In this paper, we designed the laser scanning galvanometer system according to our requirements. Based on scanning range of our laser scanning galvanometer system, the design parameters of this system were optimized. During this work, we focused on the design of the f-θ field lens. An optical system of patent lens in the optical manual book, which had three glasses structure, was used in our designs. Combining the aberration theory, the aberration corrections and image quality evaluations were finished using Code V optical design software. An optimum f-θ field lens was designed, which had focal length of 434 mm, pupil diameter of 30 mm, scanning range of 160 mm × 160 mm, and half field angle of 18°×18°. At the last, we studied the influences of temperature changes on our system.
Secchi depth, an important optical characteristic of water, is a useful index of water quality and is widely used in many
environmental studies. The Yellow Sea and the East China Sea are typical case 2 waters, where concentrations of
suspended matter, phytoplankton pigments, and colored dissolved organic matter are higher than those in other open
oceans. Two cruises were conducted to investigate the water optical characteristics in the Yellow Sea and the East China
Sea in May and June, 2009. 62 water sampling stations of Secchi disk depth were measured in situ in day time, and their
values were in the range of 0.0112 to 15.6 m with the mean of 6.72 m and a standard deviation of 3.18 m. In this paper,
we adapted a quasi-analytical algorithm to estimate the Secchi depth from satellite ocean data in both coastal and oceanic
waters. The development of the algorithm is based on the use of in situ measurements and 8-day MODIS-Aqua remote
sensing reflectance data with 4 km spatial resolution. More than 39 matchups were compiled for the MODIS sensor by
spatial-temporal matching. The comparison between water transparency retrievals from remote sensing data and in situ
measurements yields showed that the determination coefficient was 0.60 and a root mean square error of 8.4 m. This
study suggests that the quasi-analytical algorithm provide a promising result on in situ data. In the future, maps of ocean
transparency for this area will be derived using this algorithm.
Secchi disk depth (SDD) is an important optical property of water related to water quality and primary production. The
traditional sampling method is not only time-consuming and labor-intensive but also limited in terms of temporal and
spatial coverage, while remote sensing technology can deal with these limitations. In this study, models estimating SDD
have been proposed based on the regression analysis between the HJ-1 satellite CCD image and synchronous in situ
water quality measurements. The results illustrate the band ratio model of B3/B1 of CCD could be used to estimate
Secchi depth in this region, with the mean relative error (MRE) of 8.6% and root mean square error (RMSE) of 0.1 m,
respectively. This model has been applied to one image of HJ-1 satellite CCD, generating water transparency on June 23,
2009, which will be of immense value for environmental monitoring. In addition, SDD was deeper in offshore waters
than in inshore waters. River runoffs, hydrodynamic environments, and marine aquaculture are the main factors
influencing SDD in this area.