Data

WAMSI 2 - Kimberley Node - 1.4 - Remote sensing in support of marine environmental monitoring

Australian Ocean Data Network
Fearns, Peter, Dr (Principal investigator) Broomhall, Mark (collaborator) Edwards, Luke (Point of contact) Hardman-Mountford, Nick, Dr (Associated with)
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=https://catalogue.aodn.org.au:443/geonetwork/srv/api/records/e573dfd6-db4c-4e49-8a86-591a9124215d&rft.title=WAMSI 2 - Kimberley Node - 1.4 - Remote sensing in support of marine environmental monitoring&rft.identifier=e573dfd6-db4c-4e49-8a86-591a9124215d&rft.publisher=Australian Ocean Data Network&rft.description=The goal of this project is to quantify the reliability of remotely sensed turbidity products for use in the Kimberley region. There are two specific objectives. 1: Analyze uncertainties of remotely sensed turbidity products by comparison of different algorithms and different resolution products with each other and with archived in situ data 2: Analyze time series of remotely sensed turbidity data to provide first-stage pilot products that may be applicable for future use as marine management tools. The deliverables are: * Analysis of ensemble variability between different algorithms; * Assessment of sub-km scale variability from comparison with high-resolution products; * Quantification of uncertainty from comparison with archived in situ data; * Maps of turbidity hotspot regions (i.e. regions of frequently occurring high turbidity events and regions of extreme variability).; * Alternative: Maps of different turbidity regimes (e.g. permanently high turbidity, frequent turbid events, infrequent turbid events, persistently clear water).; * Turbidity indicator products (e.g. days above a set turbidity threshold)Statement: Potential for Remote Sensing to service management data needs has been divided into metrics based in the physical priniciples of remote sensing science. Atmosphere Atmospheric remote sensing works by detecting visible light scattered by air molecules and aerosols (dust, water droplets in clouds, and other small particles), or by infrared (thermal) radiation emitted from different layers of the atmosphere. The metrics able to be monitored by remote sensing methods are: Cyclones, storms, annual rainfall, and air temperature. Land The metrics potentially able to be supported by land-based remote sensing are species composition, spatial extent, canopy cover (density), canopy height, nesting abundance, sand temperature, and beach condition. Ocean The metrics potentially able to be supported by ocean remote sensing include sea surface temperature (SST), turbidity, nutrient input, sea level rise, light availability, ocean colour and sedimentation. Substrate The metrics potentially able to be supported by remote sensing technologies include Benthic cover, Spp. Composition, diversity, spatial extent, and percent cover. Acoustics Although this review does not focus on acoustics, it is worth noting the potential, and as mentioned in the terrestrial mapping discussion earlier, improvements in habitat and ecosystem mapping could potentially be gained by fusion of different data streams, such as visible (satellite or airborne) and acoustic data. Most active acoustic remote sensing is in the form of echo-sounder surveys to produce charts.&rft.creator=Fearns, Peter, Dr&rft.date=2018&rft.coverage=westlimit=120.8193359375; southlimit=-18.626302082025774; eastlimit=128.4658203125; northlimit=-12.70555387754581&rft.coverage=westlimit=120.8193359375; southlimit=-18.626302082025774; eastlimit=128.4658203125; northlimit=-12.70555387754581&rft_rights=*All users must acknowledge the source of the material with the acknowledgment*: Data sourced from Western Australian Marine Science Institution (WAMSI) project funded by Western Australian State Government and research partners and carried out by <insert authors> from <insert organisations>&rft_rights=*Suggested attribution for use in citation*: [author(s)], Western Australian Marine Science Institution (WAMSI), [author organisation(s)], [year-of-data-download], [title], [data-access-URL], data accessed (YYYY-MM-DD).&rft_rights=*Disclaimer*: WAMSI and its Partners data, products and services are provided as is and WAMSI and its Partners do not warrant their fitness for a particular purpose. WAMSI and its Partners have made every reasonable effort to ensure high quality of the data, products and services, to the extent permitted by law the data, products and services are provided without any warranties of any kind, either expressed or implied, including without limitation any implied warranties of title, merchantability, and fitness for a particular purpose or non-infringement. WAMSI and its Partners make no representation or warranty that the data, products and services are accurate, complete, reliable or current. To the extent permitted by law, WAMSI and its Partners exclude all liability to any person arising directly or indirectly from the use of the data, products and services.&rft_rights= http://creativecommons.org/licenses/by-nc/3.0/au/&rft_rights=http://i.creativecommons.org/l/by-nc/3.0/au/88x31.png&rft_rights=WWW:LINK-1.0-http--related&rft_rights=License Graphic&rft_rights=Creative Commons Attribution-NonCommercial 3.0 Australia License&rft_rights=http://creativecommons.org/international/au/&rft_rights=WWW:LINK-1.0-http--related&rft_rights=WWW:LINK-1.0-http--related&rft_rights=License Text&rft_rights=Creative Commons Attribution-NonCommercial 3.0 Australia License http://creativecommons.org/licenses/by-nc/3.0/au&rft_subject=biota&rft_subject=environment&rft_subject=oceans&rft_subject=VISIBLE IMAGERY&rft_subject=EARTH SCIENCE&rft_subject=SPECTRAL/ENGINEERING&rft_subject=VISIBLE WAVELENGTHS&rft_subject=MODIS image&rft.type=dataset&rft.language=English Access the data
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WAMSI and its Partners data, products and services are provided "as is" and WAMSI and its Partners do not warrant their fitness for a particular purpose. WAMSI and its Partners have made every reasonable effort to ensure high quality of the data, products and services, to the extent permitted by law the data, products and services are provided without any warranties of any kind, either expressed or implied, including without limitation any implied warranties of title, merchantability, and fitness for a particular purpose or non-infringement. WAMSI and its Partners make no representation or warranty that the data, products and services are accurate, complete, reliable or current. To the extent permitted by law, WAMSI and its Partners exclude all liability to any person arising directly or indirectly from the use of the data, products and services.

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Brief description

The goal of this project is to quantify the reliability of remotely sensed turbidity products for use in the Kimberley region. There are two specific objectives. 1: Analyze uncertainties of remotely sensed turbidity products by comparison of different algorithms and different resolution products with each other and with archived in situ data 2: Analyze time series of remotely sensed turbidity data to provide first-stage pilot products that may be applicable for future use as marine management tools. The deliverables are: * Analysis of ensemble variability between different algorithms; * Assessment of sub-km scale variability from comparison with high-resolution products; * Quantification of uncertainty from comparison with archived in situ data; * Maps of turbidity "hotspot" regions (i.e. regions of frequently occurring high turbidity events and regions of extreme variability).; * Alternative: Maps of different turbidity regimes (e.g. permanently high turbidity, frequent turbid events, infrequent turbid events, persistently clear water).; * Turbidity indicator products (e.g. days above a set turbidity threshold)

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Statement: Potential for Remote Sensing to service management data needs has been divided into metrics based in the physical priniciples of remote sensing science. Atmosphere Atmospheric remote sensing works by detecting visible light scattered by air molecules and aerosols (dust, water droplets in clouds, and other small particles), or by infrared (thermal) radiation emitted from different layers of the atmosphere. The metrics able to be monitored by remote sensing methods are: Cyclones, storms, annual rainfall, and air temperature. Land The metrics potentially able to be supported by land-based remote sensing are species composition, spatial extent, canopy cover (density), canopy height, nesting abundance, sand temperature, and beach condition. Ocean The metrics potentially able to be supported by ocean remote sensing include sea surface temperature (SST), turbidity, nutrient input, sea level rise, light availability, ocean colour and sedimentation. Substrate The metrics potentially able to be supported by remote sensing technologies include Benthic cover, Spp. Composition, diversity, spatial extent, and percent cover. Acoustics Although this review does not focus on acoustics, it is worth noting the potential, and as mentioned in the terrestrial mapping discussion earlier, improvements in habitat and ecosystem mapping could potentially be gained by fusion of different data streams, such as visible (satellite or airborne) and acoustic data. Most active acoustic remote sensing is in the form of echo-sounder surveys to produce charts.

Modified: 05 03 2015

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128.46582,-12.70555 128.46582,-18.6263 120.81934,-18.6263 120.81934,-12.70555 128.46582,-12.70555

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text: westlimit=120.8193359375; southlimit=-18.626302082025774; eastlimit=128.4658203125; northlimit=-12.70555387754581

Subjects
EARTH SCIENCE | MODIS image | SPECTRAL/ENGINEERING | Visible Imagery | VISIBLE WAVELENGTHS | biota | environment | oceans |

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