This PDF file contains the front matter associated with SPIE Proceedings Volume 6743, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.

The purpose of this paper is to take into account the spatial variability of a wind-roughened sea surface from 1-meter to large scale including sub-metric variability. An analytical model of infrared sea surface optical properties based on a statistical approach is proposed. We introduce a new two-scale model consisting in superimposing the small scale variability (smaller than the pixel footprint) to the large scale one. The analytical expressions given in literature are extended to account for any slope mean vector-value and covariance matrix, and the statistical properties are determined for the resolution required by the observational configuration. Verifications of the physical validity of this new approach are presented. They globally show a good agreement. A bias is observed at grazing angles, mainly explained by the fact that the multiple reflections are ignored. Our model has also been implemented for the generation of synthetic sea surface radiance images, showing its ability to produce good quality ocean scenes in various contextual conditions.

Narrow band polarization measurements were taken from a bridge in San Diego Harbor using the Advanced Coherent Technologies Multi-mission Adaptable Narrowband Imaging Spectrometer (MANTIS) multichannel imaging system. MANTIS was capable of simultaneously collecting four channels of imagery through a narrowband green (532 nm) filter together with linear polarizers oriented at 0, 45, 90, and 135 degrees. This configuration enabled the collection of the first three Stokes Vector elements. The data is being gathered to explore methods of calculating the sea surface Mueller Matrix. Models, methods, and measurements are presented. Of specific interest is the deviation of the modeled data from the measured data and its causes. The data and a model are used to estimate the contribution of upwelled polarized light.

The Cramer-Rao lower bound (CRLB) for the estimations of the cosine and sine amplitudes of multi-tone sinusoidal model is derived and applied on TOPEX/Poseidon satellite altimetry data sets covering the Indian Ocean. The CRLB depends on the variance of the White Gaussian Noise that it is computed by Modern Parametric Autoregressive Adaptative Spectral Analysis. Determining CRLB parameters it is possible to establish the minimal error associated to any model built to work in the study area what improves the intrinsic bias of the generated time series. The noise that appears in the altimetric data depends strongly on the errors from the atmospheric and geophysical corrections, so the role of the inverted barometer and tidal corrections are also analyzed. The results is summarized as: a) the spatial structure of the order of the parametric model considering the application or not of the above corrections and its relationship to the surface dynamical system of currents in Indian Ocean; b) the spatial structure of the variance of the WGN in the area and its meaning; c) the CRLB for the Geoid's estimators and the CRLB for the estimators of the semiannual and annual waves.

A variety of aerial mapping cameras were adapted and developed into simulated multiband digital photogrammetric mapping systems. Direct digital multispectral, two multiband cameras (IIS 4 band and Itek 9 band) and paired mapping and reconnaissance cameras were evaluated for digital spectral performance and photogrammetric mapping accuracy in an aquatic environment. Aerial films (24cm X 24cm format) tested were: Agfa color negative and extended red (visible and near infrared) panchromatic, and; Kodak color infrared and B&W (visible and near infrared) infrared. All films were negative processed to published standards and digitally converted at either 16 (color) or 10 (B&W) microns. Excellent precision in the digital conversions was obtained with scanning errors of less than one micron. Radiometric data conversion was undertaken using linear density conversion and centered 8 bit histogram exposure. This resulted in multiple 8 bit spectral image bands that were unaltered (not radiometrically enhanced) "optical count" conversions of film density. This provided the best film density conversion to a digital product while retaining the original film density characteristics. Data covering water depth, water quality, surface roughness, and bottom substrate were acquired using different measurement techniques as well as different techniques to locate sampling points on the imagery. Despite extensive efforts to obtain accurate ground truth data location errors, measurement errors, and variations in the correlation between water depth and remotely sensed signal persisted. These errors must be considered endemic and may not be removed through even the most elaborate sampling set up. Results indicate that multispectral photogrammetric systems offer improved feature mapping capability.

Fluorescence Line Height (FLH) algorithms are effective for fluorescence retrieval in the open ocean where elastic reflectance in the fluorescence zone does not deviate much from the baseline. In coastal waters, FLH algorithms are significantly complicated by the overlap of the fluorescence and elastic reflectance peaks. To test accuracy of MODIS, MERIS and other FLH algorithms, we compared numerical simulations using an extensive synthetic database suitable for case II waters, with results of extensive field measurements of reflectance, absorption and attenuation spectra by us in the Chesapeake Bay, as well as satellite FLH data from several areas that typically show low correlation between [Chl] and FLH. Our synthetic datasets were created using the HYDROLIGHT radiative transfer code with IOP's connected to parameterized microphysical models in accordance with procedures used to generate the IOCCG dataset, but with some added improvements. These included higher (1 nm) spectral resolution, a wider range of parameters typical for coastal waters, including chlorophyll specific absorptions with significant variations in spectral shapes and magnitude. HYDROLIGHT simulations of elastic reflectance using measured attenuation/extinction spectra followed by subtraction from measured reflectance, permitted retrieval of the fluorescence contribution to the latter, for comparisons with the data set simulations. We find relatively small fluorescence contributions to surface reflectance for mineral concentrations > 5 mg/l because of strong attenuation in the excitation zone and enhanced elastic reflectance making fluorescence detection unrealistic. For lower mineral concentrations, we find that some combinations of NIR observation bands permit reasonably good FLH retrievals in conditions where specific absorption spectral variation is not very high, and that application of multi-spectral algorithms can be more efficient for the retrieval of fluorescence contributions in coastal areas.

Hyperspectral remote sensing is an increasingly important tool for evaluating the complex spatial dynamics associated with estuarine and nearshore benthic habitats. Hyperspectral remote sensing is being utilized to retrieve information about coastal environments, such as coastal optical water properties and constituents, benthic habitat composition, and bathymetry. Essentially, the spectral detail offered by hyperspectral instruments facilitates significant improvements in the capacity to differentiate and classify benthic habitats. A design tradeoff in the design of existing and proposed hyperspectral spaceborne platforms is that high spectral resolution comes with a price of low spatial resolution when compared to existing multispectral spaceborne sensors. The expectation is that the high spectral resolution will compensate for the reduction in spatial resolution by providing information to retrieve some of the lost spatial detail as well as other pieces of information not possible to retrieve using multispectral sensors. This paper reviews different approaches to unmixing of hyperspectral imagery over benthic habitats. Two specific methods that combine water optical properties retrieval with linear unmixing are then described and compared with a standard approach to linear unmixing over land as applied to benthic habitat unmixing. Results show that water column correction is necessary for accurate mapping and that, by removing the water column, we obtain significant improvement in retrieval of bottom fractional coverage for algae, sand and reef endmembers.

Within the framework of ORPAM (03/MAC/4.2/A2) project, five years of AVHRR Sea Surface Temperature (SST) (in °C) (2001-2006) (HAZO station, Azores) and of MODIS Ocean Colour (OC) (chlorophyll a in mg m^-3) and SST (2002- 2007) data (NASA/GSFC), allowed the establishment and comparison of the mean surface temporal variability among the Azores, Madeira, and Canaries regions. Results show strong and similar seasonal SST variability patterns with average values ranging between 15°C (winter) and 27°C (summer). Largest SST differences are observed during wintertime (Azores/Canaries-lowest/highest values, respectively). Interannual SST variability shows no defined patterns among the three regions. Ocean Colour seasonal variability varies inversely with SST. In the Azores, spring blooms dominate, followed sometimes by smaller autumn ones. In Madeira, spring blooms dominate. In Canaries, OC means are highest during February and March. Interannual OC variability shows the largest variation in Canaries (summertime). These results suggest strong latitudinal gradient effects. Canaries waters are generally warmest, followed by Madeira, and Azores. Highest OC averages are found in the Azores and Canaries regions. In the latter case, this most likely reflects e.g.: the contribution of the African coastal upwelling; OC algorithms failure in Case 2 waters; and winter mixing processes in the region.

Coastal areas are under great pressure due to increase in human population and industrialization/commercialization and hence these areas are vulnerable to environmental degradation, resource reduction and user conflicts. In the present study an Integrated Coastal Zone Management Plan (ICZMP) has been developed for Udupi Coast in Karnataka, along West Coast of India. The various data products used in the present study includes IRS-1C LISS-III + PAN and IRS-P6 LISS III remotely sensed data, Naval Hydrographic Charts and Survey of India (SOI) toposheets, in addition to ground truth data. Thematic maps such as land use/ land cover map, bathymetry map, shoreline configuration map, transportation and drainage network maps, GPS survey map, CRZ map, contour map, DEM, inundation map, critical erosion area map were prepared. A Coastal Vulnerability Index has also been calculated for the study area to know the resistance of study area to sea level rise and is demarcated into four categories; Very high, High, Moderate and Low vulnerability, and a vulnerability map has been prepared. The results of the present study are encouraging. Some of the specific conclusions of the study are; about 50% study area is prone to erosion, river mouths along study area show shifting tendency towards south, and the beaches along the Udupi Coast are maintaining dynamic equilibrium. Coastal Zone Information System (CZIS) has been developed through V.B.6.0 using results of various data analysis.

The total absorption coefficient a(λ) and total backscattering coefficient b_b(λ) are the basic inherent optical properties (IOPs) in ocean color remote sensing, which is the key to connect appearance optical properties (AOPs) from the remote sensor and the concentration of water component. In this paper, based on the stable and strong spectral relationship of the absorption coefficient (excluding the contribution of pure water) and particle backscattering coefficient at 510nm and 555nm, a new quasi-analytical remote sensing IOPs algorithm with two reference wavelengths is developed. The absorption coefficient and particle backscattering coefficient at 510nm and 555nm is calculated firstly through algebraic equations, and then based on the spectral model of particle backscattering coefficient, the a(λ) and b_b(λ) at the other wavelength are extrapolated. Three optical data sets are used to validate the algorithm, including the in situ data set of China Yellow Sea and East China Sea in the spring of 2003, the synthesis data set and the global in situ data set from IOCCG. Meanwhile, the performance of this new algorithm is also compared with the results of GSM01 and Lee-QAA algorithms with the ECS data set. The results show that, in the coastal area with high influence of terrestrial material, the two reference wavelength algorithm has better flexibility for the special optical water.

The effect of the polarization response is remarkably for some of the ocean color remote sensors with high polarization sensitivity, such as MODIS. The current implementation of the MODIS polarization correction algorithm has been applied operational, however it ignores the polarization component produced by aerosol scattering. In order to assess the effect of the aerosol scattering, we use the coupled ocean-atmospheric vector radiative transfer model PCOART to simulate the top of atmosphere linear polarization radiance at two cases, one is the pure Rayleigh atmosphere which absents aerosol, the other case has the aerosol thickness of 0.2. The results show that aerosol scattering has neglect effect on the blue wavelength (443nm) except at the sun glint, however, the effect on the near infrared wavelength (865nm) is remarkable. Otherwise, we compare the POLDER remote sensing and PCOART simulated TOA linear polarization radiance with the pure Rayleigh atmosphere and the results also show that aerosol scattering has neglect effect on the blue wavelength (443nm), but has large effect on the near infrared wavelength (865nm). Finally, we improve the ocean color polarization correction algorithm of MODIS by considering the aerosol scattering effect on the TOA linear polarization radiance. By using POLDER remote sensing polarization data, this improved algorithm is validated and the result shows that the improved algorithm has more accuracy than the origin polarization correction algorithm, especially at near infrared wavelength.

The spectral absorption models of phytoplankton are established based on the in-situ measurements and the accuracy of the models is assessed with the comparisons among the models. A power function is used to study the phytoplankton absorption model with wavelength-dependent coefficients determined by the least squares method. The accuracy of the power model is assessed by three kinds of spectral error indices, which are root mean square error (RMSE), the spectral-average-relative error, the spectral average log-transformed relative error and with the average values of 0.07 m^-1, -12.5% and -4.5%, respectively. The accuracy of the models is influenced by many factors such as the equation forms, the parameter values of the models, the phytoplankton species, pigments composition and particle size structure. The performances of the models are obviously different, even the same form of the model with different parameters. Two phytoplankton absorption models of Sathyendranath are validated and other three forms of phytoplankton absorption model are also developed to check whether the models are sensitive to chlorophyll a concentration and to the forms of the equations. The results show that it is the parameters of the models that dominate the performances of the models instead of the form of the equations. It is also indicated that the absorption values estimated by the models fall within the ranges of the measured data and the models are difficult to be validated without information of the phytoplankton species.

The study, proposed within the framework of the cooperation with Kenyan Authorities, has been carried out on the Kenyan part of the Lake Victoria. This lake is one of the largest freshwater bodies of the world where, over the last few years, environmental challenges and human impact have perturbed the ecological balance. Pollution and sediments loads from the tributaries rivers and antrophic sources caused a worrying increase of the turbidity level of the lake water. Secchi transparency index has declined from 5 meters in the 1930s to less than one meter in the 1990s. With the aim of providing an inexpensive way to gather information linked to the water clarity and quality, a method for remotely sensed data interpretation, devoted to produce chl (chlorophyll), CDOM (coloured dissolved organic matter) and TSS (total suspended solids) maps, has been assessed. At this purpose a bio-optical model, based on radiative transfer theory in water bodies, has been refined. The method has been applied on an image acquired on January 2004 by ENVISAT/MERIS sensor just a week after an in situ campaign took place. During the in situ campaign a data set for model refinement and products validation has been collected. This data comprise surface radiometric quantity and samples for laboratory analyses. The comparison between the obtained maps and the data provided by the laboratory analysis showed a good correspondence, demonstrating the potentiality of remote observation in supporting the management of the water resources.

China Marine Surveillance is equipped with the modern aerial equipments for marine law-execute with the advantages of functioning agilely and larger surveillance coverage, which provide the powerful safeguard for the harmonious and sustainable development of Chinese coastal economy. Onboard the plane, the marine airborne multi-spectrum scanner (MAMS), made by Shanghai Institute of Technology and Physics CAS, is an important equipment. In this paper we will briefly introduce a flight experiment in East Chinese Sea using MAMS at first. To retrieve the quantitative information from MAMS data, atmospheric correction is a necessary step. So we will focus on applying atmospheric correction algorithm MODTRAN to the MAMS airborne ocean color remote sensing data. Then case study of Zhoushan sea area in East Sea will be discussed. The result demonstrates that the MODTRAN is insufficient in retrieving sea surface reflectance when apply it directly for the low-altitude airborne remote sensing in Chinese coastal area.

With the availability of scatterometer data, surface wind vectors can be estimated from the backscatter measurement over oceans, guarantee global, long-term monitoring of the winds on the oceans, which make them very valuable for climate studies and other applications. At moderate wind speeds, the wind speed derived by scatterometer is considered reliable. But at higher wind speeds, scatterometers appear to underestimate the wind speed, especially in tropical cyclones, because of deficiencies of the geophysical model function for high winds, attenuation caused by rain, influence of wind gradient, and the saturation of the backscattering under high wind. As a passive microwave sensor, radiometer does not show obvious saturation phenomena under high wind, therefore it is an appropriate candidate to be used to retrieve high wind speed. In this paper, combined scatterometer and radiometer data is used to retrieve wind field under high wind condition. Using in situ data and meteorological data as a criterion, we compared the wind retrieval performances of scatterometer and radiometer. Results show that it is better to use radiometer data as a replacement of scatterometer while observing high wind speed.

It is well known that ocean-atmosphere dynamic affects the weather conditions over the continents and the ocean itself. The hydrologic cycle is driven by climatic parameters like precipitation, temperature, evaporation, winds and humidity. Hence, the river's water discharges and lake water level variations are impelled by climatic conditions also. Lake Izabal is the largest one in Guatemala; its main tributary is the Polochic River. Its level is related to the Polochic Rivers runoff and therefore to the precipitation/evaporation over its catchment area. The Lake Izabal water level fluctuations are driven by the annual cycle of rainy and dry seasons. In this study the ENVISAT RA-2 Geophysical Data Records orbits over the lake, coupled with in-situ measurements are used in order to determine and characterize the lake level fluctuations. The precipitation records over the lake's catchment area are also analyzed. In addition, some relationships of the lake level interannual variations with the climate indexes of Southern Oscillation Index SOI and the Tropical North Atlantic NATL were investigated. The main result is that the abrupt lake level rise in July 2006 is correlated to an abnormal precipitation in June 2006. Theoretically, this was forced by "La Nina" Southern Oscillation events during early 2006.

Global standard ocean colour algorithms may be inefficient to estimate the concentration of seawater constituents in the Mediterranean Sea. Local overestimation or underestimation of chlorophyll, suspended sediments and yellow substance are in fact quite common. To avoid this problem, our research group works on the local calibration of empirical or semi-analytical algorithms through comparison to in situ measured data. The spectral features of chlorophyll, suspended sediments and yellow substance were found for a number of samples near the coast of Tuscany (Italy). An unconventional algorithm was then developed and applied to satellite data (MODIS) for the retrieval of water constituent concentrations. This inversion algorithm is based on the minimization of the spectral angle between simulated and measured remote sensing reflectances. The estimated concentrations show a lower error with respect to that obtained by a standard error minimization criterion. Monthly maps of seawater constituent concentrations obtained by applying the proposed algorithm to numerous satellite images confirm the oligotrophic nature of the Tuscany Sea, where high values of these concentrations can be found only in early spring near the mouths of the main rivers.

The atmospheric correction for the ocean color remote sensing is the most important technique to retrieve the water leaving reflectance, which is less than about 10% of the satellite reflectance, and its major uncertainties are occurred by the estimation error of atmospheric aerosols that is highly variable in both space and time. Especially, in the general algorithm with two near-infrared observation data, the correction over the coastal region becomes more difficult because the influence of the signal other than atmosphere (e.g. turbid water background) cannot be ignored. To improve the atmospheric correction accuracy in the turbid water area, the atmospheric correction algorithm with multi-viewing observation data was examined. In this paper, we present the application result with POLDER2 multi-viewing observation data over the Yellow Sea. As the results of this test, the water leaving reflectance with the standard deviation from 0.79% to 11.48% was retrieved for two test points.

The aim of the paper is to analyze the fluorescence characteristics of the neritic water on the Romanian Black Sea coast under anthropogenic influences. A fluorescence LIDAR, based on excimer (308 nm) and a dye laser (367, 460 nm) was used in order to map the Dissolved Organic Matter (DOM) and chlorophyll variations in a marine area. Onboard ship campaign was performed during spring time to evidence the algal blooming. Physicochemical parameters of water and chlorophyll concentration were determined also by laboratory measurements of collected samples. The organic compounds and phytoplankton were characterized based on Laser Induced Fluorescence (LIF) and Raman scattering. Highly polluted areas were noted and mapped along the ship trajectory.