Development of Suspended Particulate Matter Algorithms for Ocean Color Remote Sensing KCI OTHER

Title
Development of Suspended Particulate Matter Algorithms for Ocean Color Remote Sensing
Author(s)
안유환; 문정언; S. Gallegos
KIOST Author(s)
Moon, Jeong Eon(문정언)
Publication Year
2001-01
Abstract
We developed a CASE-II water model that will enable the simulation of remote sensing reflectance( Rrs ) at the coastal waters for the retrieval of suspended sediments (SS) concentrations from satellite imagery. The model has six components which are: water, chlorophyll, dissolved organic matter (DOM), non-chlorophyllous particles (NC), heterotrophic microorganisms and an unknown component, possibly represented by bubbles or other particulates unrelated to the five first components. We measured Rrs , concentration of SS and chlorophyll, and absorption of DOM during our field campaigns in Korea. In addition, we generated Rrs from different concentrations of SS and chlorophyll, and various absorptions of DOM by random number functions to create a large database to test the model. We assimilated both the computer generated parameters as well as the in-situ measurements in order to reconstruct the reflectance spectra. We validated the model by comparing model-reconstructed spectra with observed spectra. The estimated Rrs spectra were used to (1) evaluate the performance of four wavelengths and wavelengths ratios for accurate retrieval of SS. 2) identify the optimum band for SS retrieval, and 3) assess the influence of the SS on the chlorophyll algorithm. The results indicate that single bands at longer wavelengths in visible better results than commonly used channel ratios. The wavelength of 625nm is suggested as a new and optimal wavelength for SS retrieval. Because this wavelength is not available from SeaWiFS, 555nm is offered as an alternative. The presence of SS in coastal areas can lead to overestimation chlorophyll concentrations greater than 20-500%.
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/5921
Bibliographic Citation
Korean Journal of Remote Sensing, v.17, no.4, pp.285 - 295, 2001
Keywords
CASE-II Water; Remote Sensing Reflectance Model; SS Algorithms
Type
Article
Language
English
Related Researcher
Research Interests

Ocean color,Ocean optical observation,Remote sensing,해색원격탐사,해양광학관측,원격탐사

Files in This Item:
There are no files associated with this item.

qrcode

Items in ScienceWatch@KIOST are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse