We have investigated the correlation of remotely-sensed infrared spectral information with in situ field measurements and sampling to monitor ecosystem health, salinity, and population distributions of specific microbial communities occupying the salt ponds of southern San Francisco Bay. Approximately 61 km² of these salt evaporation ponds are scheduled to be restored to natural habitat over the next few decades as part of a historic remediation project. Significant cost reduction may be achieved through the use of a remote infrared monitoring approach in place of extensive sampling expeditions by field teams. Unique spectral signatures of microbial populations sensitive to salinity and other chemical concentrations provide the key to this method. The Airborne Visible and InfraRed Imaging Spectrometer (AVIRIS) instrument operated by the Jet Propulsion Laboratory (JPL) has created a ten-year archive of spectral information concerning these ponds which can be used to establish a baseline for comparison. We report here on in situ field sampling of microbial populations, including spectral measurements, and our results using these spectra to train a supervised classification algorithm (the US Geological Survey Tetracorder Algorithm) to identify microbial populations and physical parameters from an AVIRIS scene. Future measurements and data from satellite-based sensors may prove vital in monitoring the restoration process. High spectral resolution measurements from AVIRIS will be used to determine the efficacy of similar approaches using existing multispectral spaceborne sensors as well as to provide a reference for future, AVIRIS-class spacecraft as a surrogate for expensive ground surveys.

There are the results for the 3 groups of fiber-optical sensors. First is the fiber-optical sensor with changed sensitive heads on the base on porous polymer with clamped activated dye. Vibration method for fiber-optical sensors provides more convenient output measurements of resonant frequency changes, in comparison with the first device. The self-focusing of the living sells into optical wave-guides in laser road in water will be considered as a new touch method for environment remote sensing.

China Bohai Sea and Yellow Sea are semi-enclosed sea which locate between China continent and Korea peninsula, and affected by high turbid runoffs and strong monsoon. With the significant seasonal variation in temperate zone and local interests about fishery and ecosystem security in Margin Sea, China Bohai Sea and Yellow Sea is a good place for ocean primary production observation and researches. China has its own ocean satellite HY-1A in year 2002, and accumulated nearly two years of ocean color data, which can apply to marine environmental protection and resources management. Utilized the data of HY-1A aboard sensor, COCTS, ocean primary production of China Bohai Sea and Yellow Sea from July, 2002 to July, 2003 was estimated with a local primary production model. The seasonal evolution of algal biomass and external environmental changes, like depth of euphotic layer (Zeu), photosynthetic available radiation (PAR), and sea surface temperature (SST), affect the primary production in a complex way. Based on the input parameters of algorithm, spatial and temporal variation of primary production in China Bohai Sea and Yellow Sea was analyzed, revealing a maximum in summer, and a minimum in winter, and the offshore maximum front of primary production is significantly observed, under the balance of available light and nutrient limitation. The application of China ocean satellite data shows its good performance in the retrieval of compound biological and chemical parameters.

Field investigation was carried out during 4, April, 2001 to 15, April, 2001 around Zhoushan Fishing Ground. The surface nutrient and suspended sediment (SS) concentration exhibit remarkable features. Most striking are that all data show very high values at the end member Changjiang Diluted Water (CDW), decrease abruptly at the onset of mixing of Taiwan Warm Current. The frontal zone is mainly located near 123°E, which is supported powerfully by NOAA sea surface temperature (SST) image. Total phosphorus (TP) concentration is affected profoundly with SS concentration, for robust relationship between total particulate (TPP) and TP is observed in most stations (R²=0.9073, n=10). Positive correlation between in-situ concentration of TP and SS are found. The experimental regression equation is represented as C_TP=0.0195*C_SS+0.5266, R²=0.5645(n=32). NO₃- is the main form of DIN, of more than 82% in DIN, exhibits considerable conservative feature. Although lack of in-situ CDOM measurement, good relationship was established between in-situ DIN concentration with near real time SeaWiFS ACD data: C_DIN=135.1351*C_ACD-6.0, R2=0.7514 (n=15). The two empirical regression algorithms were utilized for inversing TP and DIN concentration from SeaWiFS SS and ACD. The algorithms were adopted to evaluate the impaction of terrestrial pollutant input to the area by CDW.

A multidisciplinary, multi-institution team of scientists has been working for over three years to evaluate the performance of sea ice parameter algorithms applied to data from the AMSR-E (Advanced Microwave Scanning Radiometer - EOS) carried aboard NASA's Aqua platform. The AMSR-E data and derived sea ice geophysical products have been compared against a variety of measurements, including ground truth data from an ice field camp, imagery from aerosondes and an aircraft-borne microwave radiometer, and imagery from RADARSAT, MODIS, and AVHRR. Arctic ice environments examined include first-year and multiyear pack ice in the Beaufort and Chukchi Seas, polynyas and flaw leads in the Bering Sea, and the ice edge. This paper will outline the AMSRIce03 project, cover the validation methodology in detail, and discuss the results and their implications for use of sea ice products derived from the AMSR-E.

Although other uses have emerged, ERS scatterometer data is operationally used to measure wind speed at the surface of the oceans. The wind speed and direction can indeed be inverted from the measured backscattering coefficients provided the measurements were performed over sea. While a land-mask can be used to reject measurements made over land, operational constraints make the use of an externally-provided ice-mask unpractical. It is thus desirable to discriminate between measurements made over sea and measurements made over ice using the backscattering coefficients alone. Due to operational constraints, a temporal averaging of the measurements is not feasible. Several methods have been proposed to discriminate between sea and ice. These are based on measuring the distance between the measurements made and a model. An ice model and a wind model are available. Measurements located far from the ice model were most likely not performed over ice and similarly, measurements close to the wind model were most likely performed over sea. However, for particular values of the incidence angles, these models are very close to each other, which leads to classification errors. In this paper, we propose to enhance the criterion of the distance to the wind model by taking into account the wind direction. This permits a better discrimination between ice-and sea-measurements. The enhanced criterion is implemented using a neural-network. The other methods proposed in the literature are also implemented in the same neural-network framework, which permits an easy comparison of their relative performances. Finally, the various methods are combined in a Bayesian framework.

Previously, it was shown that it is possible to separate the elastic scattering from the chlorophyll fluorescence signal using a polarization discrimination technique. The separation procedure depends however fundamentally on the degree of polarization of the water leaving radiance. In this paper, we compare polarization effects and efficiency of the fluorescence retrieval by simulating the total and polarized reflectance of waterleaving radiances originating from elastic scattering in case 1 and case 2 waters using radiative transfer and multiple component Mie scattering programs. This is done by superimposing upon these reflectances the contribution of known fluorescence spectra, and by using our polarization discrimination procedure to invert the resulting data back into fluorescence spectra. It is shown that a Mie scattering code which does not take into account multiple scattering effects can strongly overestimate the degree of polarization for case 1 and case 2 waters as well as reflectances in the green part of the spectra. Making use of these results we propose and evaluate an improvement for the traditional height over baseline fluorescence extraction method which strongly overestimates fluorescence value for case 2 waters. For our approach we use inverse absorption spectra of water and chlorophyll a scaled up and fitted to the reflectance spectra in the red and near IR bands with the subsequent retrieval of the fluorescence spectrum and chlorophyll a concentration. Results and potential of this approach are discussed.

This study suggests a new approach for ocean color algorithms (OCAs) in Case 2 water using bio-optical field measurements in the Western Arctic Ocean (WAO). Relationship between the inherent optical properties (IOPs) and the apparent optical properties (AOPs) on the sea surface were highly correlated through remote sensing reflectance, Rrs(λ). This result indicates that the radiance and irradiance can statistically reflect the effect of combined the absorption and backscattering of particulates. Based on the AOPs data, estimated surface chlorophyll a concentrations (chla) using SeaWiFS global algorithm, OC4V4 and the tuned for the Arctic, Arctic OC4L, showed much different from in situ chla including 25% and 30% errors, respectively. Absorption coefficients of suspended material and colored dissolved organic matter were also high in addition to high values of Rrs(λ) spectra from 510nm to 565nm, which indicates that the waters is classified into Case 2 water. These results demonstrate that in Case 2 water, current OCAs would be not applicable, and hence a new idea for developing OCA is required. Here as the approach, relationship between in situ chla and Rrs(555)/Rrs(510) is used to identify waters as spectral classified water groups. Especially in Case 2 water, with empirically derived Rrs(555)/Rrs(510) to be 0.75, when tuned intercepts with fixed regression coefficient for all data is applied on each spectral classified water group, chla can be estimated with excellent accuracy (<10% errors). This approach would be essential when varieties of spectral water groups in nature considered.

From the beginning of its mission, in 1995, the ERS-2 satellite has recorded an important set of data. The performance and accuracy of its instrument provide precious information for the scientific community. The experience acquired during 10 years has led the European Space Agency (ESA) to plan a reprocessing activity of the entire set of the available scatterometer data. This reprocessing activity will use the enhanced on-ground processing¹ and calibration² chains. In this paper, the calibration strategy for the scatterometer data reprocessing from the beginning of the mission is presented. It consists in looking for a calibration area (rainforest, ocean or ice) which would allow a highly accurate tuning of the antenna patterns (already tuned within the specifications).

The radar altimeter data sets are used to study several dynamical characteristic of the World's Oceans because the artificial satellites have a global coverage. One of the most important applications is related to the Mean Sea Level changes. The authors take into account the TOPEX/Poseidon data for the Mediterranean Sea and the Iberian Atlantic in order to compute the trend of the Mean Sea Level by means of two different procedures: the linear regression and fractal geometry. The first one leads to very well known results but the errors in the estimation are quite large and the second leads to more reliable results.

Two novel microwave instruments, the Advanced Synthetic Aperture Radar (ASAR) on the Envisat satellite and the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) on EOS satellites, have recently become available to the scientific community. They offer new possibilites to study polynya size fluctuations: high-resolution ASAR images give a perfect view of polynya conditions but only a limited number of scenes is available in the ESA archive over a small area (circa 2 scenes per month); low-resolution AMSR-E images allow the detection of polynya extent on a day by day basis but with a much coarser accuracy. This study, while confirming the strong correlation between wind intensity and polynya area, suggests the feasibility of using ASAR images to calibrate the "open water" threshold in AMSR-E images for polynya size detection on a daly basis.

Over a two year period, measurements of the daily levels of 74.91 kHz. acoustic signals transmitted between oil - immersed acoustic waveguides [AWG] correlated fairly well [20 to 70%] with daily tidal levels controlled by the sun and moon's gravitational forces on earth. Consequently, it is reasoned, the AWG measurements are also in some sense or degree related to these forces. Assuming that the daily AWG measurements are indeed gravity related, then a 1 Hz. to 15 Hz. pulsatory background noise or jitter which was found to be associated with the AWG signal with a peak response at 6 Hz. could possibly be indicative of gravitational - type of waves or disturbances occurring somewhere in space. In thls regard, it is interesting to note that pulsars have been studied as possible sources of gravitational waves or disturbances, and that the pulsed radio energy emissions of >90% of pulsars catalogued occur in the <1 Hz. to 20 Hz. frequency range and peak emission also occurs at 6 Hz. This raises the possibility of a gravity - type of low frequency background noise or hum at that frequency.

Much progress has been made toward modeling the spectral infrared (IR) emissivity of wind-roughened water surfaces. Existing emissivity models explicitly calculate the ensemble mean emissivity of the wavy surface for a given observer zenith angle and local wind speed. However, field observations of emissivity spectra obtained by the Marine Atmospheric Emitted Radiance Interferometer (M-AERI) suggest that emissivity models are deficient at larger view angles and wind speeds. In this preliminary work, we attempt to identify and explain the sources of error in these models using M-AERI data acquired at sea (e.g., during AEROSE 2004). Our results demonstrate that proper accounting for non-unity surface emissivity must ultimately include appropriate specification of the reflected IR radiation field, especially in window channels. Atmospheric IR surface reflectance becomes important for high accuracy applications (e.g., sea surface skin temperature), that rely on window channel observations at zenith angles ≳45 deg. Lookup tables of ensemble mean effective incidence angle, rather than mean emissivity, are generated using different published mean square slope PDF models. These results roughly agree with recent findings. Lookup tables of ensemble mean local zenith incidence angle are also generated. This new approach to emissivity/reflection modeling will be refined and validated against M-AERI field data from several previous oceanographic cruises, and will be the subject of a forthcoming paper.

A fundamental challenge to Remote Sensing is mapping the ocean floor in coastal shallow waters where variability, due to the interaction between the coast and the sea, can bring significant disparity in the optical properties of the water column. The objects to be detected, coral reefs, sands and submerged aquatic vegetation, have weak signals, with temporal and spatial variation. In real scenarios the absorption and backscattering coefficients have spatial variation due to different sources of variability (river discharge, different depths of shallow waters, water currents) and temporal fluctuations. This paper presents the development of algorithms for retrieving information and its application to the recognition, classification and mapping of objects under coastal shallow waters. A mathematical model that simplifies the radiative transfer equation was used to quantify the interaction between the object of interest, the medium and the sensor. The retrieval of information requires the development of mathematical models and processing tools in the area of inversion, image reconstruction and detection. The algorithms developed were applied to one set of remotely sensed data: a high resolution HYPERION hyperspectral imagery. An inverse problem arises as this spectral data is used for mapping the ocean shallow waters floor. Tikhonov method of regularization was used in the inversion process to estimate the bottom albedo of the ocean floor using a priori information in the form of stored spectral signatures, previously measured, of objects of interest, such as sand, corals, and sea grass.

EOS\MODIS data have been proved a suitable and relative low-cost complementary tool to monitor large inland lake water quality for its re-visit frequency, moderate spatial and spectral resolution and appropriate channels designed for inversing water quality parameters. In this study, by the support of hi-tech research and development program of China, Lake water quality remote monitoring pre-operational system (LWQRMPS) was constructed aimed for practical monitoring of Taihu Lake water quality. The main water quality parameters including Chl-a and SPM, TN and TP inversion algorithm were developed. These parameters were obtained every month from time series fusion satellite data. With the routine trophic state evaluation system, the water quality was assessed every month based on the above retrieved MODIS water quality parameters, varied level of eutrophic area was computed. The obvious high reflectance in near-infrared spectrum caused by blue-green algal bloom support the application of 250m MODIS data in the algal bloom emergency monitor. Therefore, MODIS data were utilized successfully for inversing water quality parameters, evaluating eutrophication status, and detecting algal bloom in near real time. Standard thematic maps were produced and distributed to corresponding management departments. The accuracy of products and retrieve algorithm for operational use were tested with separate data sets. The result suggested that system is good enough for practical monitoring water quality of large size lakes and acquired identification.

Rapid urbanization and increasing agricultural activities raises risks of surface water impoundment pollution at the Salt Lake which is one of the most important natural sources in Turkey. The Lake is a hazardous region for surface measurements especially in spring months due to its bottom covered with a 1 to 30 cm. salt layer. It is, therefore, necessary to make water quality assessment using remote sensing data. The applications of remote sensing techniques have been in use over the years for this purpose. In order to evaluate changes, in this paper, the water quality at the Salt Lake was examined by using remote sensing data. Firstly, Landsat (MSS, TM and ETM) and ASTER images were collected for providing multitemporal satellite data. After the image processing operations such as geometric correction, image classification, all resulting data were evaluated together. It is obvious from the remotely sensed and treated data that the water quality has retrogressed during the last two decades due to uncontrolled domestic, agricultural and industrial wastewaters. It is suggested that the waste discharges should be controlled and the surface water pollution monitoring should be carried out using satellite technology in addition to ground measurements.

Flood vulnerabilities of various flooded entities are dependent on flooding process, e.g. time period, flooding intensity, spatial and temporal distribution, especially for growing crops affected. This information can not be obtained by classical methods (like field survey, middle to high-resolution images and hydraulic models) due to factors of laboring, cost, complicacy and accuracy. It is necessary to develop a new approach of lower cost and reasonable accuracy to gain our ends. This paper made an experimental study of linear unmixing method to try to approximate our goal with easy-to-get, high frequent revisit, though low spatial resolution NOAA AVHRR image in Poyang lake region of Jiangxi province, P.R.China. This region is located at north Jiangxi province; its low flat plain topography has very little multiplicative spectral reflections, and is suitable for linear unmixing application. After analyzing the histograms of NOAA AVHRR images, we decided to use the difference image of band-2, band-1 and minus band-2 to differentiate water from others. After application of linear unmixing, we assumed area fraction of water in each pixel is approximately equal to calculated spectral fraction of water in each pixel (this is virtually true when there is little multiplicative reflection and refraction), then fine geo-referencing and spatial assignment were made based on the relation between the element (water) to be spatially assigned and other high-resolution thematic factor DEM. This study provide a new Earth Observation approach for continuously monitoring distribution change of relatively homogeneous large-scale features, like waters, desert, oil spillage extension etc.

In recent years, great amount of polluted water discharged into the north part of Lake TaiHu, results in water eutrophication and frequent occurrences of blue-green algal bloom in the area. In order to obtain the information about blue-green algal bloom distribution for monitoring water quality, four navigation of in situ hyperspectral measurement and MODIS data of 250 m resolution were used to study the radiance reflectance character and distribution of blue-green algal bloom in the lake. Hyperspectral measurement showed that the peak of water leaving radiance near 700 nm transferred to 750-780 nm as the water covered with blue-green algal bloom and increased with the increasing density of water bloom. Band ratio of channel I to channel II and band synthesize of MODIS image of 250 m resolution were used for detection of algal bloom, and proved that band ratio of channel I to channel II was more suitable for detection of algal bloom. The methods for differentiating submerged vegetation and algal bloom from MODIS image were also tested: The area covered with submerged vegetation usually had high secchi depth, with algal bloom usually low secchi depth, and the phenomena can be used efficiently for differentiating submerged vegetation and algal bloom on MODIS image.

China has launched the first ocean color satellite HY-1A on May 15, 2002, which carried two remote sensors. The Chinese Ocean Color and Temperature Scanner (COCTS) is the main sensor on HY-1A, and it has not only eight visible and near-infrared bands similar to the SeaWiFS, but also two more thermal infrared bands to measure the sea surface temperature. Therefore, COCTS has broad application potentiality, such as fishery resource protection and development, coastal monitoring and management and marine pollution monitoring. In this paper, the standard atmospheric correction algorithm of COCTS is expatiated firstly, and the reasons why this algorithm and some other atmospheric correction algorithms for turbid waters fail in china coastal and inland water are analyzed. The result shows that not only the non-neglected water leaving radiance at near-infrared bands, but also the error of the aerosol single scattering reflectance between bands 7 and 8 for COCTS. On the base of analyzing the principle of the water-leaving radiance varying with the sediments concentration, we have developed an atmospheric correction algorithm in turbid waters for COCTS, which eliminates the over correction and negative water-leaving radiance at blue wavelength bands in China coastal and inland waters, and the result shows that the normalized water-leaving radiances derived by this algorithm accord with reality much better. By comparing with the SeaWiFS data, it shows that the atmospheric correction algorithm of COCTS is reliable, and the water-leaving radiance derived from COCTS data is consisted with SeaWiFS data.

The numerical model of the vector radiative transfer of the coupled ocean-atmosphere system is developed based on the matrix-operator method, which is named PCOART. In PCOART, using the Fourier analysis, the vector radiative transfer equation (VRTE) splits up into a set of independent equations with zenith angle as only angular coordinate. Using the Gaussian-Quadrature method, VRTE is finally transferred into the matrix equation, which is calculated by using the adding-doubling method. According to the reflective and refractive properties of the ocean-atmosphere interface, the vector radiative transfer numerical model of ocean and atmosphere is coupled in PCOART. By comparing with the exact Rayleigh scattering look-up-table of MODIS(Moderate-resolution Imaging Spectroradiometer), it is shown that PCOART is an exact numerical calculation model, and the processing methods of the multi-scattering and polarization are correct in PCOART. Also, by validating with the standard problems of the radiative transfer in water, it is shown that PCOART could be used to calculate the underwater radiative transfer problems. Therefore, PCOART is a useful tool to exactly calculate the vector radiative transfer of the coupled ocean-atmosphere system, which can be used to study the polarization properties of the radiance in the whole ocean-atmosphere system and the remote sensing of the atmosphere and ocean.

POLDER 3 is a multispectral and multidirectional imaging radiometer/polarimeter, the third instrument of the POLarization and Directionality of Earth Reflectances family. It is designed to collect global images of the earth/atmosphere reflectances with a wide field of view of 1600 km and a moderate spatial resolution of 6 km. It was developed and successfully launched onboard the PARASOL microsatellite by the Centre National d'Etudes Spatiales (the French Space Agency) on December 18, 2004, and the first images were acquired on January 7, 2005. The nominal acquisition phase has started on march 10, 2005 after a successful flight commissioning phase. The specificity of this instrument is to measure polarized reflectances for three out of the 10 spectral channels from 443 to 1020 nm, from 16 viewing directions during a single satellite pass. The purpose of this paper is to present the preliminary ocean color scientific products: marine diffuse reflectances, amount and type of aerosols derived from the atmospheric correction scheme and concentration of chlorophyll pigments. The level 3 products will be compared to another ocean color instruments, MODIS.