Beijing-1 small satellite has three bands of green, red and
near-infrared, with spatial resolution of 32 meters. Three days
Beijing-1 data are used to retrieve distribution and living status of Enteromorpha clathrata (a kind of green algae and
called Hutai in Chinese). First, use the non-supervised classification to separate the kinds who has big spectral
differences. Second, the cloud and cloud-covered green algae can be separated by the ratio of near-infrared and red. In
the end, the green algae distribution is obtained. The NDVI is used for indicator of living status and density.
MODIS has the advantage of high temporal although its spatial resolution is much coarse than Beijing-1. A decision tree
is developed to retrieve green algae. First, the cloud is eliminated by its high reflectance. Second, the NDVI is calculated
and a threshold value is set to determine whether the grid is green algae.
The green algae distribution results from Beijing-1 and MODIS are compared. Generally, the Beijing-1 extracted green
algae is coincide with the MODIS extracted green algae. The Beijing-1 extracted algae area is smaller than that of
MODIS, because the MODIS has spatial resolution of 250-meter, its situation of mix pixel is severer.
Sea fog is considered as a cloud cling the surface and reducing visibility to 1km or less in this paper. For fog or cloud,
simulating results show that the reflected radiance in the visible spectral region depends mainly on the fog/cloud optical
thickness and the reflected radiance in near-infrared spectral region depends mainly on the fog/cloud particle effective
radius. Owing to this, by combining the visible and the near-infrared reflected solar radiation and using the lookup table
about the reflectance function for various values of optical thickness and effective particle radius created by the Streamer
radiative transfer model, a retrieval algorithm was developed to determine the optical thickness and the effective particle
radius of sea fog simultaneously from NOAA17 AVHRR3 data. According to the definition of visibility and liquid water
content, the relations and formulas of fog properties (optical thickness, particle effective radius, liquid water content and
visibility) are described. Lastly, the other two properties, liquid water content and visibility on known sea fog regions are
also estimated. It is those four sea fog properties retrieved from satellite observations that can offer the condition for
analyzing and forecasting the time of fog clearance in future.
Multi-temporal series of satellite SPOT-VEGETATION Normalized Difference Vegetation Index (NDVI) has long
time-series from 1998 to present. The convenient downloading policy make those data can be widely used all through the
world. The data is used for global vegetation monitoring and variation analysis. The spring onset date reflects the
vegetation growth and its feedback to climate and human activity, and become an important variable for the global
climatic change and production monitoring. In this paper, the spatial spring onset date information in south and central
China is portrayed, and the spring onset frequency distribution map is sketched by using the multi-year 10-days
composite SPOT/VGT NDVI data. First, the long time series NDVI is reconstructed. Then a relative threshold value
method is given to determine whether the vegetation begins to resuscitate. The spring onset frequency map mainly
parallels the latitude. But because of the heterogeneity of vegetation and monsoon, the spring onset movements do not
parallel the latitude completely.
By analyzing several collocated QuikSCAT measurements and Special Sensor Microwave Imager (SSM/I) rain rate in
typhoons, the evidence of rain influence to wind retrieval is presented. The results show that the present of heavy rain in
typhoons will cause large bias in both wind speed and wind direction for QuikSCAT wind retrieval. So that the
Holland's model is applied in the ambiguity clear process to correct the errors in wind direction induced by rain. Also, a
radiate transfer function (RTF) and collocated SSM/I rain rate is employed to correct the attenuation and scattering
effects of rain. The performance of RTF method is limited due to lack of information of the collocated rain rate and the
un-precise of the RTF. As an alternative way to RTF, an interpolation method which just uses the data from QuikSCAT
itself is introduced to correct the attenuation and scattering effects of rain. This method is applied to retrieve the wind
vector in typhoon Ioke, the result shows that the bias in the wind direction and wind speed induced by rain has both been
well corrected, indicating that our correction to the impacts of rain on QuikSCAT wind retrieval in typhoons is effective.
Altimetry data under extreme weather events such as tropical cyclones, typhoons and hurricanes are valuable although
the measurements are affected by various factors associated with high sea states, such as big winds, high waves,
especially atmospheric rains and ocean surface foams. Both rains and foams can strongly affect the propagation and
reflection of microwave signal, but the effects of sea foam on altimeter measurements have not been adequately
addressed. Although the sea foam only appears when the wind speed is high and ocean wave is breaking, the attenuation
effect of foam in typhoons should not be neglected. The major challenge is the effects of rain and foam on altimeter
received backscatter are similar and are hard to be separated. In this paper, we proposed a iterative method to correct
both rain and sea foam effects using a simplified stratified foam model and the liquid water content measurements from
nadir viewing Jason1 Microwave Radiometer. Finally a case study to maintain accurate wave height, wind speed, and
rain rate measurements and to retrieve the additional results of foam coverage considering both the effects of rain and sea
foam in the typhoon Shanshan is presented.
At the beginning of 2008, the south area of China suffered a rare heavy snow and low temperature weather, which
brought enormous economic lose and broke the environment. The abnormal weather also influenced the ocean color
environment. Through analysis of MODIS remote sensing 3A data during 2 months before and after the snowstorm and
low temperature weather, the author finds that, on the one hand,compared with same period of last year, the sea surface
temperature (SST) from the East China Sea to the South China Sea (18°N-32°N 108°E-126°E descended 2.57°C; the
average chlorophyll-a concentration(CHL-a)rose from 1.198 mg. m-3 to 1.75 mg. m-3 in the snowstorm and low
temperature weather period from January 11 to 31 of 2008 which was 1.46 times more than that of the same period of
last year. On the other hand, compared with the period before snowstorm,the SST decreased from 22.42°C to 18.34°C but the CHL-a rose from 1.32 mg. m-3 to 1.60 mg. m-3 after the snowstorm. In addition,the sea water transparency(SDD)
had a certain increase in the open sea of South China Sea, but the suspended sediment concentration(SSC) increased
significantly near the seashore, the Yangtse River Estuary and the Pearl River Estuary, which increased 200% compared
with the period before the snowstorm 2008. Through researching and indicating, the main reason of increase of the
CHL-a in the near seashore area(the I water) was more probably due to the increase of the SSC, and the CHL-a by
remote sensing has greater error, which rising from the high SSC led to the increase of CHL-a; but in the open sea the
increase of CHL-a is that the SDD improved and then the euphotic increased. As a result,this could promote the growth
of primary productivity. Therefore, it faces the better applied foreground to monitor the influence on the ocean
ecosystem environment caused by the snowstorm and low temperature weather through remote sensing.
After Analyzing correlations of ocean surface wind speeds and the channel combinations of brightness
temperature, it is found that the difference of brightness temperature between 22GHz vertical polarization and
19GHz horizontal polarization and the ratio of the difference between 19GHz vertical polarization and 19GHz
horizontal polarization to the difference between 37GHz vertical polarization and 37GHz horizontal polarization
should be used to retrieve ocean surface wind speed. So we add these two channel combinations to improve the
Goodberlet's algorithm and derive wind speeds from the brightness temperature of SSM/I five channels measured in
2005. Comparing the results of two algorithms against in-situ buoy wind speeds shows that the improved wind speed
retrieval algorithm is better than Goodberlet's algorithm, the wind speed estimation accuracy improves by 0.9m/s
and 0.5m/s under clear condition and cloudy condition respectively.
A complete data set is crucial for many applications of satellite images. Therefore, this paper tries to reconstruct the
missing data sets by combining Empirical Orthogonal Functions(EOF) decomposition with Kriging methods. The
EOF-based method is an effective way of reconstructing missing data for large gappiness and can maintain the
macro-scale and middle-scale information of oceanographic variables. As for sparse data area (area without data or with
little data all the time), EOF-based method breaks down, while Kriging interpolation turns effective. Here are the main
procedures of EOF-Kriging(EOF-K) method: firstly, the data sets are processed by the EOF decomposition and the
spatial EOFs and temporal EOFs are obtained; then the temporal EOFs are analyzed with Singular Spectrum
Analysis(SSA); thirdly, the sparse data area is interpolated in the spatial EOFs by using Kriging interpolation; lastly, the
missing data is reconstructed by using the modified spatial-temporal EOFs. Furthermore, the EOF-K method has been
applied to a large data set, i.e. 151 daily Sea Surface Temperature satellite images of the East China Sea and its adjacent
areas. After reconstruction with EOF-K, comparing with original data sets, the root mean square error (RMSE) of
cross-validation is 0.58 °C, and comparing with in-situ Argo data, the RMSE is 0.68 °C. Thus, it has been proved that
EOF-K reconstruction method is robust for reconstructing satellite missing data.
Because of global climatic variations and anthropogenic influence on local environment, as the active interaction belt
between ocean and land, the coastal ecosystems are sensitive even part of them are under pressure. It is of very necessary
to diagnose whether they are in healthy stage. The Zhejiang coastal zone situated at about 120°E-123°E and 27°N-31°N, the landuse have changed largely during the past 20 years as long as the rapid economic development. In this
paper the largest island-Zhoushan island- in the Zhejiang coastal line is selected as the study site. The objective is to
establish a way to assess coastal ecosystem health stage. Indicators include the landuse transformation, water quality,
ecosystem services during 1986 to 2005. The results indicate that the human pressure become more and more large. The
scene generally is the outcome of economic pursuing activity. In the discussion we also provide some strategy to keep
the human and nature harmonious.
With the availability of scatterometer data, surface wind vectors can be estimated from the backscatter measurement over
oceans, guarantee global, long-term monitoring of the winds on the oceans, which make them very valuable for climate
studies and other applications. At moderate wind speeds, the wind speed derived by scatterometer is considered reliable.
But at higher wind speeds, scatterometers appear to underestimate the wind speed, especially in tropical cyclones,
because of deficiencies of the geophysical model function for high winds, attenuation caused by rain, influence of wind
gradient, and the saturation of the backscattering under high wind.
As a passive microwave sensor, radiometer does not show obvious saturation phenomena under high wind, therefore it is
an appropriate candidate to be used to retrieve high wind speed. In this paper, combined scatterometer and radiometer
data is used to retrieve wind field under high wind condition. Using in situ data and meteorological data as a criterion,
we compared the wind retrieval performances of scatterometer and radiometer. Results show that it is better to use
radiometer data as a replacement of scatterometer while observing high wind speed.
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