The radiance collected by each spectral filter outside of its expected bandwidth introduce errors on the derived products, this is the Out of Band contribution which needs to be minimized to increase the accuracy of the recovered signal. Three methods are proposed to mitigate this spurious signal for a push broom multi spectral camera, without additional information from external sources.

A new methodology is presented to identify the spectral response of multi-band remote sensing optical camera. The proposed set-up is based in the system theory where the input-output relationship allows to characterize the internal parameters as it is the Absolute Spectral Response (ASR). The new approach allows one to minimize the instrumental set-up as well the time to develop the identification of the ASR.

A new algorithm is proposed to obtain the Sea Surface Temperature (SST) from a satellite instrument. The characteristics of the camera enable observing the same ground pixel through multiple view angles. The method errors as well as a way to smooth the jitter due to the observation errors are presented.

The SABIA-Mar satellite mission, developed by CONAE, aims to provide valuable information and products for studying marine ecosystems, the carbon cycle, coastal dynamics, and marine habitats. The SABIA-Mar main cameras (measuring from visible to short wave infra-red) have a nonconventional design, since each spectral band has different viewing angles, which raises a challenge for the application of traditional atmospheric correction (AC) schemes. This work presents a preliminary analysis, based on simulated data sets, of uncertainties in the AC algorithm proposed for SABIA-Mar to retrieve water reflectance. This algorithm, a version of the standard AC scheme, was applied to SABIA-Mar angular and spectral characteristics, and the results compared to those obtained assuming the same viewing geometry for all the spectral bands. Performance is slightly degraded for the SABIA-Mar geometrical configuration, but the statistical results meet the goals of the SABIA-Mar mission and the requirements for ocean color applications.

The determination of the Sea Surface Temperature (SST), as well as the Land Surface Temperature (LST), is typically achieved through the algorithm called Split Windows (SW). This method is compatible with detectors whose Noise Equivalent Delta Temperature (NEDT) is on the order of 0.1 °K or less. The method increases the observation error by a factor of 4 or 5 on the SST determination. The NEDT of un-cooled micro-bolometers detectors (used in small and medium satellites) is in the range of 0.5°K to 1.5°K. To achieve a SST error less than 0.7°K it is necessary to search for other algorithms. In [1] an alternative method is presented, but in this work a new algorithm is presented, based on the theory of perturbations and stochastic process, compatible with the new generation of areal micro-bolometer detector, that allows one to meet the accuracy requirement.

The determination of the Sea Surface Temperature (SST) has many applications in areas such as marine biology, environment preservation, oil spill detection, the fishery industry, among others. To achieve these objectives (or at least some of them), the required SST accuracy should be below 0.7° C (at least). The power generation is a limiting factor on small satellites, that precludes the use of cooled detectors which easily can fulfill the required temperature accuracy. Usually in thermal infrared cameras, the SST is determined by variations of a method based on two narrow bands located away from the atmospheric absorption windows. These bands are generally centered at 11 µm and 12 µm, with a bandwidth of 1 µm. This method is named Split Windows (SW) algorithm. In case of having uncooled microbolometers as the detector, which is common for small missions, an expensive on-ground calibration is needed to accomplish the required SST accuracy. The present report shows an improvement to the traditional SW method, in order to substantially reduce the total error and set the SST accuracy inside the required limits.

Sun glint is an important issue in satellite ocean-color remote sensing since the glint signal may dominate other radiance sources, in particular the signal backscattered by the water body. The presence of Sun glint in the camera field-of-view generally prevents the generation of ocean color products. Ocean color misions attempt to minimize the direct reflection of the Sun by selecting the appropriate geometry of the camera line of sight. To deal with glinted areas, the first condition is to avoid detector saturation over those areas. In the SABIA-Mar mission this is achieved by having two integration times, the so-called short and long times. The short time assures no saturation over clouds and glinted areas while the longer time allows adequate signal-to-noise ratio over not contaminated areas. In this paper, we present a computational scheme to calculate the magnitude of the directional glint radiance reaching the detector. The scheme exploits the relative readings among spectral bands, some of them including the Sun glint and some of them not affected by glint because of the view angle. This difference feeds an algorithm to determine glint magnitude and its contribution to the detected signal in each band. The scheme is specialized for push-broom camera geometry and the SABIA-Mar mission is used as example, but it can also be applied to other cases.

After ADEOS-2 launch on 14 December 2002, GLI ocean group has investigated vicarious calibration, algorithm improvement and product validation, and released version-1 products on 24 December 2003. Although we lost ADEOS-2/GLI on 24 October 2003, we continue product evaluation and algorithm revision toward the future product updates. For example, we are investigating absorptive aerosol correction and 250-m ocean color image processing. The absorptive aerosol correction is very important especially in the East Asia where is surrounded by the fast developing countries and influenced frequently by a kind of carbon aerosols. The 250-m products are made using GLI 250-m channels from blue to near-infrared, and enable to detect fine spatial structures in the coastal areas.

A methodology for water vapor retrieval over ocean, using a differential absorption technique from near-IR channels, is presented. Over ocean, surface reflectance is close to zero and aerosol scattering is used to estimate water vapor contents, from an accurate radiative transfer code to account for optical thickness and scale height of aerosols. This method has been applied to POLDER data and comparisons with ECMWF (European Centre for Medium-Range Weather Forecasts) data are presented over the Straits of Gibraltar.

The radiometric sensitivity of the POLarization and Directionality of the Earth's Reflectances (POLDER) instrument in the ocean color spectral bands (443, 490, and 565 nm) was checked vicariously by comparing top-of-atmosphere normalized radiances measured by the instrument with those computed for the same geometries using a radiative transfer model. In situ measurements of aerosol optical thickness and marine reflectance at the time of the satellite overpass were used as input to the model. The accuracy of the vicarious calibration coefficients was estimated to better than 3%. A large decrease in the POLDER instrument response was found in the blue, confirming the results previously obtained using alternative techniques.

An analysis of ocean color temperature scanner [(OCTS) on board the advanced earth observation satellite (ADEOS)] spectral radiance data was performed for retrieving global distributions of Angstrom factor and exponent, which represent the aerosol optical thickness at a reference wavelength (500 nm in the authors' study) and a spectral dependence of the optical thicknesses, respectively, over ocean. Determination of calibration constants for OCTS-received radiances and development of an efficient look-up table method for synthesizing the radiances are key issues for development of the present two-channel algorithm with use of channel 6 and 8 radiances of OCTS. This algorithm has been applied to Level-1B OCTS GAC data sets for producing three month (April, May, and June 1997) global distributions of Angstrom parameters. Geographical and seasonal distribution patterns of Angstrom parameters suggest that anthropogenic sulfate aerosols in mid-latitudes and biomass burning aerosols in the subtropical region are characterized by small particles having large Angstrom exponents, whereas mineral dust particles from subtropical arid regions are characterized by large particles having small Angstrom exponents. There was a fairly good agreement between satellite-retrieved values of Angstrom parameters and values obtained by sky radiometers located on coasts.

The international community, recognizing the importance of global ocean color observations in the global carbon cycle, has proposed or flown six global ocean color missions over the next decade: the Ocean Color and Temperature Sensor (OCTS), Sea-viewing Wide Field-of-view Sensor (SeaWiFs), Moderate Resolution Imaging Spectrometer-AM (MODIS-AM), Medium Resolution Imaging Spectrometer (MERIS), Global Imager (GLI), and MODIS-PM. Each of these missions contains the spectral band complement considered necessary to derive oceanic pigment concentrations (i.e., phytoplankton abundance). This paper assesses whether assembling and merging data from these missions can improve ocean coverage, since clouds and Sun glint prevent any single satellite from observing more than about 15% of the ocean surface in a single day, and whether new information about diel cycles of phytoplankton abundance is possible. Extensive numerical analysis, given the orbit and sensor characteristics of each mission, showed that merging data form three satellites can produce better ocean coverage in less time. Data from three satellites can improve coverage by 58% for a single day, including the obscuring effects of clouds and sun glint. Thus, observation of approximately 25% of the ocean can be provided, instead of only about 15-16% from a single satellite. After four days, approximately 62% of the ocean surface was observed, an increase from 43% observed by a single satellite. The addition of more satellites produced diminishing returns. Since the proposed missions have different orbits, the view the same location of the ocean at different times of day. This leads to the possibility of using data from the set of six missions to help understand diel phytoplankton dynamics.

The correspondence between the normalized difference vegetation index (NDVI) calculated from average reflectances, M/sub NDVI/, and NDVI integrated from individual NDVIs, I/sub NDVI/, by simulating AVHRR data from high spatial resolution SPOT 1 Haute Resolution Visible radiometer and Landsat Thematic Mapper data is analyzed. For the considered sites, located in tropical West Africa and temperate France, and the scales analyzed, 300-1000 m, a strong correlation exists between the two types of index. The relationship is almost perfectly linear, with a slope depending slightly on the variability of the vegetation cover. Effecting the scale change using M/sub NDVI/ instead of I/sub NDVI/ does not introduce significant errors.>