**8. Modelling of satellite measure under sea water**

The knowledge of the topography of the seafloor is important for several applications. The principle of measure of bathymetry necessarily takes this model of reflectance joining the intensity of radiometric signal measured by the satellite to the depth as a basis; it can call on the physical method that requires the knowledge of all parameters governing this model (optic properties of water, coefficient of reflection of the bottom, transmittance of the atmosphere (Minghelli-Roman et *al.,*2007). The model provides of image mono channel where each pixel of the maritime domain is represented either by a radiometry in-situ but rather by a calculated depth. In general the use of hybrid multiple SPOT band regression algorithms are superior to the exclusive use of any single band. (Bachari & Houma 2008, Houma et *al.*,2010)

The spectral distribution of the submarine radiance varies in a complex way with the depth, in relation with the selective character of the attenuation.

The total signal received by a sensor operating at high altitude water above can be decomposed in a first time, in two terms:

$$\mathbf{S}\_{\mathbf{t}\_{\lambda}} = \mathbf{S}\_{\mathbf{a}\lambda} + \mathbf{S}\_{\mathbf{e}\_{\lambda}} \tag{29}$$

with Ssλ is an atmospheric component and Seλ is a water component

In a second time, it is possible to analyze the composing water measured near the surface:

$$\mathbf{S}\_{\mathbf{e}\_{\lambda}} = \mathbf{S}\_{s\lambda} + \mathbf{S}\_{d\lambda} + \mathbf{S}\_{\hat{\mathbf{n}}} \tag{30}$$

Fig. 25. Radiometric correction in the SPOT XS3 channel of the bay of Algiers.

B2 (red: 0.61 – 0.68 microns), and B3 (near infrared: 0.78 – 0.89 microns).

**8. Modelling of satellite measure under sea water** 

in relation with the selective character of the attenuation.

with Ssλ is an atmospheric component and Seλ is a water component

decomposed in a first time, in two terms:

scattering and Rayleigh are less experienced.

Houma et *al.*,2010)

In the histogram of the coefficient of variation we wish to point out that the first channel has a high coefficient corrected this can be explained as the effect of correction is more experienced in this channel than in the other two channels. In the third channel (NIR), Mie

Images are acquired by satellite sensors (HRV pour SPOT 2) (B1 (green: 0.50 – 0.59 microns),

The knowledge of the topography of the seafloor is important for several applications. The principle of measure of bathymetry necessarily takes this model of reflectance joining the intensity of radiometric signal measured by the satellite to the depth as a basis; it can call on the physical method that requires the knowledge of all parameters governing this model (optic properties of water, coefficient of reflection of the bottom, transmittance of the atmosphere (Minghelli-Roman et *al.,*2007). The model provides of image mono channel where each pixel of the maritime domain is represented either by a radiometry in-situ but rather by a calculated depth. In general the use of hybrid multiple SPOT band regression algorithms are superior to the exclusive use of any single band. (Bachari & Houma 2008,

The spectral distribution of the submarine radiance varies in a complex way with the depth,

The total signal received by a sensor operating at high altitude water above can be

In a second time, it is possible to analyze the composing water measured near the surface:

tae SSS λ λ = +λ (29)

esdf SSS S <sup>λ</sup> =++ λ λλ (30)

with Ss<sup>λ</sup> a specular reflection at the surface, Sf<sup>λ</sup> is a reflectance of the bottom in shallow waters, Sdλ a component owed to the diffuse reflection by volume water.

$$\begin{split} \mathbf{S}\_{\mathsf{e}\lambda} &= \mathbf{G}\_{\lambda}\boldsymbol{\rho}\_{s} + \mathbf{G}\_{\lambda}\boldsymbol{\rho}\_{s}.\mathrm{o}\boldsymbol{\rho}\_{0} \left( \frac{1}{\boldsymbol{\rho}\_{s}} - 1 - \left( \frac{1}{\boldsymbol{\rho}\_{s}} - 1 \right) \mathbf{R}\_{\mathsf{a}} \exp(-\mathrm{k}\mathbf{z}\left( \cos\boldsymbol{\theta}\_{\mathsf{z}} + \cos\boldsymbol{\theta}\_{\mathsf{v}} \right)) \right. \\ &+ \mathbf{G}\_{\lambda} \left( 1 - \boldsymbol{\rho}\_{s} \right) \mathbf{R}\_{\mathsf{a}} \exp - \mathrm{k}\mathbf{z} (\cos\boldsymbol{\theta}\_{\mathsf{z}} + \cos\boldsymbol{\theta}\_{\mathsf{v}}) \end{split} \tag{31}$$

with ρλ a reflectance of the sea water, Ra, a reflectance of the bottom, k, is attenuation coefficient, z, a depth, ω0 albedo of diffusion of water molecules, θz a zenith angle and θv a viewer angle of the sensor.

Fig. 26. A variation a luminance's of a SPOT XS with a depth

Fig. 27. A variation a luminance's of a LANDSAT TM with a depth.

Solar Radiation Modeling and Simulation of Multispectral Satellite Data 219

contribution of different elements making up the signal that reaches the sensor. Simulation

The proposed radiometric correction method is simple because it is based on pixels that are known to support their radiometric images. The luminances are simulated using the software (SDDS) which allows us to establish rules between reported digital luminance and luminance reflectance. The techniques of normalization of images are to correct the atmospheric degradation, the effects of illumination and variations in the responses of the sensors in the multitemporal and multispectral imaging. Thus the methods developed in

Bachari N.E.I., Belbachir A.H ., et Benbadji N.,1997 .Numerical Methods for Satellite

Bachari N.E.I., et Houma F., 2005. Combination of data soils and data extracted of satellites images for the survey of the bay of Algiers, MS'05 Rouen, 6-8 Juillet 2005,France. Bachari N.E.I., et Houma F., 2008.Contribution of satellites visible and infrared images for

Bachari N.E.I.,1999. *« Méthodologie d'analyse des données satellitaires en utilisant des données* 

Becker F., 1978. Physiques fondamentales de la télédétection. Ecole d'été de physique

Becker F., et Rffy M., 1990. Modèles et modélisation en télédétection, Télédétection spatiale:

Bukata R.P., Jérome J.H., Kondratyev C., and Poszdnyakov D.V., 1995. *Optical properties and remote sensing of inland and coastal waters*. CRC Press, Boca Raton, Florida Chadin A.,1988. Les modèles d'interaction rayonnement-atmosphère et détemination de

Deschamps P.Y., Herman M., and Tanré D., 1983. Modeling of the atmospheric effects and its application to the remote sensing of ocean color. *Appl. Opt*., 22: 3751-3758 Gordon H.R., et Clark D.K., 1981. Clear water radiances for atmospheric correction of Coastal Zone Color Scanner imagery », *Appl. Opt.*, no 20, p. 4175-4180. Guyot G., and Fagu X.,1992. Radiometric corrections for quantitative analysis of multispectral, multitemporal and multisystem satellite data, Int, J, Remo.Sens . Houma F., Abdellaoui A., Bachari N.E.I., and Belkessa R., 2010.Contribution of Multispectral

Algiers bay, Algeria. *Journal Physical Chemical News, volume 53, P57-61*. Houma F., R. Belkessa, Khouider A. Bashar NIS, and Z. Derriche, 2004. Correlative Study of

the follow-up of the inshore water quality; International Conference on "Monitoring & Modeling of Marine pollution" (INCOMP 2008); KISH 1-3 /12

*multi-sources » Thèse de Doctorat d'état* en Physique; Rayonnement-Matière, 11 avril

Aspects physiques et modélisation., pp 37-162, Toulouse, Cepadues-édition, 1032

paramètres météorologiques et climatologiques à partir d'observation satellitaires. Télélédétection spatiale : Aspects Physiques et Modélisation, Cepadues Editions, p

Satellite Imagery to the Bathymetric Analysis of Coastal sea bottom. Application to

Physico-chemical parameters and satellite data to characterize IRS1C water

this section may be modified or combined as required by the user.

Imagery Analysis, AMSE.,J Volume.38, N°1,2, pp 49-60.

Bougeur P., 1953. Essai d'optique sur la graduation de la lumière Ann.Pys.8

software satellite data is developed.

**10. References** 

2008

pages.

1031.

1999, Oran USTO, Algérie.222p.

spatiale C.N.E,S.

In the case of the channel 2 of the spot the sensitivity of this channel to effects of the bottom can reach 10 meters. For the channel 1 of the spot the effect of the bottom can reach funds that pass the 30 meters. For the TM1 the effect of the bottom can reach funds of 40 to 50 meters.

The CN2 quantities and CN1 are luminance's corrected of the atmospheric effects. As in this case we removed the point that present a maximum of SM. This singular point presents an anomaly that indicates the streamlined convergence of currents.

Notices the variable Z is just to the middle in relation to the two luminance's. We removed data that correspond to depths superior to 60ms. Since for depths that pass the 50 meters the effect of the bottom on measure satellite is non-existent. The set of the corrected data are analyzed by an exponential regression. Results in this case are better presented and the curve of adjustment is representative of the cloud of points since the coefficient of interrelationship reaches the 88%. (Bachari & Houma, 2005)

### **Correlative analysis**

1. Monoband model

Results of studies led on the bathymetry are bound directly to features of satellites. On curves of reflectance's we notice that more the depth is important, more the radiance is absorbed and more the level of radiometry is weak. The spectral resolution permits to observe in the light waters objects as far as 40 ms on the XS1 channel, and as far as 15m on the XS2 channel. The XS3 channel when to him doesn't bring any bathymetric information since the infrared is absorbed by water.

The reflectance of the bottom, during his ascension toward the surface, sudden a selective attenuation. All it has for effect a bruising of the spectral answer of the bottom that returns discriminations noise in that the depth increases.

$$\mathbf{X}\mathbf{S1} \qquad \qquad \mathbf{Z} = \text{-0.27823} + \text{2.68400.exp} \text{(-(XS1-47)/5.8886)} \tag{32}$$

$$\textbf{X}\textbf{S}\textbf{2} \qquad \textbf{Z} = \textbf{-0}\angle\textbf{5}79 + \textbf{5}\angle\textbf{8}\textbf{3}\textbf{9}\textbf{5}.\exp\left(\because \text{(\text{\textquotesingle}\textbf{X}\textbf{2}\cdot\textbf{2}\textbf{5}\rangle\textbf{/4},\textbf{2}\textbf{4}\textbf{1}\textbf{3}\text{4}\right)}\tag{\text{\textquotesingle}}\tag{\text{\textquotesingle}}\tag{\text{\textquotesingle}}\tag{\text{\textquotesingle}}\tag{\text{\textquotesingle}}$$

#### 2. Several channels'

For this reason one tried to achieve some multiple and polynomial interrelationships between these three variables:

$$Z = -148.8 - 2.76 \text{ XS1} + 17.93 \text{ XS2} - 0.014 \text{XS1}^2 + 0.57 \text{ XS1}^\* \text{XS2} - 2.04 \text{ \* } \text{XS2}^{\*2} \tag{34}$$

The developed equation permits us to achieve a direct extraction of the bathymetries while combining the two pictures satellites one hold in the channel1 and the other in the channel 2. To achieve the extraction of the bathymetry from pictures satellites we used the software *PCSATWIN* . (Bachari,1997)

#### **9. Conclusion**

A methodology was developed to solve the problem caused by the effect of the atmosphere that usually results in a signal noise. To make this work, we first followed the path of the solar spectrum as a double drive-ground and ground sun-sensor. To highlight the contribution of different elements making up the signal that reaches the sensor. Simulation software satellite data is developed.

The proposed radiometric correction method is simple because it is based on pixels that are known to support their radiometric images. The luminances are simulated using the software (SDDS) which allows us to establish rules between reported digital luminance and luminance reflectance. The techniques of normalization of images are to correct the atmospheric degradation, the effects of illumination and variations in the responses of the sensors in the multitemporal and multispectral imaging. Thus the methods developed in this section may be modified or combined as required by the user.

#### **10. References**

218 Atmospheric Model Applications

In the case of the channel 2 of the spot the sensitivity of this channel to effects of the bottom can reach 10 meters. For the channel 1 of the spot the effect of the bottom can reach funds that pass the 30 meters. For the TM1 the effect of the bottom can reach funds of 40 to 50

The CN2 quantities and CN1 are luminance's corrected of the atmospheric effects. As in this case we removed the point that present a maximum of SM. This singular point presents an

Notices the variable Z is just to the middle in relation to the two luminance's. We removed data that correspond to depths superior to 60ms. Since for depths that pass the 50 meters the effect of the bottom on measure satellite is non-existent. The set of the corrected data are analyzed by an exponential regression. Results in this case are better presented and the curve of adjustment is representative of the cloud of points since the coefficient of

Results of studies led on the bathymetry are bound directly to features of satellites. On curves of reflectance's we notice that more the depth is important, more the radiance is absorbed and more the level of radiometry is weak. The spectral resolution permits to observe in the light waters objects as far as 40 ms on the XS1 channel, and as far as 15m on the XS2 channel. The XS3 channel when to him doesn't bring any bathymetric information

The reflectance of the bottom, during his ascension toward the surface, sudden a selective attenuation. All it has for effect a bruising of the spectral answer of the bottom that returns

 **XS2** Z = -0,2579 + 5,83395.exp (-(XS2-25)/4,24134) (33)

For this reason one tried to achieve some multiple and polynomial interrelationships

The developed equation permits us to achieve a direct extraction of the bathymetries while combining the two pictures satellites one hold in the channel1 and the other in the channel 2. To achieve the extraction of the bathymetry from pictures satellites we used the software

A methodology was developed to solve the problem caused by the effect of the atmosphere that usually results in a signal noise. To make this work, we first followed the path of the solar spectrum as a double drive-ground and ground sun-sensor. To highlight the

Z 148.8 2.76 XS1 17.93 XS2 0.014 XS1² 0.57 \* XS1 \* XS2 2.04 \* XS2² =− − + − + − (34)

**XS1** Z = -0,27823 + 2,68400.exp(-(XS1-47)/5,8886) (32)

anomaly that indicates the streamlined convergence of currents.

interrelationship reaches the 88%. (Bachari & Houma, 2005)

meters.

**Correlative analysis**  1. Monoband model

2. Several channels'

between these three variables:

*PCSATWIN* . (Bachari,1997)

**9. Conclusion** 

since the infrared is absorbed by water.

discriminations noise in that the depth increases.


**10** 

**Reactivity Trends in** 

**Radical-Molecule Tropospheric** 

**Reactions – A Quantum Chemistry** 

Cristina Iuga1, Annia Galano2, Raúl Alvarez-Idaboy3,

*3Facultad de Química, Universidad Nacional Autónoma de México* 

*1Universidad Autónoma Metropolitana, Azcapotzalco 2Universidad Autónoma Metropolitana, Iztapalapa* 

*4Instituto Andaluz de Ciencias de la Tierra,* 

*CSIC-Universidad de Granada* 

*1,2,3México 4Spain* 

**and Computational Kinetics Approach** 

Ignacio Sainz-Dìaz4, Víctor Hugo Uc1 and Annik Vivier-Bunge2

The most relevant chemical reactions that take place in the atmosphere involve free radicals and volatile organic compounds (usually termed VOC). In the troposphere, the main sink of volatile organic compounds (VOC) is oxidation, initiated typically by reaction with hydroxyl (OH) free radicals. Many of these processes give rise to the formation of new radicals, which ultimately cause higher OH radical levels and thus higher rates of reactions

Kinetic investigations of the OH radical reaction with VOC's are essential for the evaluation of their significance in air pollution. Reaction rate coefficients are used, for example, in estimating their tropospheric lifetimes, or in atmospheric chemical model calculations which are used to generate distribution maps of air pollutants under given meteorological and topographical conditions. Furthermore, the use of temperature dependent reaction rate coefficients in model calculations increases their accuracy, since the temperature gradient of the troposphere and the seasonal temperature variations can be taken into consideration.

As a result of almost three decades of research, the rate constants and mechanisms of the initial reactions of OH and NO3 radicals with VOCs are now reliably known or can be estimated. Significant advances have been made in our understanding of the mechanisms of the reactions subsequent to the initial OH and NO3 radical attack on selected VOCs and of first-generation products formed from these reactions. Extensive and comprehensive reviews on the current state of knowledge of atmospheric reactions of VOCs have been written periodically over the years. Modern rate constant measurements are often precise, and individual values are known fairly well. In addition, methods exist for estimating rate

**1. Introduction** 

of the other VOC present.

pollution. Application to the Bay of Oran, Algeria. Water Science , volume 17 / 4, 429-446.

