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Extraction of coastal ocean wave characteristics using remote sensing and computer vision technologies

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dc.contributor.author Johnson, M
dc.contributor.author Lück-Vogel, Melanie
dc.date.accessioned 2017-06-07T07:08:25Z
dc.date.available 2017-06-07T07:08:25Z
dc.date.issued 2017-05
dc.identifier.citation Johnson, M. and Lück-Vogel, M. 2017. Extraction of coastal ocean wave characteristics using remote sensing and computer vision technologies. International Symposium of Remote Sensing of the Environment, CSIR ICC, Pretoria, 8-12 May 2017 en_US
dc.identifier.uri http://isrse37.org/wp-content/uploads/2017/05/ISRSE-37-Abstract-Book-as-at-8-May-2017.pdf
dc.identifier.uri http://hdl.handle.net/10204/9162
dc.description International Symposium of Remote Sensing of the Environment, CSIR ICC, Pretoria, 8-12 May 2017 en_US
dc.description.abstract The coastal zone occurs at the interface of three major natural systems. These systems include the atmosphere, the ocean and the land surface. Ocean waves are among the most important forces shaping the world¿s coastlines. They drive environmental processes and human activity that occur within the coastal zone as well as on the open ocean. The assessment of wave characteristics, such as wave direction, wavelength, wave period and wave velocity, is critical to understanding coastal processes as baseline for better coastal management. However, monitoring and assessment of wave characteristics is challenging, given the high complexity of the ocean dynamics and large spatial extent. Traditionally, wave observation instruments such as wave buoys, wave poles, pressure transducers, inverted echo-sounders and current meters have been used to record ocean wave characteristics. Although delivering very accurate measurements, they only record punctual data. The work presented here is assessing whether optical imagery from the RapidEye satellite can be used to extract ocean wave characteristics such as wave direction, wavelength, wave period and wave velocity. If successful, the advantage of the proposed remote sensing-based approach would be the spatially continuous provision of wave characteristics for large areas, including the near-shore in a very cost-effective way.. As ground truth data for validating open ocean wave conditions are sparse, a lab test with simulated, controlled wave conditions was conducted to assess various approaches for the extraction of wave characteristics from remote sensing imagery. The techniques identified and developed under lab conditions are to be tested using RapidEye imagery on two study areas on the South African coast. Results are expected to significantly contribute to a more comprehensive understanding and monitoring of waves dynamics for better coastal planning. en_US
dc.language.iso en en_US
dc.relation.ispartofseries Worklist;19058
dc.subject Remote sensing en_US
dc.subject RapidEye en_US
dc.subject Wave detection en_US
dc.title Extraction of coastal ocean wave characteristics using remote sensing and computer vision technologies en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Johnson, M., & Lück-Vogel, M. (2017). Extraction of coastal ocean wave characteristics using remote sensing and computer vision technologies. http://hdl.handle.net/10204/9162 en_ZA
dc.identifier.chicagocitation Johnson, M, and Melanie Lück-Vogel. "Extraction of coastal ocean wave characteristics using remote sensing and computer vision technologies." (2017): http://hdl.handle.net/10204/9162 en_ZA
dc.identifier.vancouvercitation Johnson M, Lück-Vogel M, Extraction of coastal ocean wave characteristics using remote sensing and computer vision technologies; 2017. http://hdl.handle.net/10204/9162 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Johnson, M AU - Lück-Vogel, Melanie AB - The coastal zone occurs at the interface of three major natural systems. These systems include the atmosphere, the ocean and the land surface. Ocean waves are among the most important forces shaping the world¿s coastlines. They drive environmental processes and human activity that occur within the coastal zone as well as on the open ocean. The assessment of wave characteristics, such as wave direction, wavelength, wave period and wave velocity, is critical to understanding coastal processes as baseline for better coastal management. However, monitoring and assessment of wave characteristics is challenging, given the high complexity of the ocean dynamics and large spatial extent. Traditionally, wave observation instruments such as wave buoys, wave poles, pressure transducers, inverted echo-sounders and current meters have been used to record ocean wave characteristics. Although delivering very accurate measurements, they only record punctual data. The work presented here is assessing whether optical imagery from the RapidEye satellite can be used to extract ocean wave characteristics such as wave direction, wavelength, wave period and wave velocity. If successful, the advantage of the proposed remote sensing-based approach would be the spatially continuous provision of wave characteristics for large areas, including the near-shore in a very cost-effective way.. As ground truth data for validating open ocean wave conditions are sparse, a lab test with simulated, controlled wave conditions was conducted to assess various approaches for the extraction of wave characteristics from remote sensing imagery. The techniques identified and developed under lab conditions are to be tested using RapidEye imagery on two study areas on the South African coast. Results are expected to significantly contribute to a more comprehensive understanding and monitoring of waves dynamics for better coastal planning. DA - 2017-05 DB - ResearchSpace DP - CSIR KW - Remote sensing KW - RapidEye KW - Wave detection LK - https://researchspace.csir.co.za PY - 2017 T1 - Extraction of coastal ocean wave characteristics using remote sensing and computer vision technologies TI - Extraction of coastal ocean wave characteristics using remote sensing and computer vision technologies UR - http://hdl.handle.net/10204/9162 ER - en_ZA


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