Xavier Briottet

Monte Carlo approach for solving the radiative transfer equation over mountainous and heterogeneous areas

An algorithm based on the Monte Carlo method is developed to solve the radiative transfer equation in the reflective domain (0.4-4 microm) of the solar spectrum over rugged terrain. This algorithm takes into account relief, spatial heterogeneity, and ground bidirectional reflectance. The method permits the computation of irradiance components at ground level and radiance terms reaching an airborne or satelliteborne sensor. The Monte Carlo method consists of statistically simulating the paths of photons inside the Earth-atmosphere system to reproduce physical phenomena while introducing neither analytical modeling nor assumption. The potentialities of the code are then depicted over different types of landscape, including a seashore, a desert region, and a steep mountainous valley.

Radiative transfer solution for rugged and heterogeneous scene observations

A physical algorithm is developed to solve the radiative transfer problem in the solar reflective spectral domain. This new code, Advanced Modeling of the Atmospheric Radiative Transfer for Inhomogeneous Surfaces (AMARTIS), takes into account the relief, the spatial heterogeneity, and the bidirectional reflectances of ground surfaces. The resolution method consists of first identifying the irradiance and radiance components at ground and sensor levels and then modeling these components separately, the rationale being to find the optimal trade off between accuracy and computation times. The validity of the various assumptions introduced in the AMARTIS model are checked through comparisons with a reference Monte Carlo radiative transfer code for various ground scenes: flat ground with two surface types, a linear sand dune landscape, and an extreme mountainous configuration. The results show a divergence of less than 2% between the AMARTIS code and the Monte Carlo reference code for the total signals received at satellite level. In particular, it is demonstrated that the environmental and topographic effects are properly assessed by the AMARTIS model even for situations in which the effects become dominant.

Comparison of measured and modeled BRDF of natural targets

The Bidirectional Reflectance Distribution Function (BRDF) plays a major role to evaluate or simulate the signatures of natural and artificial targets in the solar spectrum. A goniometer covering a large spectral and directional domain has been recently developed by the ONERA/DOTA. It was designed to allow both laboratory and outside measurements. The spectral domain ranges from 0.40 to 0.95 micrometer, with a resolution of 3 nm. The geometrical domain ranges 0 - 60 degrees for the zenith angle of the source and the sensor, and 0 - 180 degrees for the relative azimuth between the source and the sensor. The maximum target size for nadir measurements is 22 cm. The spatial target irradiance non-uniformity has been evaluated and then used to correct the raw measurements. BRDF measurements are calibrated thanks to a spectralon reference panel. Some BRDF measurements performed on sand and short grass and are presented here. Eight bidirectional models among the most popular models found in the literature have been tested on these measured data set. A code fitting the model parameters to the measured BRDF data has been developed. The comparative evaluation of the model performances is carried out, versus different criteria (root mean square error, root mean square relative error, correlation diagram . . .). The robustness of the models is evaluated with respect to the number of BRDF measurements, noise and interpolation.

Calibration of SPOT4 HRVIR and Vegetation cameras over Rayleigh scattering

The Rayleigh scattering over a clear ocean is a target which radiance is very well modeled and which enables to calibrate the short wavelengths of remote sensing instruments. But the quality of the calibration strongly depends on the evaluation of the other contributors to the observed Top Of Atmosphere radiance i. e. aerosol scattering and reflection over the sea surface (water color, foam, glint...). However these contributors can be reduced by appropriate viewing conditions. This technique is used to calibrate B1 (051-0.59 µm) and B2 (0.61-0.68µm) channels of HRVIR camera, and B0 (0.4-0.5µm) and B2 channels of VEGETATION camera both of which are aboard SPOT4. This article presents the calibration results obtained during the satellite two years in orbit. The results are compared to: - pre-flight results (integrating sphere) - in-flight results. The in-flight results are provided by: - on board calibration system (lamp and sun sensor) - vicarious calibration over test sites (White Sands, La Crau) - calibration over stable deserts - calibration over the sun glint The analysis of the sensitivity of the calibration to the different parameters used to model the TOA radiance shows the accuracy of such a technique.

A nonlinear unmixing method in the infrared domain

This paper presents the physical principle of a new (to our knowledge) unmixing method to retrieve optical properties (reflectance and emissivity) and surface temperatures over a heterogeneous and a folded landscape using hyperspectral and multiangular airborne images acquired with high spatial resolution. In fact, over such a complex scene, the linear mixing model of the reflectance commonly used in the reflective domain is no longer valid in the IR range for the two following reasons: multiple reflections due to the three-dimensional (3D) structure and the radiative phenomenon introduced by the temperature by way of the black body law. Thus, to solve this nonlinear unmixing problem, a new physical model of aggregation is used. Our model requires as inputs knowledge of the 3D scene structure and the spatial contribution of each material in the scene. Each elementary scene element is characterized by its optical properties, and its temperature, spectral, and multiangular acquisitions are required. This paper focuses only on the theoretical feasibility of such a method. In addition, an analysis is conducted evaluating the impact of the misregistration between the radiometric image and its digital terrain model, estimating a threshold of the relative importance of every elementary material to retrieve its corresponding optical properties and temperature. The results show that the 3D geometry must be accurately known (accuracy of 1 m for a spatial resolution of 20 m), and the relative contribution of material in the mixed area must be above 15% to retrieve its surface temperature with an accuracy better than 1 K. So, this method is applied on three different landscapes (heterogeneous flat surface, V shape, and urban canyon), and the results exhibit performances better than 1% for optical properties and 1 K for surface temperatures.

Remote sensing of aerosol plumes: a semianalytical model.

A semianalytical model, named APOM (aerosol plume optical model) and predicting the radiative effects of aerosol plumes in the spectral range [0.4,2.5 microm], is presented in the case of nadir viewing. It is devoted to the analysis of plumes arising from single strong emission events (high optical depths) such as fires or industrial discharges. The scene is represented by a standard atmosphere (molecules and natural aerosols) on which a plume layer is added at the bottom. The estimated at-sensor reflectance depends on the atmosphere without plume, the solar zenith angle, the plume optical properties (optical depth, single-scattering albedo, and asymmetry parameter), the ground reflectance, and the wavelength. Its mathematical expression as well as its numerical coefficients are derived from MODTRAN4 radiative transfer simulations. The DISORT option is used with 16 fluxes to provide a sufficiently accurate calculation of multiple scattering effects that are important for dense smokes. Model accuracy is assessed by using a set of simulations performed in the case of biomass burning and industrial plumes. APOM proves to be accurate and robust for solar zenith angles between 0 degrees and 60 degrees whatever the sensor altitude, the standard atmosphere, for plume phase functions defined from urban and rural models, and for plume locations that extend from the ground to a height below 3 km. The modeling errors in the at-sensor reflectance are on average below 0.002. They can reach values of 0.01 but correspond to low relative errors then (below 3% on average). This model can be used for forward modeling (quick simulations of multi/hyperspectral images and help in sensor design) as well as for the retrieval of the plume optical properties from remotely sensed images.

POLDER multiangular calibration using desert sites: method and performances

The multiangular calibration is used to estimate the sensitivity changes in the different points of the wide field of view of an optical instrument equipped with linear or array detectors. The baseline method consists in having the instrument looking at a spatially uniform landscape. For a wide field of view instrument, continuous uniform landscape does not exist, so we propose a new method using several desert sites to simulate a spatially known landscape. Desert areas are already good candidates for the assessment of multitemporal calibration of optical satellite sensors. This requires that the sites be well characterized in terms of directional variations of their top of atmosphere reflectances, to account for variations in the solar or viewing configurations between each measurement. A ground campaign has been done to evaluate the bidirectional reflectances of different sites which are then used as reference. POLDER instrument is the first instrument using these references for the multiangular calibration. First, this paper describes the multiangular calibration method used on POLDER based on the knowledge of these desert sites. The site selection criteria and the method developed to localize these desert sites are remembered. Then the results are presented in different spectral bands and the performances of this calibration estimated.

Sensor radiance physical model for rugged heterogeneous surfaces in the 3–14 μm region.

We present a physical model describing the radiance acquired by an infrared sensor over a rugged heterogeneous surface. This model predicts the radiance seen over complex landscapes like urban areas and provides an accurate analysis of the signal, as each component is available at ground and sensor level. Plus, it allows data comparison from different instruments. Two representative cases (natural and urban) are analysed to show the composition and the construction of the sensor signal and to highlight the importance of having a 3D model, especially for rugged surfaces where environment weights in the overall spectral domain.

Directional effect on change of spatial scale over heterogeneous surface in thermal infrared remote sensing

The issue of deriving cross-scale aggregation rules has been heavily investigated during the past two decades. The widely used approach consists of formulating grid-scale surface fluxes using the same equations that govern the patch-scale behavior but whose arguments are the aggregate expressions of those at the patch-scale. Such approach has been used in the past derive area-averaged or effective radiative surface temperature as it might be observed using low spatial resolution satellite data. The problem however is such satellite data exhibits large directional effect and none the past studies have addressed this issue. The present work tackles this issue of the combined effects of surface heterogeneity and view angle variations on surface temperature measurements. The directional effects are modeled on surfaces having a known heterogeneity. Then, the angular properties of local surfaces, assumed homogeneous, are calculated according a multiple scattering model. By applying the principle of aggregation, the equivalent angular radiance of the whole heterogeneous scene is then defined. This made it possible to show that this radiance is particularly sensitive to the directional effects, in particular when the spatial variation of surface temperature is significant and when there is a vegetation component in the heterogeneous land surface. The structure of the vegetation component is also a significant factor of directional effect on equivalent angular radiance.

Assimilation of satellite data over the Sahara desert for intercalibration of optical satellite sensors

About twenty Saharian desert regions have been selected a few years ago in order to carry out in-flight calibration of the different instruments operating in the visible and near- infrared spectral domain. Since then, CNES has collected an important number of measurements acquired by these instruments of interest (SPOT, AVHRR, SeaWiFS, Polder, Vegetation, MODIS, MISR) over the selected desert areas (SADE database). The present work fits into a global assimilation approach which aims to improve both the characterization of the calibration sites and the cross- calibration of optical satellite sensors. This work is particularly devoted to the spectral characterization of the selected site using the SADE database. The method is based on the use of a spectral model of ground surface reflectance at global scale. It is assumed that this model can be derived from laboratory reflectance measurement (i.e. Small scale measurement). Then, instead of reversing the top of atmosphere measurement into ground reflectance, the ground reflectance model is transported at the top of atmosphere for comparison to available measurement, and the parameters adjustment is done at this level. A top of atmosphere simulated reflectance dataset (corresponding to various usual multispectral sensors) is used in a first step to assess for the relevancy of the proposed method.