The factors sensitive to suspended sediment concentration (SSC) with both strong correlation and evident physical
meaning are found step by step with the data collected from Sheyang River estuary. These factors combined by
reflectance of 605 nm, 715 nm and 810 nm which near the reflectance peaks of turbid water have strong correlations
with SSC. The results of the model established by the factor R605xR715/( R605-R810) were consistent well with real
distribution laws of SSC and its relative accuracy arrived over 65%. It shows the advantage of hyperspectral sensors on
monitoring SSC in offshore area.
Quantitative analysis of the temporal and spatial distribution characteristics of coastal nutrient substances enables to
adequately estimate the state of coastal marine environment and describe environmental change processes conditioned by
anthropogenic forces. Remote sensing has the potential to provide synoptic information and has been somewhat
successful in monitoring nutrient properties at rivers and estuaries. So taking total inorganic nitrogen (TIN) as typical
nutrient monitoring index, Sheyang River estuary located in middle part of Jiangsu coastline, China was chosen for water
quality simulation and variation trend analysis. Six correlation coefficient matrixes were calculated by using
synchronous TIN concentration and its corresponding normalized water surface reflectance data from 15 field samples.
Results showed that band combination of 804 and 630nm with the form of pseudo-sediment parameter could get the best
correlation capacity and minimized reversion error. Based on this selected parameter, an inverse model was built for TIN
quantitative reversion. R2 coefficients reached 0.97 and 0.9972 in calibration and validation period respectively. And
then the spatial distribution pattern of TIN in Sheyanghe River estuary was obtained using the inverse model via
Hyperion hyperspectral remote sensing image. A coupled wave-tide-surge model and material transport and diffusion
model were adopted for TIN concentration cross validation of the reversion precision exactly at river outlet. Comparison
results indicated that these two dataset made a good consistency for TIN diffusive characters in Sheyang River estuary
with the R2 reached 0.6549. The magnitude of TIN concentration was also agreed fairly well.
Accurate atmospheric correction is an important and essential process in ocean color remote sensing because the
influence of atmosphere account for the main part of signals received by sensors. Traditional methods usually depend on
in-situ measured parameters of atmosphere and could not be applied in operational system. In this paper, MODIS
products synchronize with Beijing-1 micro-satellite image were used to extract the parameters of atmosphere. we chose
a marine space of clean water far away from the coast in MODIS image and used the products include MOD02, MOD03
and MOD07 to calculate the aerosol radiance of near-infrared bands of MODIS which were used to extrapolate the
aerosol radiances of each band of Beijing-1 micro-satellite. Brought the results into radioactive transfer equation and
fulfilled atmosphere correction. We found this method can enhanced the detail information of water body, especially to
case 2 water. We compared the correction results with original image and the results from 6S model; its effect was
consistent well with real conditions and better than 6S model. All these indicated that this method is feasible to
atmospheric correction of turbid coastal waters and expands the application of multi-spectral sensors in ocean color
remote sensing.
With the advantage of image-spectrum integration and quantitative analysis, space-borne hyperspectral remote sensing
technique was increasingly applied in ground object identification and information extraction at coastal region to solve
the difficulty for field observation and sampling. In order to deeply excavate the embedded spectral information for
different features in coastal area, the preprocessing process of hyperspectral image was essential and necessary. So taking
Hyperion hyperspectral image as example dataset, the objective of this article is to study and build a doable flowchart for
Hyperion image preprocessing to get the reflectance image of coastal region for further study and use. The processes
include: (1) bad lines fixing; (2) vertical stripes removing; (3) atmospheric correction; (4) geometric correction and (5)
tidal flat area separation from vegetation and water body. Related algorithms and parameters were also discussed in
detail.
Mapping surface sediment types is particularly challenging in muddy intertidal flat area due to muddy characteristics and
tidal fluctuation. With the combination of Hyperion hyperspectral image and field survey data, two regression based
image interpretation methods, namely characteristic band method (CBM) and band differential method (BDM), were
used for sediment type classification and mapping. It was found that under low tidal level there was a strong correlation
between surface sediment reflectance and its sand, silt and clay contents in shortwave infrared band. For 2102nm
wavelength, the correlation coefficient by former method reached -0.8954, 0.9070 and 0.6547 respectively while the
latter method had a relatively lower correlation capability. So choosing this band as the characteristic band, three linear
regression models were constructed and the sand, silt and clay contents were quantitatively inversed from their
corresponding reflectance values. A linear equilibrium corrective method was then applied to some "bad" pixels for
inversed contents amendment due to regression model's linear transforming limitation. Based on these corrected
component contents, Shepard triangular classification method was adopted and the sediment types for the whole
intertidal flat were automatically obtained with a high interpretation precision of 87.9%. Results showed that the
hyperspectral remote sensing reversion method could be well utilized for dynamic monitoring and analyzing of the
depositional environment changes in muddy intertidal flat region.
Red tides have been increasingly observed in the gulf of Haizhou and considered a serious environmental problem from
the beginning of the new century. Eutrophication of water is an important reason of red tide occurrence. This paper used
the observation data of the concentration of dissolved inorganic nitrogen (DIN) and dissolved inorganic phosphorus
(DIP) in Haizhou Gulf from 2004 to 2006 and selected synchronous MODIS Terra 1B data with 500m spatial resolution
in this period of time. We established factors with single band and multi-bands, and then calculated the correlation of
each factor with DIN concentration, DIP concentration, and their logarithm respectively. The factors with stronger
correlation were used to establish regression models of DIN and DIP's concentration. After comparing these models, we
chose the linear model of DIN concentration established by factor ) 4, 3 ( 11 F and inverse model of the logarithm of DIP
concentration established by factor ) 5, 6 ( 7 F as their final regression model. The relative accuracy of DIN concentration
model achieved about 70%; the retrieving results of DIN concentration were consistent well with real conditions. The
relative accuracy of the logarithm of DIP concentration achieved about 90%. The results prove the feasibility of
monitoring DIN concentration and the exponential order of DIP concentration in offshore of Jiangsu Province.
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