Multichannel Earth observation data have been available to the science community since the launch of ADEOS. To retrieve several geophysical parameters, not one, we need multiple-band observation. The ADEOS satellite carried eight instruments that covered bands from ultraviolet to microwave. We have begun to analyze the spectrally wide ADEOs data, or multiple- instrument data, to seek new methods to infer crucial geophysical parameters. Satellites observed data in the visible and near infrared bands comprise radiation from molecular scattering (Rayleigh scattering), aerosol scattering (Mie scattering), water vapor absorption, and surface reflection. The separation of components is an important goal of satellite remote sensing retrieval. In this paper, we introduce the ADEOS satellite, its instrumentation, and the ADEOS SYNERGISM dataset. We will discuss the characteristics of the radiance received by satellites and show interesting data and properties derived from the ADEOS SYNERGISM dataset. We will also discuss further separation of the components that constitute satellite observed data in the visible and near- infrared bands.

The issue of quantitatively remotely sensing the biological constituents of the global oceans is a complex challenge. The term 'remotely' is used here specifically to refer to on-orbit sensing. When compared with in situ sensing, on-orbit sensing is complicated by effects such as those due to sea state, the molecular and aerosol atmosphere and sunglint: each of which is variable spatially and temporally. If we remove the on- orbit restriction and sense at or near the sea surface we still encounter a number of complications including decisions on the suite of variables to be measured, the measurement protocols, calibration of instruments, spectral band selection, choice of algorithm(s), validation etc. If we add to these the case II water scenario, the question of measuring water properties and constituents becomes somewhat more difficult.

The presentation focuses on the peculiarity of Asian waters with respect to the atmospheric correction of the satellite ocean color data such as of Ocean Color and Temperature Scanner (OCTS). We first demonstrate the effect of highly turbid case 2 waters on the atmospheric correction via non- zero water reflectance in the near infrared region. The results of applying the OCTS standard correction scheme to typical Chinese coastal OCTS scenes reveal that a significant portion of the area is masked due to the negative water reflectance retrieved by the scheme, even using 765 nm and 865 nm bands instead of 670 and 865 nm pair to determine aerosol contribution. An optical model that relates suspended solid (SS) and chlorophyll-a (Chl-a) concentrations to the near infrared water reflectances was implemented into the atmospheric correction, together with a neural network that estimates Chl-a and SS concentrations. The new iterative scheme is applied to the Chinese coastal scenes and the results are assessed to be favorable. The paper then discuss the modeling of Asian dust aerosol in hope of establishing aerosol models that can be used for atmospheric correction. A set of models are designed with varying controlling parameters such as size distribution, vertical profile, and imaginary part of the refractive index. A series of radiative transfer simulation is conducted and the spectrum of the top-of- atmosphere radiance is compared to that of a Sea Wide Filed- of-view Scanner (SeaWiFS) data obtained under Asian dust event. The results of the comparison suggest that the Asian dust aerosol has unique spectral absorption feature at the blue region (in 412 nm band, i.e.).

Existing atmospheric correction algorithms for multi-channel remote sensing of ocean color from space were designed for retrieving water leaving radiances in the visible over clear deep ocean areas. The information about atmospheric aerosols is derived from channels between 0.66 and 0.87 micrometer, where the water leaving radiances are close to zero. The derived aerosol information is extrapolated back to the visible when retrieving water leaving radiances from remotely sensed data. For the turbid coastal environment, the water leaving radiances from the 0.66-micrometer channel may not be close to zero because of back scattering by suspended materials in the water. This channel may not be useful for deriving information on atmospheric aerosols. As a result, the algorithms developed for applications to clear ocean waters cannot be easily modified to retrieve water leaving radiances from remotely sensed data measured over the coastal environments. We have developed an atmospheric correction algorithm for hyperspectral remote sensing of ocean color with the near-future Coastal Ocean Imaging Spectrometer (COIS). The algorithm uses lookup tables generated with a vector radiative transfer code. Aerosol parameters are determined by a spectrum-matching technique utilizing channels located at wavelengths longer than 0.86 micrometer. The aerosol information is extracted back to the visible based on aerosol models during our retrieval of water leaving radiances. Quite reasonable results have been obtained when applying our algorithm to process hyperspectral imaging data acquired with an airborne imaging spectrometer.

The spectral reflectance of oceanic whitecaps in the visible and near infrared was investigated using high-altitude, 20 m resolution AVIRIS measurements off the Southern California coast. The whitecap effect on surface reflectance was expressed as a function of the difference between the reflectance of pixels contaminated by whitecaps and of adjacent pixels free of whitecaps. Whitecap reflectance was found to decrease substantially in the near infrared, by about 40% at 850 nm and 80% at 1,600 nm, in agreement with previous measurements in the coastal zone and the open ocean. The spectral dependence of whitecap reflectance appears to be fairly independent of environmental conditions, making it easy to take into account the resulting -- and significant -- effects in ocean color and aerosol remote sensing algorithms.

Two types of algorithm selected for ADEOS-II/GLI atmospheric correction for ocean applications were summarized. The standard algorithm, OTSK1a, is an extension from the OCTS algorithm (and also similar to current SeaWiFS/MODIS algorithm). The research algorithm, OTSK1b, is selected to validate OTSK1a. OTSK1b is a new approach for atmospheric correction by using multi-layered perceptrons (i.e. neural network) to model the transfer function between top-of- atmosphere GLI reflectances and above-surface marine reflectances. The performance of these two algorithms was tested with GLI synthetic dataset and MODIS data.

We intend to propose the effective procedure for aerosol retrieval for ocean color remote sensing. Ocean color sensors are designed to monitor the oceanic and atmospheric environments with near infrared (NIR) data as well as ocean color data. Aerosol properties such as optical thickness of aerosols. Angstrom exponent etc. are usually retrieved from reflectance observed in the NIR region based on one- or two- channel algorithm. In addition we found that polarization degree is useful to estimate such an optical constant of aerosols as refractive index, and polarized reflectance is especially available to retrieve the continental aerosols. It is of interest to mention that the aerosol retrieval is greatly improved once the observed quantities have been provided together with the sufficient directional information. Several algorithms for aerosol retrieval are examined and compared with each other using ocean color sensor data from CZCS to SeaWiFS.

NASA's Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) aims to measure global ocean color from space to within 5% to provide insights into fundamental ocean processes. SeaWiFS must be backed by comprehensive calibration and validation programs if the mission is to achieve this. In situ measurements of normalized water-leaving radiance (L_wn) made simultaneously with satellite measurements can complement on- orbit methods of tracking changes in the calibration of the satellite radiometer and allow end-to-end vicarious validation of the remotely-sensed data. A moored optical databuoy was developed at Plymouth Marine Laboratory, UK to measure L_wn in the western English Channel. Tests indicate that the buoy is capable of measuring spectral incident irradiance with less than 10% error and water-leaving radiance with less than 20% error; these errors are reduced by averaging and show no bias. There were 24 match-ups with good quality SeaWiFS data at the buoy site during the 10 months of deployment within the period May 1997 and September 1998. The differences between the buoy and SeaWiFS measurements of L_wn were found to be variable and often large. The root-mean-square (RMS) differences varied from 102% at 412 nm to 50% at 555 nm. The RMS differences in measurements of L_wn could be reduced to less than 18% by a combination of increasing the calibration coefficients of SeaWiFS by between 0.2 and 4.3% in the visible bands and by tuning the extrapolation of aerosol radiances from the near infra red to the visible wavelengths. These results imply that the monitoring of the absolute calibration of the SeaWiFS bands is imperfect and errors remain in the extrapolation of aerosol radiances for atmospheric correction.

The results of comparisons of chlorophyll (alpha) concentrations, measured using different methods in various regions of the Ocean, are presented. The data measured simultaneously by remote sensing (SeaWiFS, CZCS) and from the moving ship using of the laser induced fluorescence, spectrometer for measuring of the spectral distribution of the upwelling radiation and standard absorption method were analyzed.

Near-shore coastal waters are important for our quality of life, but near-shore environments are under continuous stress due to human activities and natural events. Also, data on some navigational charts are often decades old. Many do not reveal changes due to recent strong storms or coastal evolution. As a result, the doubtful bathymetric data can make coastal navigation dangerous. Methods and techniques are also needed to monitor the properties of near-shore waters as well as the condition of benthic ecosystems such a seagrass beds. Traditional ship-borne surveys are slow and expensive, and there is no need to remeasure all coastal areas as environmental change is in general a slow process. It is more important to find and flag the places where significant changes may have occurred and then focus field programs in those regions. One practical method may be to use satellite sensors, which have been proven very useful for quickly providing important environmental information over large areas. Satellite sensors for ocean studies use the relationship between the spectral signals received at the sensor and the contents below the sea surface to detect oceanic properties such as chlorophyll concentration. The use of passive spectral data for bathymetry was first demonstrated in the late 1960s (Polcyn and Sattinger 1969). Using several different approaches, reasonable results were obtained with limited spectral channels (Polcyn et al. 1970, Lyzenga 1985, Clark et al. 1987). All of these approaches require some important assumptions, however. These assumptions are not always valid. There is a strong need for a method to analytically and simultaneously derive bottom depth and albedo and the optical properties of the water column relying simply on remotely sensed data.

A method based on a four flux model has been developed for a more accurate estimation of multiple-substance concentrations in the water. The results estimated by real Landsat TM for the northern part of Tokyo Bay were in good agreements with the sea truth data, assuming that chlorophyll-(alpha) , suspended mineral, and dissolved organic matter exist in the area.

A model of particle absorption coefficients is presented as a function of chlorophyll concentration. The model has been derived from remote sensing reflectance and chlorophyll concentration of CalCOFI bio-optical data set, using a radiance model. Variance in absorption coefficient for a given chlorophyll concentration can be reduced by introducing site- dependent particle backscattering coefficients, average of which is assumed to follow Morel's backscattering model. With an empirical algorithm for estimating the absorption by dissolved organic matter, we separate the absorption by particles from the total absorption. Through a simple quality control, statistical regression gives the parameterization of particle absorption. By applying the derived model to a semi- analytical inversion algorithm, we demonstrate the proposed model could be used to retrieve in-water parameters such as chlorophyll concentration, absorption by colored dissolved organic matter and particle backscattering coefficients.

Hyperspectral imaging sensors greatly expand the potential of remote sensing to assess, map, and monitor marine coastal zones. Each pixel in a hyperspectral image contains an entire spectrum of information. As a result, hyperspectral image data can be processed in two very different ways: by image classification techniques, to produce mapped outputs of features in the image on a regional scale; and by use of spectral analysis of the spectral data embedded within each pixel of the image. The latter is particularly useful in marine coastal zones because of the spectral complexity of suspended as well as benthic features found in these environments. Spectral-based analysis of hyperspectral (AVIRIS) imagery was carried out to investigate a marine coastal zone of South Florida, USA. Florida Bay is a phytoplankton-rich estuary characterized by taxonomically distinct phytoplankton assemblages and extensive seagrass beds. End-member spectra were extracted from AVIRIS image data corresponding to ground-truth sample stations and well-known field sites. Spectral libraries were constructed from the AVIRIS end-member spectra and used to classify images using the Spectral Angle Mapper (SAM) algorithm, a spectral-based approach that compares the spectrum in each pixel of an image with each spectrum in a spectral library. Using this approach different phytoplankton assemblages containing diatoms, cyanobacteria, and green microalgae, as well as benthic community (seagrasses), were mapped.

Northern Sakhalin is a region of the intensive oil and gas transportation by oil-pipe lines. In July 2, 1997, the oil spill has happened at the oil-pipe line 'Okha-Komsomolsk-on- Amur.' Oil pollution spread over the basin of Tengi Rive (Amur estuary). The Tengi River is a spawning area for endemic and important commercial fish. There is a reserve on the river. Genus Oncorhynchus (pink and chum salmon) prevail in ichthyofauna. A satellite data analysis (NOAA-12, NOAA-14) was a success to accurate the oil distribution over the Amur estuary. As a result of the accident, more than 120 t of oil have been spilled. 26.3 km of the river area, more than 60 km of the Amur estuary coast and about 850 km² of its water area were polluted. In the basin of Tengi River about 58000 m² of spawning area were lost. The main damage (89%) was caused to the fry feeding near the coast. The loss of fish production has constituted about 1800 t. By species the damage was as follows: 53% -- pink salmon, 29% -- chum salmon, 11% -- masu salmon and 7% -- coho salmon.

The fluorescence lidar can positively distinguish the oil from the water or biological substances. A rugged system with real- time display mounted in a small airplane and on a ship could make significant aides for pollution response sites. This paper describes a compact lidar system which is suitable for rapid identification of oil slicks with a wider field of view. Functions of the proposed system were evaluated by airborne and shipborne tests. During a flight from an altitude of 1000 ft above the water surface, spots illuminated by the laser were acquired in an image with angular view of 18.2 degrees. Fluorescence data was interpreted in terms of substances referenced with the fluorescence characteristics measured with a streak scope. A GPS instrument was used to position data precisely, to map out a flight line.

Analysis of hyperspectral data has produced encouraging results in the discrimination of common and optically similar coral reef substrates such as healthy corals, bleached corals, sea grass, and algae-covered surfaces, but at the present time, such high spectral resolution data is unavailable from a satellite platform. If currently available satellite imagery is to be used to map and monitor changes in coral reef geographic extent and health, a quantitative procedure must be developed to discriminate healthy coral from other optically similar benthic substrates with coarse spectral resolution. The primary goal of this study is to evaluate the feasibility of using coarse spectral resolution data to map the geographic extent and monitor the changes in coral reef ecosystems. While previous studies have based analysis upon reflectance values extracted from images, an attempt is made here to discriminate common coral reef features using in situ spectral reflectance measurements with spectral resolution equivalent to SPOT HRV data. Results of a one-way analysis of variance suggest that the broad categories of in situ reflectance measurements (n equals 596) can be considered separate populations with respect to broadband reflectance characteristics.

We proposed a photosynthetically available radiation dependent primary productivity model. A vertical distribution of PAR is defined as an empirical equation of the chlorophyll-a concentration in the surface, which is observed by an ocean color sensor. A vertical distribution of chlorophyll-a concentration is defined as an empirical equation of the vertical distribution of PAR and the chlorophyll-a concentration in the surface. A vertical distribution of primary productivity is defined as an empirical equation of the vertical distribution of PAR and the temperature. We retrieved those empirical equations from the previous in-situ measurement. A primary productivity of the water column is given as an integration of those parameters along the water column. Results of primary productivity model, applied on a series of SeaWiFS data, showed a good agreement with in-situ observation.

We developed an algorithm to estimate primary production from ocean color satellite data, and estimated the global distribution of primary production with OCTS and SeaWiFS data. The VGPM is one of the simplest and most usable models for primary production estimation from satellite chlorophyll. We propose two-phytoplankton community model of primary production to improve the VGPM. In general, chlorophyll concentration tends to be proportional to phytoplankton cell size and phytoplankton productivity tends to be inversely proportional to cell size. Based on these facts, we improved P^B_opt(maximum carbon fixation rate within a water column), which is one of the most important parameters of the VGPM. We assume that the phytoplankton community is composed of large and small cell size phytoplankton and that there are limits to the biomass of small phytoplankton. Based on this hypothesis, we matched P^B_opt to the functions of sea surface temperature and sea surface chlorophyll concentration. The results indicate that small phytoplankton has higher productivity with higher temperature dependency. We estimated the global distribution of primary production using this modified VGPM. The global distribution of primary production is basically similar to that of chlorophyll concentration. The modified VGPM estimates lower productivity than original VGPM in high chlorophyll concentration areas, and conversely estimates higher productivity in low chlorophyll concentration areas. With total global primary production, the modified VGPM results are 12% lower than the original VGPM.

Objectives of this study are to apply the integrated chlorophyll estimation method to time-series satellite ocean color data and to examine the characteristics of the fishing ground formation and its marine environment for three kinds of fisheries, including purse seine fisheries, pole and line fisheries, and longline fisheries. The MCSST image and the chlorophyll image of ADEOS/OCTS from April to June 1997 were used for the water types classification using clustering method with non-supervisor. We defined water types to four categories of Kuroshio, Warm Water, Cold Water, Oyashio. Warmer water area (Kuroshio, Warm Water) and colder water area (Oyashio, Cold Water) might be clearly separated. Warm Water Area, however, has less separation rate of only 58 percent. On the other hand, Cold Water Area has relatively high separation rate of 83 percent. The comparison between the fishing catches and both SST and integrated Chlorophyll (alpha) was carried out to generate 3-D scattergrams for each fisheries. The relatively high part of longline fishing catch with over 200 fishes was formed on the range of SST 15 degrees Celsius - 25 degrees Celsius and the range of integrated chlorophyll (alpha) 60 - 150 mg/m². The relatively high part of pole and line fishing catch with over 10 ton was formed on the range of SST 12 degrees Celsius - 22 degrees Celsius and integrated chlorophyll (alpha) under 60 mg/m². The relatively high part of purse seine fishing catch with over 50 ton was formed on the range of SST over 20 degrees Celsius and the range of integrated chlorophyll (alpha) 50 - 200 mg/m².

The results of the experimental measurements of the laser induced fluorescence spectra futures for different sea water cases are presented in this paper. The data were collected during two scientific cruise in 1993 year in the sea of Okhotsk and in 1997 - 1998 years in some region of the Pacific. The scattering diagrams of the peak values of the chlorophyll a fluorescence and values of the integrals of the dissolved organic matter fluorescence specter were investigated for different sea water. The close correlation between these two characteristics of the laser induced fluorescence spectra was found for the sea water case one in the Pacific. In the sea of Okhotsk and sea of Tasmaniya such correlation was not observed.

An inverse modeling has a possibility to retrieve the concentration of water constituents, such as chlorophyll (alpha) (Chl-(alpha) ), suspended matter (SS) and yellow substance (CDOM), in case 2 water from remotely sensed data. It turned out to be useful for mass processing of satellite data. Standard approach for inversion of radiative transfer needs long computation time, because iteration procedure is essential. On the other hand, Neural Network (NN) method is able to overcome this problem since it is consider to be a kind of non-linear multiple regression method, so that it is possible to retrieve the concentration of multiple water constituents by NN. The NN Method was applied to OCTS (Ocean Color and Temperature Scanner) data in the Yellow Sea and East China Sea to retrieve of chlorophyll a concentration, in organic suspended solids and yellow substances. The large mount of suspended Solids the Yellow Sea and the East China Sea were supplied from the Yellow River (Wei He) and the Yangtze River (Chang Jiang). The temporal and spatial distributions of chlorophyll (alpha) , inorganic mineral suspension and yellow substance were analyzed.

The investigation of the bio-optical features distribution in the upper ocean layer is one of the objectives of the satellite remote sensing. But, very often it is necessary to compare satellite data with simultaneous shipborne measurements to interpret some processes more definitely. The statistical processing of the chlorophyll (alpha) concentrations simultaneously measured by SeaWiFS and by the shipborne fluorometer installed on the training sailboad 'Nadezhda' in the sea of Tasmania is presented in this paper. It is shown that in both cases we have detected characteristic scales in the chlorophyll (alpha) space distribution caused by the internal Rossby scales.

A radiative transfer model for a coupled atmosphere-ocean system was developed for satellite remote sensing of costal pollution to estimate water-leaving radiance from polluted sea surfaces. The optical properties of suspended substances in the ocean such as phytoplankton (Skeletonema costatum and Heterosigma akashiwo), detritus, submicron particles, and inorganic particles were measured or estimated. The equation of radiative transfer in the coupled atmosphere-ocean system was solved by using the invariance imbedding method. The water-leaving radiance in clear and Case II waters, turbid waters with soil particles, and red tide waters, were calculated. It was possible to estimate the soil particle concentration of water by using the ratio of the upward radiance at different wavelengths with a high resolution sensor for the land like the Landsat TM. However, estimating the red tide phytoplankton concentration using Landsat TM was difficult, because the water-leaving radiance varies little with phytoplankton concentration, and is affected by assumed amounts of detritus.

Measurements of 'Photosynthesis versus Irradiance' were conducted at 9 stations along the Equator from 145 degrees East to 170 degrees West in December 1999. Samples were obtained at about from the surface and chlorophyll maximum layer. The samples were inoculated with C-13 and incubated for 3 hours in a temperature controlled linear incubator which has 8 light levels. The P-I equation of Platt et al. is employed to calculate the initial slope, Pmax and the saturation parameters. It was La-Nina condition in this period and the influence of 'cold-tongue' came over around 160 degree East. Pmax varied from 1.7 to 4.7 (gC/gChl/h) on the surface. The minimum value of Pmax on the surface was observed at 160 degree East. The value increased gradually to the east and also to the west. On the other hand, the initial slope does not change so much and we cannot see such an east-west variability as Pmax. As it has been pointed out in previous studies, Pmax and the saturation parameter tend to decrees with depth and the initial slope tends to be lower near the surface.

In recent years environmental problems in the coral reefs attract both scientific and social attentions. However, most coral reefs have few maps showing the reef topography and the distributions of various benthic habitats in the reef. Satellite remote sensing can be used for coral reef mapping because satellites can observe the reefs scattered in tropical oceans in a short time repeatedly. Simple comparison between satellite images acquired on two different days is, however, strongly affected by the changes of the tidal level. Applying conventional classification algorithms to such satellite images often results in misclassification. We developed Bottom Index (BI) algorithm to minimize the water depth effect on satellite data. BI is a modified reflectance ratio between two bands in satellite data and corresponds to the proportion of benthic community cover in a pixel. In this study we applied this algorithm to Landsat TM data acquired during 1984 - 1996 on Ishigaki coral reefs, Japan, and evaluated its accuracy. We also developed the method for the separation of sand and coral/ algae/seagrass habitat using BI. We also found that the extinction coefficient ratio between two TM bands that is necessary for BI algorithm was basically constant there. And temporal variations of the sea floor cover type in Ishigaki during 1984 - 1996 were indicated by BI maps. Sea truth survey was conducted in August 2000 to validate the BI maps.

Small size phytoplankton are dominated in the western and central equatorial Pacific. Our study of HPLC measurements, size fractions of chlorophyll (alpha) and flow cytometric measurements indicate that phytoplankton communities in the equatorial Pacific are dominated by prokaryotic picophytoplankton with Prochlorococcus and Synechococcus, and small size autotrophic eukaryotes. Phytoplankton populations and the distribution were showed to differ from oligotrophic warm water region of the western equatorial Pacific and mesotrophic upwelling region of the central equatorial Pacific. In the oligotrophic region, phytoplankton distribution forms maximum layer around the nitracline. Prochlorococcus is most abundant in there. In the mesotrophic region, chlorophyll maximum layer is not found clearly. The population of autotrophic eukaryotes represented as prymnesiophytes were increased in there. Specific spectral absorption coefficients of phytoplankton [(alpha) *_ph((lambda) )] were measured throughout the euphotic zone in the two different regions. The (alpha) *_ph((lambda) ) were also reconstructed from HPLC results as the total of specific spectral absorption coefficients of chlorophyll (alpha) [(alpha) *_chla((lambda) )], chlorophyll b [(alpha) *_chlb((lambda) )], chlorophyll c [(alpha) *_chlc((lambda) )], photosynthetically active carotenoids [(alpha) *_psc((lambda) )] and photoprotective carotenoids [(alpha) *_ppc((lambda) )]. Reconstructed (alpha) *_ph((lambda) ) were compared with measured (alpha) *_ph((lambda) ). Reconstructed (alpha) *_ph((lambda) ) were overestimated at the field of (alpha) *_psc((lambda) ), especially in the mesotrophic region. The (alpha) *_psc((lambda) ) were considered as high contribution of prymnesiophytes. It was assumed that the package effect of prymnesiophytes was a cause of the overestimate of reconstructed (alpha) *_ph((lambda) ).

Possible enhancement of nutrient availability in the euphotic zone was challenged by lifting up subsurface nutrient-rich water in a coastal area. Man-made sea-mount was designed to enhance the rate of upwelling on continental shelf area. Since 1995, a project has been carried out for six years to build up a sea-mount and to research its possible effect on the primary productivity on the continental shelf at a depth of 80 m off Nagasaki Prefecture of Kyushu Island. A dual cone of around 120 m in width and around 11 m in height is being constructed in this area. During the research period, the availability of clear data sets of ocean color satellite images as about 7% of all scenes taken in this study area by the OCTS and SeaWiFS sensors. Patchy areas of higher chlorophyll-a concentrations than the surrounding water were occasionally observed in the square area of about 10 km * 10 km where the sea-mount was under construction at the center, particularly after the completion about 2/3 of the final stage for the sea-mount, while the chlorophyll pigments distributed almost homogeneously before the construction. The geophysical locations occurring the high chlorophyll a patches corresponded with the area predicted by a mathematical simulation model.

The Straits of Messina was surveyed on September the 25th 1999, at 14:15 local time, by means of the 4 spectrometers of Multispectral Infrared Visible Imaging Spectrometer instrument, recording 102 channels from Visible to Thermal Infrared along four southwards oriented flight lines. The first flight line was recorded from an altitudes of 1500 m a.s.1. (nadir pixel size of 3 m), while the others have been acquired from an altitudes of 4000 m a.s.1. (nadir pixel size of 8 m). In the Straits of Messina the strong tidal currents as well as the morphological features determine the upwelling of deep waters to the photic layer. Traditional oceanographic surveys, based on period punctual sampling, are sometimes inadequate to deeply investigate the areas subjected to high variability altering in space and in time the distribution of abiotic and biotic parameters. The effect of tidal currents on the upwelling of the Straits of Messina was measured by using the MIVIS hyperspectral sensor and through the continuous survey of some tracer parameters from sailing vessel. The collected hyperspectral data sets, once calibrated to reflectance (by using atmospheric model and fields spectra collected during the campaign) and geometrically corrected, were used to develop preliminary local bio-optical algorithms derived from in situ (ground and sea) measurements and to obtain suitable mapping of the chlorophyll distribution and of the Sea Surface Temperature of the investigated area.