Operational MERIS (MEdium Resolution Imaging Spectrometer) level-2 processing uses auxiliary data generated by two radiative transfer tools. These two codes simulate upwelling radiances within a coupled 'Atmosphere-Ocean' system, using different approaches based on the matrix-operator method (MOMO) and the successive orders (SO) technique. Intervalidation of these two radiative transfer codes was performed in order to implement them in the MERIS level-2 processing. MOMO and SO simulations were then conducted on a set of representative test cases. Results stressed both for all test cases good agreements were observed. The scattering processes are retrieved within a few tenths of a percent. Nevertheless, some substantial discrepancies occurred if the polarization is not taken into account mainly in the Rayleigh scattering computations. A preliminary study indicates that the impact of the code inaccuracy in the water leaving radiances retrieval (a level-2 MERIS product) is large, up to 50% in relative difference. Applying the OC2 algorithm, the effect on the retrieval chlorophyll concentration is less than 10%.
Operational MERIS (MEdium Resolution Imaging Spectrometer) level 2 processing uses auxiliary data generated by two radiative transfer tools. These two codes simulate upwelling radiances within a coupled 'Atmosphere Land' system, using different approaches based on the matrix operator method (FUB), the discrete ordinate method and the successive orders technique (LISE). Intervalidation of these two radiative transfer tools was performed in order to implement them in the MERIS level 2 processing.. An extensive exercise was conducted for cases without gaseous absorption. The scattering processes both by the molecules and the aerosols were retrieved within few tenths of a percent. Nevertheless, some substantial discrepancies occurred if the polarization is not taken into account mainly in the Rayleigh scattering computations. Errors on the aerosol optical depth reach up to 30 percent in some geometries as observed in the SeaWiFS (Sea viewing Wide Field of view Sensor) images. The parameterization of the water vapor absorption defined for each of these two codes leads to a well agreement not only for the MERIS bands with residual absorption but also in the MERIS band centred at 900nm which is used for the water vapor retrieval. As for the strong oxygen absorption at the 760.625 nm MERIS wavelength, its parameterization varies between the two codes. Nevertheless, the systematic biases in the two codes will be removed thanks to the use of a differential method between two MERIS adjacent bands. For the oxygen absorption at 760.625 nm, a more exhaustive study need to be achieved.
On January 13th 2001, a very strong earthquake struck El-Salvador, causing almost 1000 deaths and huge destruction, leaving more than one million people homeless. As support to the rescue teams, a project was initiated to provide up-to date maps and to identify damages to housing and infrastructures, covering the whole country. Based on the analysis of SPOT Panchromatic satellite imagery, updated maps were delivered to the rescue teams within 72 hours after the earthquake. In addition, during the 10 days following the earthquake, high resolution mapping of the damages was carried out in cooperation and coordination with rescue teams and relief organizations. Some areas of particular interest were even processed and damage maps delivered through the Internet, three hours after the request. For the first time in the history of spaceborne Earth observation, identification and evaluation of the damages were delivered on-site, in real-time (during the interventions), to local authorities, rescue teams and humanitarian organizations. In this operation, operating 24 hours a day and technical ability were the keys for success and contributed to saving lives.
KEYWORDS: Speckle, Image filtering, Synthetic aperture radar, Control systems design, Soil science, Digital filtering, Image fusion, Control systems, Spatial resolution, Data fusion
Two new Bayesian Maximum A Posterior vector speckle filters are developed for multi-channel detected synthetic aperture radar (SAR) images. These filters incorporate statistical descriptions of the scene and of the speckle in multi- channel SAR images. These filters incorporate statistical descriptions of the scene and of the speckle in multi- channel SAR images. These models account for the scene and system effects which result in the presence of a certain amount of correlation between the different channels. In order to account for the effects due to the spatial correlation of both the speckle and the scene in SAR images, estimators originating from the local autocorrelation functions are incorporated to these filters, to refine the evaluation of the non-stationary first order local statistics, to improve the resolution of the scene textural properties, and to preserve the useful spatial resolution in the speckle filtered image. Since the new established Bayesian speckle filters present the structure of control system, their application is the first processing step of application-oriented control system designed to exploit the synergy of SAR sensors. We present here such a control system, designed to retrieve soil roughness and soil moisture through Bayesian ERS/RADARSAT data such a control system, designed to retrieve soil roughness and soil moisture through Bayesian ERS/RADARSAT data fusion. Results obtained on a couple of ERS PRI and RADARSAT standard beam SAR images show that the new speckle filters present convincing performances for speckle reduction, for texture preservation and for small scene objects detection. The retrieval of soil roughness and soil moisture through Bayesian data fusion of ERS and RADARSAT data provides also valuable results for the monitoring of agriculture and environment.
Two new Bayesian Maximum A Posteriori (MAP) vector speckle filters are developed for multi-channel detected SAR images. These filters incorporate statistical descriptions of the scene and of the speckle in multi-channel SAR images. These models account for the scene and system effects which result in the presence of a certain amount of correlation between the different channels. In order to account for the effects due to the spatial correlation of both the speckle and the scene in SAR images, estimators originating from the local autocorrelation functions are incorporated to these filters, to refine the evaluation of the non-stationary first order local statistics, as well as to improve the restoration of the scene textural properties and to preserve the useful spatial resolution in the speckle filtered image. Results obtained, first on 3-look spaceborne ERS PRI multi-temporal images, then on a couple of ERS PRI and RADARSAT standard beam SAR images illustrate the performance of these estimators for different SAR combinations. These results show that these filters present convincing performances for speckle reduction, as well as for texture preservation and for small and/or thin scene objects detection. Finally, since the new established Bayesian speckle filters present the structure of control systems, promising perspectives are presented for the development of application oriented processing chains for multi-channel SAR images, where the speckle filtering operation will be the first processing step.
The DART (discrete anisotropic radiative transfer) model simulates radiative transfer in heterogeneous 3-D scenes; here, a forest plantation. Similarly to Kimes model, the scene is divided into a rectangular cell matrix, i.e., a building block for simulating larger scenes. Cells are parallelipipedic. The scene encompasses different landscape features (i.e., trees with leaves and trunks, grass, water, and soil) with specific optical (reflectance, transmittance) and structural (LAI, LAD) characteristics. Radiation directions are subdivided into contiguous sectors with possibly uneven spacing. Topography, hot spot, and multiple interactions (scattering, attenuation) within cells are modeled. Two major steps are distinguished: (1) Illumination of cells by direct sun radiation. Actual locations of within cell scattering are determined for optimizing scattering computation. (2) Interception and scattering of previously scattered radiation. Diffuse atmospheric radiation is input at this level. Multiple scattering is represented with a spherical harmonic decomposition, for reducing data volume. The model iterates on step 2 for all cells, and stops with the energetic equilibrium. This model predicts the bi-directional reflectance factors of 3D canopies, with each scene component contribution; it was successfully tested with homogeneous covers. It gives also the radiation regime with canopies, and consequently some information about volume distribution of photosynthesis rates and primary production.
Ecosystem modeling requires information about canopy chemistry. This is usually obtained through chemical analysis and laboratory spectrometric measurements. the potential of spectrometric remote sensing was investigated with an ISM (Imaging SpectroMeter) airborne campaign (1993, Les Landes, France). This spectrometer operates in the 800-3200 nm range. The study area consists of a mosaic of homogeneous parcels of maritime pines with a wide variety of ages (2-48 years). During the airborne campaign, 21 parcels were sampled and chemically analyzed for lignin, cellulose, and nitrogen. Samples were spectrally analyzed in laboratory with a Technicon InfraAlyser 450 and a NIR 6500 system. Correlations between the similar bands of the two spectrometers were surprisingly low. Predictive equations of nitrogen, lignin, and cellulose were obtained by stepwise regression analysis on spectral data. The stability of predictive relationships from laboratory to remote sensing level was especially analyzed. Technicon-derived predictive equations used with ISM data led to encouraging results for nitrogen and cellulose. Lignin could not be predicted NIR 6500-derived predictive equations were also tested with raw ISM data and data processed to minimize atmospheric effects. Minimization of atmospheric effects improved results for nitrogen and lignin.
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