G. M. Krekov

Laser Sensing of a Subsurface Oceanic Layer. II. Polarization Characteristics of Signals.

In Part I of this paper we calculated depth profiles and polarization characteristics of airborne lidar return signals by the Monte Carlo method. Here we calculate the polarization characteristics of lidar return signals for different types of water. We demonstrate the feasibility of polarization lidar application to the detection of underwater inhomogeneities of different origins. It is shown that simultaneous analysis of depth profiles of the lidar return signal power and signal depolarization ratio substantially increases the information content of airborne lidar sensing of seawater. We compare calculated results with the data of airborne lidar measurements for lambda = 0.53 mum.

Laser sensing of a subsurface oceanic layer. I. Effect of the atmosphere and wind-driven sea waves.

Depth profiles and polarization characteristics of airborne lidar return signals have been calculated by the Monte Carlo method. We analyze some peculiarities of depth profiles of lidar return signals for a rough air-water interface. The distorting effect of the atmosphere on the lidar return signal structure is evaluated as a function of the geometry of the observations. Calculated results are compared with the data of airborne lidar measurements for lambda = 0.53 mum.

Technique for the local estimation of fluxes in broadband lazer sensing problems

Using the Monte Carlo method, we solve the problem of evaluating spatially resolved signals of a broadband pulse emitter in the aerosol atmosphere with accounting for selective molecular absorption. Such a problem originates due to the necessity of the a priori analysis of the potentiality of white-light lidars for the remote sensing of the atmospheric concentrations of H2O vapors and greenhouse gases. The estimation of the backscattering signals with a high spectral resolution on the basis of the nonstationary transfer equation requires the use of precision computation algorithms. In the theory of the Monte Carlo methods, such an algorithm is the method of the local estimation of fluxes. We suggest combining this algorithm with a high-precision line-by-line computation of the transmission functions of atmospheric gases, which provides the possibility of a rigorous quantitative forecast of the efficiency of promising environmental monitoring lidar systems.

Reabsorption of laser-induced fluorescence in a plant canopy: Stochastic model

This paper continues the series of publications on the statistical simulation of transspectral processes. A system of interrelated radiative transfer equations is proposed. This system gives a formal basis for a numerical analysis of a wider range of spectroscopic effects that accompanies the propagation of laser radiation in the environment, such as the reabsorption of fluorescence in dense disperse media containing two and more fluorophores. As applied to the problem of lidar monitoring of the state of a plant canopy, an optical model is developed in which a leaf is not treated as an individual scattering element, but rather as a local volume of a multiphase medium with a complex polydisperse structure. The Monte Carlo algorithms have been modified so that they have achieved the simulation of fluorescence and reabsorption processes. Test calculations have demonstrated the adequacy of the proposed approach.

Radiative characteristics of plant leaf

Existing leaf radiation models are reviewed. A new concept of the optical model of the leaf as a multiphase system containing three aggregate ensembles of particles significantly different in microphysical and optical characteristics is proposed. The proposed model is based on the reconstruction of the particle size distribution function from the experimental leaf absorption spectrum. Based on the obtained microphysical model of the plant leaf, the spectra of optical radiation reflection and transmission in the range of 400–800 nm are calculated for various relative concentrations of light-absorbing pigments (chlorophyll a, b and carotenes) and various leaf thicknesses. Optical radiation propagation was simulated using the stochastic Monte Carlo method. The simulation results are in good agreement with relevant experimental spectra.

Lidar equation for a broadband optical range

We have numerically studied the use of a genetic algorithm for reconstructing vertical concentration profiles of trace atmospheric gases from the data of pulsed broadband lidar sounding in a frequency range covering the regions of selective optical absorption of these gases. A generalized form of the lidar equation is proposed that takes into account finite spectral intervals of backscattered radiation. The possibility of using pulsed excilamps of the new generation as sources of radiation for the optical sounding of the atmosphere is demonstrated for the first time. The validity of the proposed approach is illustrated by quantitative examples.

Estimation of the broadband lidar potential for remote sensing of the molecular atmosphere

The results of a closed numerical experiment devoted to the laser sensing of the water vapor and trace gas concentrations in the tropospheric layer of the atmosphere based on a new LIDAR-DOAS hybrid technology using atmospheric aerosol as a distributed route reflector are discussed. The quantitative estimations, performed based on the Monte Carlo method, confirm the perspectives of a similar approach, which extends the potential of the classical scheme of differential optical atmospheric spectroscopy (DOAS) used to distantly control and localize dangerous anthropogenic emissions of toxic gases up to the tropopause altitude. The statistical modeling algorithms should be substantially modified, since it is necessary to estimate lidar returns with a high spectral resolution based on the transient transfer equation. A new method, which takes into account selective absorption of the gaseous atmosphere, has been used to locally estimate a flux. The combination of this method with the genetic algorithm for solving the inverse problem of reconstructing the required tropospheric gas components makes it possible to accurately quantitatively predict the efficiency of the developed lidar systems of environmental monitoring.

Improved genetic algorithm for multiwave lidar sensing of atmospheric aerosol

An algorithm for reconstructing microphysical characteristics of cloudiness and aerosol formations by the use of white light lidars based on lasers with femtosecond pulse duration is presented. The direct problem of broadband radiative transfer is solved by the Monte Carlo method, and then the inverse problem is solved using a modified genetic algorithm permitting one to reconstruct the physical and optical characteristics of aerosol formations simultaneously.

Optical location equation for a super-Gaussian fan ladar

A new modification of the optical location equation is proposed that takes into account the specific features of super-Gaussian fan rays with high homogeneity and, correspondingly, the higher efficiency in problems of remote sensing. A computer program is implemented that simulates the operation of a monostatic ladar in the scheme of transport monitoring.

Femtosecond pulse splitting effect in the linear transfer regime

The parametric boundaries and physical mechanism of the origination of the femtosecond laser pulse splitting effect in a strongly scattering medium are ascertained on the basis of a Monte Carlo numerical solution of a nonstationary transfer equation. It is shown that the splitting effect resulting in a bimodal configuration of a pulse envelope is pronounced in a limited range of values of the scattering coefficient of the disperse medium and the anisotropy factor of the phase scattering function. The effect has been registered at pulses of less than 800 fs in length; the geometrical conditions of the signal recording are of essential importance. Under the optimal choice of parameters, the time configuration of the computed signals is in good qualitative agreement with the well-known experimental data. The accounting for the fine time structure of a transmitted signal and the multiparameter dependence of the expected effect require a certain modification of the local statistical modeling algorithms given in the Appendix.