Multi-parametric observation of biological contribution to surface structure of the water in archipelagos

Ichio Asanuma; Daisuke Hasegawa; Yessy Arvelyna

doi:10.1117/12.732895

5 October 2007 Multi-parametric observation of biological contribution to surface structure of the water in archipelagos

Ichio Asanuma, Daisuke Hasegawa, Yessy Arvelyna

Author Affiliations +

Proceedings Volume 6680, Coastal Ocean Remote Sensing; 66800V (2007) https://doi.org/10.1117/12.732895
Event: Optical Engineering + Applications, 2007, San Diego, California, United States

Abstract

The multi-parametric data observed by the Synthetic Aperture Radar (SAR) and the Moderate Image Scanning Radiometer (MODIS) were applied to analyze the water distribution in the Philippine Archipelago to build a new radar imaging model. The SAR provides information on the surface structure of the water affected by various phenomena such as currents, internal waves, swells, surface winds, rain falls, natural films, and so on. One difficult parameter among them is the natural film, which exhibits a damping effect to the surface roughness from breaking waves to capillary ones. The chlorophyll-a concentration observed by satellite sensors such as MODIS provide estimates of the standing stock of phytoplankton, which is considered as the parameter estimating the standing stock of zooplankton. The standing stocks of phytoplankton and zooplankton could be a proportional parameter to the amount of the natural film. In this study, a frequency dependent multi-parametric equation was proposed to rebuild the surface roughness with various parameters in the spectrum domain. Possible validation study was conducted with the relationship between the sum of power spectrum for certain frequency range with chlorophyll-a concentration on the Mindanao Sea and the Surigao Strait.

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Ichio Asanuma, Daisuke Hasegawa, and Yessy Arvelyna "Multi-parametric observation of biological contribution to surface structure of the water in archipelagos", Proc. SPIE 6680, Coastal Ocean Remote Sensing, 66800V (5 October 2007); https://doi.org/10.1117/12.732895

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