Turbulence Experiment" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/118287495/Measurements_of_turbulent_dissipation_during_the_Bahamas_Optical_Turbulence_Experiment">Measurements of turbulent dissipation during the Bahamas Optical Turbulence Experiment</a></div><div class="wp-workCard_item"><span>Proceedings of SPIE</span><span>, Jun 3, 2013</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT The Bahamas Optical Turbulence Experiment (BOTEX) was conducted in the summer of 2011 to...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">ABSTRACT The Bahamas Optical Turbulence Experiment (BOTEX) was conducted in the summer of 2011 to investigate the impact of turbulence on underwater optical imaging. Underwater optical properties can be affected by turbulence in the water, due to localized changes in the index of refraction. We discuss measurements of current velocity and temperature, made with a Nortek Vector Acoustic Doppler Velocimeter (ADV) and PME Conductivity- Temperature (CT) probe, as well as observations made with a Rockland Oceanographic Vertical Microstructure Profiler (VMP). The instruments were deployed in close proximity in the field and in the context of measurements of optical target clarity. Turbulent kinetic energy dissipation (TKED) and temperature dissipation (TD) rates are calculated from the ADV/CT measurements and compared to TKED and TD estimated from the data collected with the VMP. The results show reasonable agreement between the two methods; differences are attributed to turbulence patchiness and intermittence, as well as sampling challenges. The study also highlights the importance of collecting concurrent data on temperature, current velocity, and current shear to assess the turbulence impact on underwater optical properties.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287495"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287495"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287495; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287495]").text(description); $(".js-view-count[data-work-id=118287495]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287495; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287495']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287495, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=118287495]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287495,"title":"Measurements of turbulent dissipation during the Bahamas Optical Turbulence Experiment","translated_title":"","metadata":{"abstract":"ABSTRACT The Bahamas Optical Turbulence Experiment (BOTEX) was conducted in the summer of 2011 to investigate the impact of turbulence on underwater optical imaging. Underwater optical properties can be affected by turbulence in the water, due to localized changes in the index of refraction. We discuss measurements of current velocity and temperature, made with a Nortek Vector Acoustic Doppler Velocimeter (ADV) and PME Conductivity- Temperature (CT) probe, as well as observations made with a Rockland Oceanographic Vertical Microstructure Profiler (VMP). The instruments were deployed in close proximity in the field and in the context of measurements of optical target clarity. Turbulent kinetic energy dissipation (TKED) and temperature dissipation (TD) rates are calculated from the ADV/CT measurements and compared to TKED and TD estimated from the data collected with the VMP. The results show reasonable agreement between the two methods; differences are attributed to turbulence patchiness and intermittence, as well as sampling challenges. The study also highlights the importance of collecting concurrent data on temperature, current velocity, and current shear to assess the turbulence impact on underwater optical properties.","publisher":"SPIE","publication_date":{"day":3,"month":6,"year":2013,"errors":{}},"publication_name":"Proceedings of SPIE"},"translated_abstract":"ABSTRACT The Bahamas Optical Turbulence Experiment (BOTEX) was conducted in the summer of 2011 to investigate the impact of turbulence on underwater optical imaging. Underwater optical properties can be affected by turbulence in the water, due to localized changes in the index of refraction. We discuss measurements of current velocity and temperature, made with a Nortek Vector Acoustic Doppler Velocimeter (ADV) and PME Conductivity- Temperature (CT) probe, as well as observations made with a Rockland Oceanographic Vertical Microstructure Profiler (VMP). The instruments were deployed in close proximity in the field and in the context of measurements of optical target clarity. Turbulent kinetic energy dissipation (TKED) and temperature dissipation (TD) rates are calculated from the ADV/CT measurements and compared to TKED and TD estimated from the data collected with the VMP. The results show reasonable agreement between the two methods; differences are attributed to turbulence patchiness and intermittence, as well as sampling challenges. The study also highlights the importance of collecting concurrent data on temperature, current velocity, and current shear to assess the turbulence impact on underwater optical properties.","internal_url":"https://www.academia.edu/118287495/Measurements_of_turbulent_dissipation_during_the_Bahamas_Optical_Turbulence_Experiment","translated_internal_url":"","created_at":"2024-04-29T13:35:57.767-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":292391191,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Measurements_of_turbulent_dissipation_during_the_Bahamas_Optical_Turbulence_Experiment","translated_slug":"","page_count":null,"language":"en","content_type":"Work","summary":"ABSTRACT The Bahamas Optical Turbulence Experiment (BOTEX) was conducted in the summer of 2011 to investigate the impact of turbulence on underwater optical imaging. Underwater optical properties can be affected by turbulence in the water, due to localized changes in the index of refraction. We discuss measurements of current velocity and temperature, made with a Nortek Vector Acoustic Doppler Velocimeter (ADV) and PME Conductivity- Temperature (CT) probe, as well as observations made with a Rockland Oceanographic Vertical Microstructure Profiler (VMP). The instruments were deployed in close proximity in the field and in the context of measurements of optical target clarity. Turbulent kinetic energy dissipation (TKED) and temperature dissipation (TD) rates are calculated from the ADV/CT measurements and compared to TKED and TD estimated from the data collected with the VMP. The results show reasonable agreement between the two methods; differences are attributed to turbulence patchiness and intermittence, as well as sampling challenges. The study also highlights the importance of collecting concurrent data on temperature, current velocity, and current shear to assess the turbulence impact on underwater optical properties.","owner":{"id":292391191,"first_name":"Alan","middle_initials":null,"last_name":"Weidemann","page_name":"WeidemannAlan","domain_name":"independent","created_at":"2023-11-14T08:25:11.103-08:00","display_name":"Alan Weidemann","url":"https://independent.academia.edu/WeidemannAlan"},"attachments":[],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering"},{"id":498,"name":"Physics","url":"https://www.academia.edu/Documents/in/Physics"},{"id":2802,"name":"Turbulence","url":"https://www.academia.edu/Documents/in/Turbulence"},{"id":79704,"name":"Underwater","url":"https://www.academia.edu/Documents/in/Underwater"},{"id":222949,"name":"Dissipation","url":"https://www.academia.edu/Documents/in/Dissipation"},{"id":2467844,"name":"Turbulence kinetic energy","url":"https://www.academia.edu/Documents/in/Turbulence_kinetic_energy"}],"urls":[{"id":41506883,"url":"https://doi.org/10.1117/12.2018303"}]}, dispatcherData: dispatcherData }); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="118287492"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/118287492/Uncertainties_assessment_and_satellite_validation_over_2_years_time_series_of_multispectral_and_hyperspectral_measurements_in_coastal_waters_at_Long_Island_Sound_Coastal_Observatory"><img alt="Research paper thumbnail of Uncertainties assessment and satellite validation over 2 years time series of multispectral and hyperspectral measurements in coastal waters at Long Island Sound Coastal Observatory" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/118287492/Uncertainties_assessment_and_satellite_validation_over_2_years_time_series_of_multispectral_and_hyperspectral_measurements_in_coastal_waters_at_Long_Island_Sound_Coastal_Observatory">Uncertainties assessment and satellite validation over 2 years time series of multispectral and hyperspectral measurements in coastal waters at Long Island Sound Coastal Observatory</a></div><div class="wp-workCard_item"><span>Proceedings of SPIE</span><span>, Oct 6, 2011</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Optical remote sensing of coastal waters from space is a basic requirement for monitoring global ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Optical remote sensing of coastal waters from space is a basic requirement for monitoring global water quality and assessing anthropogenic impacts. However, this task remains highly challenging due to the optical complexity of the atmosphere-water system in coastal areas. In order to support present and future multi- and hyper-spectral calibration/validation activities for the Ocean Color Radiometry (OCR) satellites, as well</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287492"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287492"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287492; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287492]").text(description); $(".js-view-count[data-work-id=118287492]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287492; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287492']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287492, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=118287492]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287492,"title":"Uncertainties assessment and satellite validation over 2 years time series of multispectral and hyperspectral measurements in coastal waters at Long Island Sound Coastal Observatory","translated_title":"","metadata":{"abstract":"Optical remote sensing of coastal waters from space is a basic requirement for monitoring global water quality and assessing anthropogenic impacts. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="118287490"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/118287490/Megacollect_2004_hyperspectral_collection_experiment_over_the_waters_of_the_Rochester_Embayment"><img alt="Research paper thumbnail of Megacollect 2004: hyperspectral collection experiment over the waters of the Rochester Embayment" class="work-thumbnail" src="https://attachments.academia-assets.com/113950449/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/118287490/Megacollect_2004_hyperspectral_collection_experiment_over_the_waters_of_the_Rochester_Embayment">Megacollect 2004: hyperspectral collection experiment over the waters of the Rochester Embayment</a></div><div class="wp-workCard_item"><span>Proceedings of SPIE</span><span>, Jun 1, 2005</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This work describes the water collection experiment component of the Megacollect 2004 campaign. M...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This work describes the water collection experiment component of the Megacollect 2004 campaign. Megacollect was a collaborative campaign coordinated by RIT with several institutions to spectrally measure various target/background scenarios with airborne sensors and ground instruments. An extension to the terrestrial campaign was an effort to simultaneously measure water optical properties in different bodies of water in the Rochester Embayment. This collection updates a previous effort in which water surface measurements were made during an AVIRIS mission over the Rochester Embayment (May 1999). Megacollect 2004 builds on this through an expanded campaign that increased the number of stations sampled, extended the spectral range of measurements, and improved the spatial resolution of the imagery through the use of multiple sensors (COMPASS, SEBASS, MISI, WASP). A larger set of in-water instruments were deployed on several vessels to sample and measure water optical properties near the shores of Lake Ontario, the northern portions of Irondequoit Bay, and several smaller ponds and bays in the Rochester Embayment. This paper describes the different in-water instruments deployed, the measurements obtained and how they will be used for future modeling efforts and development of hyperspectral algorithms.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="2a7132c58993fa141c5c8962cd5aad34" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":113950449,"asset_id":118287490,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/113950449/download_file?st=MTczNDE3MDA2Niw4LjIyMi4yMDguMTQ2&st=MTczNDE3MDA2Niw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287490"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287490"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287490; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287490]").text(description); $(".js-view-count[data-work-id=118287490]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287490; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287490']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287490, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "2a7132c58993fa141c5c8962cd5aad34" } } $('.js-work-strip[data-work-id=118287490]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287490,"title":"Megacollect 2004: hyperspectral collection experiment over the waters of the Rochester Embayment","translated_title":"","metadata":{"publisher":"SPIE","grobid_abstract":"This work describes the water collection experiment component of the Megacollect 2004 campaign. 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Megacollect was a collaborative campaign coordinated by RIT with several institutions to spectrally measure various target/background scenarios with airborne sensors and ground instruments. An extension to the terrestrial campaign was an effort to simultaneously measure water optical properties in different bodies of water in the Rochester Embayment. This collection updates a previous effort in which water surface measurements were made during an AVIRIS mission over the Rochester Embayment (May 1999). Megacollect 2004 builds on this through an expanded campaign that increased the number of stations sampled, extended the spectral range of measurements, and improved the spatial resolution of the imagery through the use of multiple sensors (COMPASS, SEBASS, MISI, WASP). A larger set of in-water instruments were deployed on several vessels to sample and measure water optical properties near the shores of Lake Ontario, the northern portions of Irondequoit Bay, and several smaller ponds and bays in the Rochester Embayment. This paper describes the different in-water instruments deployed, the measurements obtained and how they will be used for future modeling efforts and development of hyperspectral algorithms.","owner":{"id":292391191,"first_name":"Alan","middle_initials":null,"last_name":"Weidemann","page_name":"WeidemannAlan","domain_name":"independent","created_at":"2023-11-14T08:25:11.103-08:00","display_name":"Alan Weidemann","url":"https://independent.academia.edu/WeidemannAlan"},"attachments":[{"id":113950449,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/113950449/thumbnails/1.jpg","file_name":"427cedee73736bc6042af61e2ac7610e7807.pdf","download_url":"https://www.academia.edu/attachments/113950449/download_file?st=MTczNDE3MDA2Niw4LjIyMi4yMDguMTQ2&st=MTczNDE3MDA2Niw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Megacollect_2004_hyperspectral_collectio.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/113950449/427cedee73736bc6042af61e2ac7610e7807-libre.pdf?1714424539=\u0026response-content-disposition=attachment%3B+filename%3DMegacollect_2004_hyperspectral_collectio.pdf\u0026Expires=1734173666\u0026Signature=KmW7k59ISvG6xUL~bacs0o22nLMbqLFoYxfstsYA8PeUQPu~5znAOC~fY5TO5jYcR3XmVpGw4Pt-SyRgJwUEwwv01vw1ES4m2qxhsyzKO6wBE8xaB6ZDmMFxbXpbpXfphJPgxOXjSu7GXv4qjRImqLz2zVKMzvsVrYKOisOAHBDvzWJV40-S-6LYtVk04sRsJPJx5orqTVOxMg5UI7Hu5lX6-x8WLUpDQWyoZ63TnJkOzxzqWEwM~aAu9lJrxyL8Q4U4w36w6CzoQbgy-jkX8~Kb9F4hiC7edzRQru1gjt-8LKR-tl6-3nKIPHkl-nNzZQAJ5DI7wP9zfwwS8ck4Eg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":261,"name":"Geography","url":"https://www.academia.edu/Documents/in/Geography"},{"id":402,"name":"Environmental Science","url":"https://www.academia.edu/Documents/in/Environmental_Science"},{"id":428,"name":"Algorithms","url":"https://www.academia.edu/Documents/in/Algorithms"},{"id":6177,"name":"Modeling","url":"https://www.academia.edu/Documents/in/Modeling"},{"id":16691,"name":"Physical Oceanography","url":"https://www.academia.edu/Documents/in/Physical_Oceanography"},{"id":285356,"name":"Hyperspectral Imaging","url":"https://www.academia.edu/Documents/in/Hyperspectral_Imaging"},{"id":339262,"name":"Lessons Learned","url":"https://www.academia.edu/Documents/in/Lessons_Learned"},{"id":424115,"name":"Hyperspectral","url":"https://www.academia.edu/Documents/in/Hyperspectral"},{"id":594962,"name":"Compass","url":"https://www.academia.edu/Documents/in/Compass"},{"id":736727,"name":"DIRSIG","url":"https://www.academia.edu/Documents/in/DIRSIG"},{"id":800990,"name":"Reflectivity","url":"https://www.academia.edu/Documents/in/Reflectivity"},{"id":822358,"name":"Ground Truth","url":"https://www.academia.edu/Documents/in/Ground_Truth"},{"id":871402,"name":"High Altitude","url":"https://www.academia.edu/Documents/in/High_Altitude"},{"id":875506,"name":"Physical Model","url":"https://www.academia.edu/Documents/in/Physical_Model"},{"id":1469833,"name":"Misi","url":"https://www.academia.edu/Documents/in/Misi"},{"id":1660649,"name":"Bay","url":"https://www.academia.edu/Documents/in/Bay"},{"id":1837006,"name":"Atmospheric Effects","url":"https://www.academia.edu/Documents/in/Atmospheric_Effects"},{"id":1984483,"name":"Multispectral image","url":"https://www.academia.edu/Documents/in/Multispectral_image"},{"id":1990747,"name":"Parameter Selection","url":"https://www.academia.edu/Documents/in/Parameter_Selection"},{"id":4103932,"name":"Field Measurement","url":"https://www.academia.edu/Documents/in/Field_Measurement"}],"urls":[{"id":41506878,"url":"https://doi.org/10.1117/12.605856"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="118287489"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/118287489/Bidirectional_reflectance_function_in_coastal_waters_modeling_and_validation"><img alt="Research paper thumbnail of Bidirectional reflectance function in coastal waters: modeling and validation" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/118287489/Bidirectional_reflectance_function_in_coastal_waters_modeling_and_validation">Bidirectional reflectance function in coastal waters: modeling and validation</a></div><div class="wp-workCard_item"><span>Proceedings of SPIE</span><span>, Oct 6, 2011</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The current operational algorithm for the correction of bidirectional effects from the satellite ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The current operational algorithm for the correction of bidirectional effects from the satellite ocean color data is optimized for typical oceanic waters. However, versions of bidirectional reflectance correction algorithms, specifically tuned for typical coastal waters and other case 2 conditions, are particularly needed to improve the overall quality of those data. In order to analyze the bidirectional reflectance distribution function</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287489"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287489"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287489; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287489]").text(description); $(".js-view-count[data-work-id=118287489]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287489; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287489']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287489, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=118287489]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287489,"title":"Bidirectional reflectance function in coastal waters: modeling and validation","translated_title":"","metadata":{"abstract":"The current operational algorithm for the correction of bidirectional effects from the satellite ocean color data is optimized for typical oceanic waters. 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LISCO has both multispectral and hyperspectral radiometers for ocean color measurements. LISCO offers the potential for improving the calibration and validation activities of current and future Ocean Color satellite missions, as well as for satellite intercomparisons and spectral characterization</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287488"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287488"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287488; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287488]").text(description); $(".js-view-count[data-work-id=118287488]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287488; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287488']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287488, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=118287488]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287488,"title":"Hyperspectral and multispectral above-water radiometric measurements to monitor satellite data quality over coastal area","translated_title":"","metadata":{"abstract":"The Long Island Sound Coastal Observational platform (LISCO) near Northport, New York, has been recently established to support satellite data validation. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="118287487"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/118287487/_title_Tidal_influences_on_optical_variability_in_shallow_water_title_"><img alt="Research paper thumbnail of <title>Tidal influences on optical variability in shallow water</title>" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/118287487/_title_Tidal_influences_on_optical_variability_in_shallow_water_title_"><title>Tidal influences on optical variability in shallow water</title></a></div><div class="wp-workCard_item"><span>Proceedings of SPIE</span><span>, Feb 6, 1997</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287487"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287487"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287487; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="118287486"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/118287486/_title_Modeling_of_elastic_and_inelastic_scattering_effects_in_oceanic_optics_title_"><img alt="Research paper thumbnail of <title>Modeling of elastic and inelastic scattering effects in oceanic optics</title>" class="work-thumbnail" src="https://attachments.academia-assets.com/113950436/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/118287486/_title_Modeling_of_elastic_and_inelastic_scattering_effects_in_oceanic_optics_title_"><title>Modeling of elastic and inelastic scattering effects in oceanic optics</title></a></div><div class="wp-workCard_item"><span>Proceedings of SPIE</span><span>, Feb 6, 1997</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The results of model calculations of apparent optical properties for realistic marine waters with...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The results of model calculations of apparent optical properties for realistic marine waters with inclusion of Raman scattering and fluorescence are presented. 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Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing the burden, to the Department of Defense, Executive Services and Communications Directorate (0704-0188). Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="1ff8c5af84b991612fcf5d932a11ca7c" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":114203310,"asset_id":118287484,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/114203310/download_file?st=MTczNDE3MDA2Niw4LjIyMi4yMDguMTQ2&st=MTczNDE3MDA2Niw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="118287484"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="118287484"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 118287484; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=118287484]").text(description); $(".js-view-count[data-work-id=118287484]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 118287484; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='118287484']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 118287484, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "1ff8c5af84b991612fcf5d932a11ca7c" } } $('.js-work-strip[data-work-id=118287484]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":118287484,"title":"Diver visibility: Why one cannot see as far?","translated_title":"","metadata":{"publisher":"SPIE","grobid_abstract":"The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. 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