is Íslenska en English

Lokaverkefni (Meistara)

Háskóli Íslands > Þverfræðilegt nám > Umhverfis- og auðlindafræði >

Vinsamlegast notið þetta auðkenni þegar þið vitnið til verksins eða tengið í það: http://hdl.handle.net/1946/40394

Titill: 
  • Titill er á ensku Tracks In the snow: New automated image processing method for In-situ vertical profiling
  • Spor í snjónum: Ný sjálfvirk myndgreiningartækni fyrir mat á sjávarsnjó í heimshöfunum
Námsstig: 
  • Meistara
Útdráttur: 
  • Útdráttur er á ensku

    Due to their fragile nature, in-situ measurements of dissolved particles have been scarce. Recently, the study of dissolved particle distribution has become increasingly dependent on computer image recognition technologies. Numerous camera systems exist, some with environmental sensors, which are part of larger structures of underwater research equipment. I will present such a system, a modified SUNADAYODACAM, which has been system tested at depths ranging from 0-200 m in the Kuroshio/Oyashio ocean fronts and the Tokaira straits. Data gathering and testing were performed on the research vessel Shinsei Maru cruise in March 2021 and the research vessel Kagoshima Maru cruise in June 2021. The research areas have an elevated level of productivity due to oceanic mixing. The first study area is greatly affected by oceanic fronts that contribute to turbulent ocean mixing and availability of nutrients, while the second study area, the Tokaira straits, is highly affected by mixing due to topographic features. I developed a new MATLAB MarPar code that has numerous algorithms to process large-scale video data and uses advanced features of MATLAB blob detection, object detection and tracking features, noise removal and filters out of focus objects. Kalman filters are utilised for increased prediction accuracy of moving objects. The code was designed to fit video data from our tailor-made SUNADAYODACAM performing size and to count measurements of dissolved organic matter in a vertical depth profile of up to 200 m. Among other findings, the research outcomes suggest that turbulence enhances aggregate formation up to a critical turbulent kinetic energy dissipation rate. The main contributing factor of the amount of marine aggregate in the surface layer of the mode water is downwelling as a reducing factor and upwelling for marine snow bloom. The oceanic fronts have the greatest contrast in numbers of dissolved particles, due to these upwelling and downwelling processes.

Styrktaraðili: 
  • Styrktaraðili er á ensku WATANABE FUNDING provided much needed financial support
Samþykkt: 
  • 27.1.2022
URI: 
  • http://hdl.handle.net/1946/40394


Skrár
Skráarnafn Stærð AðgangurLýsingSkráartegund 
Ingibjörg-Sniðmát lokaritgerða - Meistaranám final.pdf8.35 MBOpinnHeildartextiPDFSkoða/Opna
Master_skil.pdf573.85 kBLokaðurYfirlýsingPDF