The basic observables of an imaging interferometer by aperture synthesis are the complex visibilities. Under some conditions, they can be simulated with reference to the Van Cittert-Zernike theorem. However, owing to the underlying assumptions some important effects that may alter them cannot be taken into account. This paper is devoted to the numerical simulation of complex visibilities with very few assumptions. The emission is modelled with random short wave trains. Each wave is transported to the antennae, transmitted to the receivers and the corresponding signals are cross-correlated. From emission to correlation, perturbating effects can be introduced. However, owing to the amount of calculations to be performed, massive parallel architectures like that found in GPU are required. To illustrate this modelling, numerical simulations are carried out in the L-band in reference to the SMOS-next project led by the french space agency. The results are discussed and compared with the estimates provided by the Van Cittert-Zernike theorem.
Since it's launch, the ESA's Soil Moisture and Ocean Salinity (SMOS) satellite, is delivering new data from its LBand
1.4Ghz 2D interferometer [1]. The observations from SMOS are used to retrieve soil moisture in the first
centimeters and ocean salinity at the surface of the water. The observations are multi-angular with a 3 days maximum
revisit time. The spatial resolution of SMOS data is 40km.
In this paper we present on event detection algorithm implemented at CATDS (Centre Aval de Traitement des
Données SMOS) the CNES level 3 and level 4 SMOS enter. This algorithm is a three stage change detection
algorithm. At stage one the possibility/probability of occurrence of the event is evaluated. This is done via spatiotemporal
constraints maps. These maps are obtained from the analysis of NSIDC's freezing index products over the
last century. Climate data from ancillary files are tested will taking into consideration the uncertainty of the data.
Some selected retrieved variables are also tested. At stage two a time series analysis is applied. In the current version
of the algorithm a direct change detection algorithm is used. The tests make use of available variables of polarization
index, retrieved soil moisture...Finally at stage three a simple fuzzy logic approach is used to decide if the event
occurred. This approaches takes into consideration the separation time of the data. Ascending and descending orbits
are taken into consideration. In this study freezing detection is presented over central CONUS. The temporal and
angular signature of SMOS will be presented. Comparison is done with the SCAN network
The Soil Moisture and Ocean Salinity (SMOS) satellite is a 2D interferometer in L-band (1.4 GHz). Over land, it enables
to probe the earth surface emissivity related to soil moisture in the first centimeters of the soil, with an aimed accuracy
better than 4m3.m-3 and an average spatial resolution of 40km. The European Space Agency's (ESA) ground segment
provides half-orbit soil moisture products at level 2. The Centre National d'Etudes Spatiales (CNES) in France has
developed the CATDS (Centre Aval de Traitement des Données SMOS) ground segment in order to produce global
maps, known as level 3 and 4 products. Over land, the algorithm is based on the level 2 soil moisture ESA's prototype.
The major enhancement of the CATDS concerns the use of multi-orbit retrieval. The level 3 Soil moisture (SM) products
are global maps of soil moisture, and other geophysical products (vegetation optical thickness, albedo, soil dielectric
constant or surface temperature). For a particular point, the revisit time is between 1 and 3 days, and the entire Earth's
surface is covered by SMOS field of view in 3 days. Level 3 SM products are available over different time periods. First,
a 1 day global product is generated for each day. Then, 1 day global maps are aggregated in 3-day global products, 10-
day and monthly products.
In this paper, we propose two approaches to achieve calibration of the SPOT5 satellite, both based on the use of ground-based measurements achieved with a CIMEL sun-photometer. These approaches present the originality not to require any hypothesis on the aerosol model, on the contrary of the standard SPOT5 calibration. The principle of one of them relies indeed on the inversion of the aerosol phase function - thus atmospheric - from the sky diffusion measurements in the principal plane. The radiance-based method, fully described in Santer and Martiny (2003), allows the retrieval of the phase function with an accuracy of less than 1% using an iterative mode. We use such phase function, optical thickness and surface reflectance as inputs of a radiative-transfer-code for computations of SPOT5 top-of-atmosphere radiances. A second approach, inspired by Biggar et al. (1990), relies more directly on the sky and surface radiances measured by the CIMEL instrument. In this paper, we remind the principles of the two methods and the radiance-based method is applied as an example on 20 July, 2002. Discrepancies up to 11% are found out with the standard calibration coefficients. To conclude on the efficiency of the SPOT5 calibration methods, we recommend applying them to a huge and adapted dataset, spread on a longer period. Moreover, if the methods are accurate at 2-3%, we know that they are weakly sensitive to the radiance calibration of the sun-photometers. Standard calibration methods using integrating spheres do not give satisfactory results especially at short wavelengths (accuracy up to 10%). We present thus in the first part of the paper in-situ radiance calibration methods, based on the Rayleigh scattering knowledge and we show up that these methods lead to an improvement of the accuracy of 5%. The study is conducted over the inland site of La Crau, South of France.
SPOT5, the fifth satellite of the SPOT remote sensing satellite family was successfully launched on the 4th of May 2002. SPOT5 is designed to ensure continuity of data acquisition and space image services but also to provide users with advanced products. It flies two identical cameras named HRG (High Resolution Geometry) providing a 2.5 m and a 5 m resolution in a panchromatic mode and a 10 m resolution in a multi-spectral mode, still keeping a 60-km ground field. Stereo application is part two of the SPOT5 mission; the satellite flies a specific High Resolution Stereo instrument (HRS) made up of two telescopes allowing a 20° fore view and a 20° aft view over a 120-km swath, sampling the landscape every 5m. VEGETATION2, a wide field of view imaging radiometer complements the mission thanks to its daily coverage of the earth. The paper presents the mission, the commissioning phase that followed the satellite launch, the assessment of the image quality and the first calibration results.
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.
In the characterization of a space-borne wide field-of-view sensor, like Végétation, the multi-angular calibration is strongly complementary to the absolute calibration. It is defined as the process of estimating the sensitivity variations at different points of the Végétation wide field-of-view. This effect has to be integrated in the data processing. Pre-flight measurements were performed before launch, but because of heavy irradiations and aging of the different part of the sensor, it is necessary after launch to check and/or adjust the multi-angular calibration coefficients, gp. For this, the gp coefficients were split into three terms which required different methods: i/ first, the low-frequency term (gpLF) which refer to variation of the optic transmission which slightly decreases when viewing angle increases. The gpLF were verified using acquisitions over 20 desert sites for which TOA reflectances are accurately characterized (from ground measurements and POLDER/ADEOS-1 measurements). No in-flight variation of the gpLF were detected. ii/ second, the high-frequency term (gpHF) which refer to variation of the sensitivity of the elementary detectors. The gpHF were verified statistically using acquisitions over the Antarctica site and were accurately checked for the 4 spectral bands. ii/ third, the medium-frequency term (gpMF) which refer to various kinds of variation (optics, detectors...). The gpMF were verified during the 9pJpWDWLRQ like using the on-board calibration device (lamp profiles) and some small variations were identified (< 0.5% for B0, B2, B3 and ~1% for MIR). This aspect is still under investigation using acquisitions over Antarctica.
The present study is part of an investigation aimed at optimizing the use of desertic sites for absolute or relative calibration of satellite visible sensors. This effort includes characterization of the surface, gathering of climatology or atmospheric data sets, ground- and air- based measurements as well as result of calibration of various sensors over these sites. All these measurements and estimates are stored in a repository and made available to various methods for calibration. Post-launch degradation and relative sensitivity of various sensor have been estimated using north african desertic sites as radiometrically stable targets. The selected area have first been characterize in terms of bidirectional and spectral reflectances by making use of POLDER capabilities, then to cross-calibrate SeaWifs, VEGETATION on-board SPOT4 and AVHRR on-board NOAA-14 by reference to POLDER. Results are compared with absolute and relative calibration issued from other sources. Extensive period of time are spanned to assess the ability of this method to monitor long term trends in sensor evolutions. Results of this cross calibration will be presented. The method developed for this study will be presented as well, in order to make it applicable to other sensor. A sensitivity study has also been realized, considering synthetic data, allowing to evalute the main contributions to the error budget. The need for aerosol optical thickness is then evidenced, and will lead to the set up of a sun photometer on one of the selected sites in 1999.
An algorithm based on the Monte Carlo principle is developed to solve the radiative transfer problem in the reflective domain of the solar spectrum and is used to precisely evaluate ground irradiance on a rugged terrain. This method allows to simulate paths of photons inside the earth- atmosphere system without any assumption and calculate the different identified irradiance components and particularly those coming from environment. To establish the relative contribution of each of these terms, several typical relief and atmosphere configurations are considered. In a first step, two ground types simulations assuming lambertian reflectances are computed. Over vegetation-covered hills in the near IR, in the portion badly exposed to the direct solar beam, the environment irradiance contributes more than 20 percent of the total signal received at ground level. When severe slopes and higher reflectance values are considered, this contribution can exceed 60 percent in shadowed areas. These simulations demonstrate the necessity to take into account the high order terms when the region of interest presents important slopes and/or high reflectance ground. the case of non-lambertian reflectances is also dealt and it is shown that in the present configuration lambertian reflectances can be assumed to calculate the environment terms without significant errors on total irradiance, even in the shadow.
Improving the ground resolution of SPOT 5 compared with SPOT 4 involves multiplying the data rate by 4. This made it necessary to seek a new image compression algorithm able to significantly increase the compression ratio while complying with the image quality requirements of SPOT users. We finally selected a DCT based algorithm embedded in a regulation loop in order to obtain a constant rate at the compressor output. This algorithm was first tested using simulated images. Quantitative and qualitative analyses were carried out at different development stages. Finally, a wide range of images chosen from the SPOT image database was used for validation purpose. This led us to propose several optimizations which have now been thoroughly tested. The result is an almost lossless compression algorithm, which will be used on both SPOT5 and HELIOS II, the French space agency's forthcoming Earth observation missions.
In this paper, we address the problem of lossless and nearly- lossless multispectral compression of remote-sensing data acquired using SPOT satellites. Lossless compression algorithms classically have two stages: Transformation of the available data, and coding. The purpose of the first stage is to express the data as uncorrelated data in an optimal way. In the second stage, coding is performed by means of an arithmetic coder. In this paper, we discuss two well-known approaches for spatial as well as multispectral compression of SPOT images: (1) The efficiency of several predictive techniques (MAP, CALIC, 3D predictors), are compared, and the advantages of 2D versus 3D error feedback and context modeling are examinated; (2) The use of wavelet transforms for lossless multispectral compression are discussed. Then, applications of the above mentioned methods for quincunx sampling are evaluated. Lastly, some results, on how predictive and wavelet techniques behave when nearly-lossless compression is needed, are given.
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.
Calibration of optical sensors onboard earth observation satellites has been a major issue for several years. A collection of techniques has been developed involving modelization, surface or airplane based measurements of surface and atmosphere characteristics. The present study has the following objectives: conceive and develop a repository for all available data sets related to optical sensor calibration, including selection of commonly used sites, characteristics of the surface, climatology of the atmosphere, ground- to air-based measurements as well as results of calibration of various sensors over these sites. The main goal is to unify the use of these sites to make inter comparison of results easier and the calibration of forthcoming sensors more accurate at little extra expenses. Conception of the database and its environment will identify the type of data to gather, the format to use, the updating frequency, as well as the theoretical background necessary to the use of these data. For instance, information will be given about spectral behavior of the surface or about how to make measurements at various resolution easy to compare.
In this paper, we address the problem of lossless multispectral compression of remote-sensing data acquired using SPOT satellites. Compression algorithms have classically two stages: a transformation of the available data and coding. In the first stage, the aim is to express the spectral data as uncorrelated data in an optimal way. In the second stage, the coding is performed via the use of either a Rice or an arithmetic coding. In the first part of this paper, we discuss two well-known schemes, namely predictive technique and S + P transform, for the spatial decorrelation of multispectral SPOT images. Obviously, using only spatial properties is not optimal. However, few works have been carried out to address simultaneously the three intrinsic dimensions of multispectral images. In order to overcome this limitation, we have developed a predictive model based on three 3D-predictors. Compression ratios obtained are presented and discussed. In particular, there is a significant improvement in the compression ratios with respect to lossless compression methods based on spatial decorrelation method.
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