It is challenging that accurate assessment of chlorophyll-a concentration by remote sensing in coastal waters. Chla
concentration is commonly retrieved by blue-green ratio in open ocean waters. And this method is efficient in open
ocean waters. But this method is confined when applied to coastal or inland waters, because of abundant variable CDOM
and tripton. It is very difficult to retrieve chla of coastal or estuary waters because of overlap of absorption and
backscattering caused by CDOM and tripton. Dall’Olmo et al put forward a semi-analytical retrieval model of chla,
three-band model. The conceptual three-band model has been successfully applied to estimate chla in turbid and
eutrophic waters by tuning the band position in accordance with the spectral properties.The aim of this paper is to testify
the three-band model that could resolve this problem. The three-band model was tuned in accord with optical properties
and the bands were optimized for accurate estimation. Finally, we found a good linear relationship between chlorophyll-a
and three-band model, with the determination coefficient of 0.63 and the RMSE of 2.22μg·L-1. Furthermore, the in situ
spectral data was averaged to the band range of MERIS (band7, band9 and band10) and developed a simulated threeband
model. A good linear relationship could be found between [(B7-1-B9-1)×B10] and chlorophyll-a, with the
determination coefficient of 0.59 and the RMSE of 0.72μg·L-1. The findings demonstrated that the three-band model of
MERIS could be applied to retrieve chlorophyll-a concentration of Yantai coastal waters.
In this paper, the method of monitoring coastal areas affected by thermal discharge of nuclear plant by using remote
sensing techniques was introduced. The proposed approach was demonstrated in Daya Bay nuclear plant based on HJ-B
IRS data. A single channel water temperature inversion algorithm was detailed, considering the satellite zenith angle and
water vapor. Moreover the reference background temperature was obtained using the average environmental temperature
method. In the case study of Daya Bay nuclear plant, the spatial distribution of thermal pollution was analyzed by taking
into account the influence of tidal, wind and so on. According to the findings of this study, the speed and direction of the
ebb tide, is not conducive to the diffusion of thermal discharge of DNNP. The vertically thermal diffusion was limited by
the shallow water depth near the outlet.
A conceptual model containing reflectance in three spectral bands in the red and near infrared ranges of the spectrum can
be used to retrieve vegetation pigment concentration. Based on this model, the bio-optical properties of Chlorophyll-a
(Chl-a), suspended solids, dissolved organic matter and water molecules were analyzed in this paper, by using in-situ
spectra data, optical parameters and water quality parameters in Taihu Lake. Under the band range determined by
spectral feature analysis, the optimal combination of bands (678 nm, 696 nm and 748 nm) was selected through the
iterative method, to compose an optimized band combination in order to build the Chl-a semi-analytical model. Based on
hyper-spectral imager (HSI) data carried on the Environmental 1 (HJ-1) satellite, this model was used successfully to
retrieve the Chl-a concentration in Taihu Lake.
To accurately assess the area of land cover in hill land, we integrated DEM data and remote sensing image in Lihe River
Valley, China. Firstly, the DEM data was combined into decision tree to increase the accuracy of land cover
classification. Secondly, a slope corrected model was built to transfer the projected area to surface area by DEM data. At
last, the area of different land cover was calculated and the dynamic of land cover in Lihe River Valley were analyzed
from 1998 to 2003. The results show that: the area of forestland increased more than 10% by the slope corrected model,
that indicates the area correcting is very important for hill land; the accuracy of classification especially for forestland
and garden plot is enhanced by integrating of DEM data. It can be greater than 85%. The indexes of land use extent were
266.2 in 1998, 273.1 in 2001, and 276.7 in 2003. The change rates of land use extent were 2.59 during 1998 to 2001 and
1.34 during 2001 to 2003.
According to the advanced feature of hyperspectral image and Correlation Simulating Analysis Model (CSAM), a new simple but efficient kernel-adaptive filter (SRSSHF) especially for hyperspectral image is suggested in this paper. It is achieved not based on the traditional sigma (standard deviation) statistics in spatial dimension, but on the valid-pixel judge in spectral dimension and the intellectualized shift convolution in spatial dimensions. So its criteria is based on the intrinsic property of objects by adequately utilizing the spectral information that hyperspectral affords. Such a filter also is an adaptive filter, and its kernel size theoretically has no strong influence on the filter results. What it concentrates is the feature of signal itself but not the speckle noise, its criterion is in spectral dimension, and multiple iteration is available. So the tradeoff of spatial texture is not necessary. It is applied to filter and improve quality of PHI hyperspectral images acquired both in Changzhou, China and Nagano, Japan, and a >200 looks iteration and a comparison with other typical adaptive filters also are tried. It shows that SRSSHF can smooth whole the internal of a homogeneous area while ideally keep and, as well as, enhance the edges well. As good results are achieved, this paper suggests that SRSSHF on the base of CSAM is a relative ideal filter for HRS images. Some other features of SRSSHF are also discussed in this paper.
Position and Orientation System/Direct Georeferencing (POS/DG) data is important to hyperspectral images, for it has much information of flight attitude, such as absolute position (x,y,z) and rotation parameters. The largest advantage of this method, using POS/DG data to correct remote sensing images, is to save much manual work and money. This method doesn't need any ground work. It can get high quality images just through a correction program. It is more economical, simpler and faster than conventional methods. This article concentrates on the research of how to use POS/DG data to correct the hyperspectral images (in this article is PHI images) and discuss the efficiencies of a few kinds of resampling methods.
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