Title :
A Review of Some Important Technical Problems in Respect of Satellite Remote Sensing of Chlorophyll-a Concentration in Coastal Waters
Author :
Jun Chen ; Minwei Zhang ; Tingwei Cui ; Zhenhe Wen
Author_Institution :
Sch. of Ocean Sci., China Univ. of Geosci. (Beijing), Beijing, China
Abstract :
With the development of quantitative ocean color remote sensing, estimation of chlorophyll-a concentration in the coastal waters has aroused increasing attention from researchers. Currently, researches are confronted with difficulty in improving the accuracy of chlorophyll-a concentration estimation for turbid waters. Atmospheric correction, chlorophyll-a concentration modeling, and scale effect have already been identified as three critical factors affecting coastal water remote sensing. The in-depth exploration of them will accelerate the research progress of ocean color remote sensing. The ultimate objective of atmospheric correction and scale effect correction is to accurately estimate active constituents of turbid coastal waters in an optical way. Accordingly, the chlorophyll-a concentration modeling is a basic problem to be resolved, while atmospheric correction is the essential one. The scale effect problem arises during the modeling procedure where unrealistic homogeneous assumption is taken to measure chlorophyll-a concentration from the realistic non-homogeneous pixel. In the coastal remote sensing field, these three problems have become the most important topics in the current researches, and they will remain be the hot topics in the future.
Keywords :
ocean composition; oceanographic techniques; remote sensing; underwater optics; atmospheric correction; chlorophyll-a concentration; ocean color remote sensing; satellite remote sensing; scale effect correction; turbid coastal waters; Aerosols; Atmospheric modeling; Oceans; Remote sensing; Satellites; Scattering; Sea measurements; Atmospheric Correction; Chlorophyll-a Concentration; Coastal Waters; Remote Sensing; Scale Effect;
Journal_Title :
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
DOI :
10.1109/JSTARS.2013.2242845