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Remote Sensing application of current field on sea water surface layer and water quality on harbor and bay

Li Yinxi
Remote Sensing Satellite ground Station of Chinese Academy of sciences, Beijing, China

ChiYaobin
Beijing Research Institute for information of Remote Sensing, Beijing, China

Li Teifang
Center for Remote Sensing, Zhongshan University Guangzhou,China


Abstract
The remote sensing sea water current field is an instantaneous status data surface current which is recorded during satellite pass it shows the directions and speeds of the surface layer currents, interactions between different current systems and water patches, and relationships between sea water, land and island. Because the surface layer current field is certainly related to the situation under seawater, it can be well used to analyze water bodies, under seawater dynamics, and water exchange in bodies. Besides, the remotely sensed information about water temperatures, transparencies tells how the natural environmental factors influence harbor water quality, so that it is useful for evaluation of cultivation in sea water, city and harbor sewage disposal engineering, and self-cleaning capability. The advantage of remote sensing technology is the provision of global, cheap, direct information about how the environment influences water quality, its diffusion and exchange, so that we can have a better understanding of the wide sea areas. In this paper we discuss characteristics of the remote sensing current field and extractions of various sea water surface current field information based on images processing and fuzzy criteria method so as to evaluate the preset status of the sea water resources of sea areas around the Miao Islands, Bohai sea , China.

Characteristics of the Remote Sensing current field
There are two features for the spectral reflectance of surface current: the movement of seawater surface in vertical or horizontal directions causes irregular distribution of the roughness of water surface. The ratio of incident and reflected sunlight changes. For example, if velocity is high, the water surface vibrates more strongly, the ratio of diffused and reflected light increases, while the ratio of entering part decreases, which results in the increase of the brightness value of the pixels. On the contrary, if the water surface is quiet and smooth, the entering part increases, the brightness value of the pixels decreases, the second feature is the dependence of quality, chemical, physical characteristics of suspended matter and dissolved substances, which result in the water color changes, and in turn the forms of currents, current tracks. That is, the suspended matter and dissolved substances play the role of tracking items. For example, the alongshore currents carry a lot of mud and sand from the land, they are mostly yellow color; the currents from deep seas are blue. These two color differences are big, which shows the relationships between their interactions.

The above-mentioned current information is represented as spectral information and sensed by sensors. Total signal L can be shown as follows:

L= Lsg + Lhg + Lp+ Lw ----------------(1)

where : Lsg - information about the change of water surface rough-ness
Lw-radiation signal of water bodies, providing the color information of different current system and wate patches

Extraction of Surface Current Field Information
  1. Extraction of current field information through Water surface Roughness

    The water surface information is implified in the signal Lsg as :

    Lsg = E0 * cosqs * EXP [-t/cosqs] * gv (q2 , js ; qr , jr)----------(2)

    Where E0 is the solar radiation on top of the atmosphere, q the sunlight incident angle, EXP [-t/cosqs] - the transmission function of atmosphere path, gv bi-directional reflectance function; where (qs js)- solar zenith and azimuth angle (qr js) view angle. If the atmospheric columns are uniform above the area of acquistion , E0 * cosqs * EXP [- t cosqs] can be taken as constant, so signal Lsg is mainly dependant by term gv, which is related to sea status only gv can be consideredas a function of sea surface horizontalmovement. If the wind is strong there are foams,then gv in (2) can be represented as:

    gf = (1-Cf) * gv ; (qs js) + Cf * rf /p---------------------(3)

    Where Cf-foaming coverage index

    Cf = foaming covering area / total sea area

    When the wind velocity u£9m/s , Cf = (1.2*10-5) * u3.3, r f the spectral reflectance of the foams. To decide term Lsg, we must first select the bands, TM3, TM4 and TM5, which penetrate not much into the water, so that water depth change related term Lw does not contribute much. Then atmospheric correction processing is conducted to remove the contribution of Lhg (atmospheric diffusion) and Lp (sky paricles), such that L@Lsg. If gv and other parameters are known, the reflectance of water surface can be calculated . Due to that sea status varies a lot from time to time and from space to space,so function gv is a variable . It is very difficult to optain its parameters. Therefore fuzzy matmatics is used to establish the function between remote sensing signal and current fields. By formula (2) of the fuzzy relation between remote sensing image bightness value and texture density, and current the fuzzy member ship function mc(L) described as:




    where L- pixel brightness values, L@ Lsg . The texture characteristics in the image is related with current velocity, so the relaton between them can also be described by fuzzy membership

    where T- testure density of the image. In shallow water sea area , the water velocity is often effected by the terrain under water. If terrain rises suddently, the water velocity will increase to maintain the continuity of water flow. So the terrain changes under sea water result in corresponding roughness change of surface water that is texture feature change. Combining (4) and (5), the current change of the whole sea area is me(E)

    me (E)= mc U mc (T)-------------------(6)

    where U - fuzzy "OR" operation. The meaning is that the current velocity represented by pixel brightness and texture density can be obtained by the method of taking the big value. The flood rise field picture was made for the sea area around Miao Island with the above mentioned procedures (see Fig. 2)




    The points of same brightness values and texture densities are connected by dolted lines, showing roughly equal current velocities . The velocities are differentiated by the values of brightness and texture densities. When the satelite passes over, the current velcoities and directions were measured synchronously. The field measured points are used as control points. The field information from the remote sensing current velocity picture can be marked . Actural mesurement is not strictly synchronous , because it was only 10-30 sec. for the satelite to be above the area, so it is only quasi-sychronous, sea status and sun elevation angle should not change a lot, while points of measurement are only a few . Nevertheless, the correlation of the drawn current field picture with in-site measurements is still up to 80%

    The directions at currents shown on the remote sensing image are very explicit. They can be directly determined by interpreting current lines and directions, clustering, diffusing of textures.

  2. Extraction of the feature information of water dynamics>

    Different current systems and water patches often result from wind field on the sea surface, water temperatures, water densities and kinds of suspended matters. Their interaction is shown as water color changes and texture interleaves. For example, different water colors or the merging, paralleling, clustering, diffusing, and so on. of water dynamics. water dynamics feature information is mainly represented by term Lw of about the band combination. Lw is back diffusion spectral signal of water bodies, is the combined result of back diffusion energy signals of suspended matters and diolved substances in water. In order to display the features of current systems and water patches of different nature, it is necessary to remove (Lhg + Lp) in (1) from the particle radiation interference to increase the contrast in term Lw. TM3-5 are selected . They do not penetrate a lot, but represent a lot of water body information . The signal energy contributed by water particles and depths should be decreased , so that color contrast can be increased for suspended matters in different current systems or dissolved substance. After image stretching, the current system information is very audio -visual. One example is Fig.2, the image picture for Miao Islands during flood rise. We can see the Eastward flood rise a North eastward alongshore currents in winter . We vcan also see these two currents merge at south of Dengzhou waterway. This is the dynamic condition of the formation of Dengzhou shallow . Synthesizing the features of flood rise and outgoing tide current fields, and water dynamic, the relationship picture of the relative water exchanges in the harbors is shown as fig.3
Extraction of turbidity information
The turbidity is mainly determined by mud, sand and quantity of Chlorophyll, and represented as the seawater color. When there is a lot of sand, the water is yellow; when the quantity of chlorophyll is high, the water is green because they have different spectral characteristics for different TM bands. The first thing to extract turbidity information is to eliminate the watercolor differences caused by terrain changes and differences of surface current velocities. The method is to select different TM bands and time phases, and also to correct terrain influence by sea chart data. The second thing is to use band ratio (TMi / TMj) . The selection of i, j should be favorable for maing the ratio of mud and sand in water (TM2/TM1 ) , or for the ratio of chlorophyll (a) (TM1/TM3) . The third thing is to select the conditions to control the dynamics of the quantities of mud, sand and chlorophyll. For example, the water bodies with much sand are usually found in sediment areas, where the water is shallow and velocity is low. Once if it happens that strong current brings up sand, the sand contained in the water will increase. The area with a


large quantity of chlorphyl is the sea area, where the exchanging of water is bad. It means that the current field, current system, and terrain are control parameters of sea water turbidity. By the application of remote sensing image, sea chart, and related hydrometric information, we can make synthetic analysis. We can also use fuzzy membership functions m (C1) m(C2) to describe the control factors of sand quantity and chlorophyll quantity. At last the related membership functions of sand, chlorophyll ,and turbidity can be set up:

m(s) = F [TM2/TM1] Çm(C1)------------------(7)

m(ch) = F [TM 1 /TM3] Çm(C2) ----------------(8)

m(T) = m (S) + m(ch) --------------------------(9)


where m(S) - sand membership function
m(ch) - chlorophyl quantity membership function
m(T) - synthetic related function of sand and cholorophy quantity
Ç-the "AND" logical operation of fuzzy function.

At last by practical sampling of membership functions and further relative analyzing we can transform (extrapolate) the related values to a distribution chart of sand, chorophyl quantity and turbidity

Extraction of tempera true information
As is well known, the remote sensing data about surface sea water temperatures can be obtained with TM7 or meteorological satellite sensors (NOAA10 AND NOAA 11)

Evaluation of Remote Sensing water quality environment
The water quality environment is composed of many factors. Different purposes of water quality requirements correspond to different water quality environment factors. For example, in the sea areas nearMiao island, an important seafood production place, the scallop is raised mainly. The water quality requirements are: appropriate temperatures, turbidities (especially alongshore current with various Nutritious salts and halliplankton), source transportation conditions, water exchange conditions, and seabed material and water depth conditions. Fig.4 is a cultivation condition chart after synthesizing various factors and related chart according to the scallop cultivation requirements. Relative classes of the conditions are shown on the chart. Class 1 is the best and Class 5 is the worst. The evolution results coincide with the field cultivation quantities. The remote sensing evaluation shows that the joining dam between North and South Changshan is - lands had destroyed the water exchange conditions for the water west to Changshan Island, Which results in low productivity of scallop in that area.

The water quality environment Remote Sensing evaluation has the advantages of global view, audiovisual, real-time, and synthesizing. It can be used as a complement or extension of routine survey. The practical profit of water resources survey in broad shallow seawater areas can be increased. It helps to make decisions about how to make better use of coastal zones.


References
  1. Arthur P. Cracknel < Remote Sensing Applications in Marine Science and Technology > published in cooperation with NATO Scientific Affairs Division 1982.

  2. Robert H. Stewart published uder the auspices of the Scripps institution of oceanography UCSD 1985 P 108-113

  3. A.P. Cracknell< remote Sensing in Meteorology Oceanography and Hydrology> published by ELLIS HORWOOD LIMITED in 1981. P178-204

  4. yang yilong Vol.9, No.6, Nov., 1985