This pdf file contains the front matter associated with SPIE Proceedings Volume 7858, including Title Page, Copyright information, Table of Contents, and Conference Committee listing.

Coastal ocean-color estimation needs to retrieve not only molecular and aerosol scattering (ρ_a), but also high spatial resolution sea-surface reflectance (ρ_a) because ρ_g has fine temporal and spatial scales due to variable winds and air-sea stability caused by the coastal geographical structure. Murakami and Frouin 2008 showed a possibility of ρ_g correction by using near infrared (NIR) and shortwave infrared (SWIR) channels of MODIS 500m observations. This study investigated the correction of the atmospheric and sea-surface reflectance on the southwest of New Caledonia lagoon using AVNIR-2 which has 10-m resolution but doesn't have SWIR. After corrections of gas absorption and molecule scattering, we estimated ρ_a+ρ_g and water-leaving reflectance iteratively through IOPs retrieved from visible bands. Spectral slope of ρ_a+ρ_g was assumed uniform within our small target area (60km×40km). We tested sensitivity to several possible IOP spectra (total absorption of particle and dissolved matter and back-scattering coefficients) with comparison to in-situ IOP measurements. The AVNIR-2 derived remote sensing reflectance agreed well to the MODIS one (rootmean square difference / average of Rrs 443nm was 43%), and AVNIR-2 IOPs agreed well to in-situ IOP measurements (correlation coefficients more than 0.9) when we used the IOP spectra modeled by in-situ measurements around the New Caledonia. Chlorophyll-a (Chla) calculated by the AVNIR-2 IOPs showed better agreement to in-situ Chla in the lagoon areas where traditional blue/green algorithms overestimated.

An atmospheric correction algorithm, defined as the solution of a statistical inference problem, has been developed to process satellite ocean-color data into water reflectance. The definition of the inversion algorithm relies on an estimate of the distribution of the uncertainties on the top-of-atmosphere (TOA) reflectance, corrected for molecular effects. This distribution is estimated from an in-situ match-up dataset. The forward operator is discretized using a radiative transfer code, and the theoretical solution is approximated numerically. SeaWiFS spectral bands and Case-1 waters are considered in the simulations. The inverse problem is signicantly ill posed, i.e., quite different water reflectance spectra may correspond closely to the observed TOA reflectance spectrum. In view of this, the solution is approximated in a Bayesian framework by the conditional expectation of the water reflectance given the TOA reflectance. Satellite estimates of marine reflectance agree with in situ measurements. The mean squared differences (in ×10^-5) are 2.16 at 412 nm, 1.12 at 443 nm, 0.77 at 490 nm, 0.53 at 510 nm, 0.46 at 555 nm, and 0.03 at 670 nm, and the mean absolute relative difference is 19.7%. Application to SeaWiFS imagery shows a substantial noise reduction in the spatial elds of water reflectance compared with the corresponding SeaDAS-derived fields. The methodology allows the construction of uncertainties on the retrieved water reflectance, without shape restrictions, a perspective for future work.

Traditional sampling method for marine environment monitoring is time consuming and needs a high cost to carry out the survey. Remote sensing data have been widely used for monitoring marine environment and remote sensing is an efficient method to overcome the problem. This paper assesses the use of multispectral satellite imagery from THEOS for mapping spatial distribution of TSS in a coastal zone. The aim of this study is to evaluate the feasibility of using THEOS satellite image for the water quality studies. Simultaneous in situ measurements of total suspended solids (TSS) concentration and acquisition of satellite imageries were carried out over Penang Island, Malaysia. The locations of in situ sample were determined using a handheld Global Positioning System (GPS). The algorithm used is based on the reflectance model which is a function of the inherent optical properties of water and this in turn can be related to the concentration of its constituents. Multiple regression algorithm was employed using the multi-band data for retrieval of the water constituent. Digital numbers corresponding to the water sample locations were determined for algorithm calibration. Various types of algorithms were tested; R and RMS value were noted. The proposed algorithm is considered superior based on the values of the correlation coefficient and root-mean-square The algorithm was used to generate the TSS map for the Penang Island, Malaysia. Geometric correction was performed to the TSS map and colour-coded for visual interpretation. This study shows the potential application of THEOS satellite images for TSS mapping using the proposed multispectral algorithm.

Estimation and monitoring Chlorophyll-a concentration (CHLA), especially low CHLA in lake using remote sensing data is very important for early warning of blue-green algal bloom. In spite of better overall goodness fit in three-band CHLA inversion model of turbidity water proposed by Gitelson, the estimation errors of samples with low CHLA are often higher, and this kind of error has great influence on the evaluation of lake nutritional status. In this paper, two methods of data transformation-logarithm of CHLA and continuum removal of spectrum-were used to decrease model error. Data set includes the routine monitoring sampling data collected from June to September, 2004 in Taihu Lake and field data in March, 2010 in Meiliangwan of Taihu Lake. Water surface spectrum data were measured in situ by ASD FieldPro. Comparative analysis showed that both logarithm transformation (LT) and continuum removal transformation (CRT) can increase model's accuracy. For all sample data, the average relative accuracy of model built by data after LT increased by 30%, and that of model built by data after LT and CRT increased by 35%. For the samples with CHLA lower than 50μg/L, the average relative error decreased from 76% of model built by data without transformation to 36% of LT and 27% of LT and CRT. The paper concluded that data transform is a simple and effective method to increase precision of CHLA remote sensing inversion.

The fine-scale study of the diffuse attenuation coefficient, K_d(λ), of the spectral solar downward irradiance is only feasible by ocean color remote sensing. Several empirical and semi-analytical methods exist. However, most of tthese models are generally applicable for clear open ocean waters. They show limitations when applied to coastal waters. A new empirical method based on neural networks has been developed using a relationship between the remote-sensing reflectances between 412 and 670 nm and K_d(490), for the SeaWiFS ocean color remote sensor. The architecture of the neural network has been defined using synthetical and in situ dataset and the optimal design is a tow hidden layer neural network with 4 neurons of the first layer and three on the second layer. The comparison with the SeaWiFS empirical algorithms shows similar retrievals accuracies for low values of K_d(490) (i.e. <0.20 m^-1) and better estimates for greater values of and K_d(490). The new model is suitable for open water but also for turbid waters and does not show the limitations of the empirical method. The new model is more general that the empirical methods.

The MERIS instrument delivers a unique dataset of ocean colour measurements of the coastal zone, at 300m resolution and with a unique spectral band set. The motivation for the Coastcolour project is to fully exploit the potential of the MERIS instrument for remote sensing of the coastal zone. The general objective of the project is to develop, demonstrate, validate and intercompare different processing algorithms for MERIS over a global range of coastal water types in order to identify best practices. In this paper the Coastcolour project is presented in general and the Regional Algorithm Round Robin (RARR) exercise is described in detail. The RARR has the objective of determining the best approach to retrieval of chlorophyll a and other marine products (e.g. Inherent Optical Properties) for each of the Coastcolour coastal water test sites. Benchmark datasets of reflectances at MERIS bands will be distributed to algorithm provider participants for testing of both global (Coastcolour and other) algorithms and site-specific local algorithms. Results from all algorithms will be analysed and compared according to a uniform methodology. Participation of algorithm providers from outside the Coastcolour consortium is encouraged.

Spilled oil is one of the most serious marine environment disasters, which damaged ecological environment seriously with long-term and large-scale impact. Based on the experiment and research in the Canadian Centre of Environmental Technology, an experiment is taken to detect the underwater suspended oil-spills by Laser-induced fluorescence. It quantizes the conditions that Laser-induced fluorescence can be used to detect underwater oil, and makes a solid theory foundation for the system design of underwater oil detection by Laser-induced fluorescence. This environmental solves a key problem for underwater oil detection by Laser-induced fluorescence.

Inherent optical properties (IOPs), e.g., absorption, back scattering coefficients, and volume scattering function, are important parameters for radiance transfer simulation. Commercially available instruments (e.g., Wetlabs ACS, BB9, etc, and HOBILabs a-sphere, HS6, etc) basically only measure absorption and back scattering coefficients. In this paper, we used the same IOPs of International Ocean-Colour Coordinating Group (IOCCG) report 5 and Hydrolight to simulate the radiance distribution, however, different phase functions, say, a new phase function derived from the measured data by multispectral volume scattering meter (MVSM) in coastal waters, the widely used Petzold average phase function, and the Fournier-Forand (FF) phase function, were employed in the simulations. The simulation results were used to develop the retrieval algorithm with angular effects correction based on the quasi-analytical algorithm(QAA) developed by Lee et al.. Results showed that not only the back scattering probability, but also the angular shape of phase function are important for ocean color retrieval algorithm. Considering the importance of phase function in ocean color remote sensing, methods to validate the phase function data should be developed.

We use a multiple regression analysis and a data bank of about 400 reflectance spectra to reconstruct hyperspectral reflectances between 400 and 900 nm with a 5 nm step using only the values known at the wavelengths of the MERIS sensor level 2 data. For in situ remote sensing reflectances measured during different oceanographic missions, the reconstruction is within 2 per cent almost over the entire spectrum. The main difference (to a maximum of 4 per cent) usually occurs at the inflexion point of the reflectance curve between 580 and 600 nm. Observed in-situ remote sensing reflectances or reconstructed spectra are inverted using a Water Colour Simulator bio-optical model (WASI) to obtain the inherent optical properties (IOP) of the water. The values derived by the model are compared with the measurements when available. To validate the reconstruction, we compare the results of the model inversion using the initial spectrum or the reconstructed one as input. Preliminary results show that the derived values from the inversion of the reconstructed spectrum are very close to the values generated from the inversion of the initial spectrum, especially in case 1 waters. This reconstruction technique is used to generate hyperspectral remote sensing reflectances from reflectance data calculated by the MERIS sensor. We use the reconstructed spectra as input to be inverted in the WASI model in order to quantify the substances' concentrations; in particular, the inversion is working well for the suspended particulate matter concentrations.

Estimation of the underwater attenuation of light is important to ecosystem modellers, who require information on Photosynthetically Available Radiation (PAR), and on the euphotic depth for calculation of primary production. Characterisation of these processes can be achieved by determining the diffuse attenuation coefficient of PAR, KPAR . A review of bio-optical models of the spectral diffuse attenuation coefficient for downwelling irradiance, K_d , is presented and stresses the necessity for a better knowledge and parameterization of these coefficients. In the second part of this work, radiative transfer simulations were carried out to model K_dZ1% the spectral diffuse attenuation of downwelling irradiance averaged over the euphotic depth Z_1% (depth where the downwelling irradiance is 1% of its surface value). This model takes into account the effects of varying sun zenith angle and cloud cover and needs absorption and backscattering coefficients (the inherent optical properties, IOPs) as input. It provides average and maximum relative errors of 1% and 5% respectively, for sun zenith angles [0°-50°] and of 1.7% and 12% respectively at higher sun zenith angles. A relationship was established between K_dZ1% at a single wavelength (590nm) and KPAR at Z_PAR1% (where PAR is 1% of its value at the surface) which allows for a direct expression of KPAR_ZPAR1% in terms of inherent optical properties, sun angle and cloudiness. This model provides estimates of KPAR within 25% (respectively 40%) relative errors respectively with a mean relative error less than 7% (respectively 9%) for sun zenith angles ranging from 0° to 50° (respectively higher than 50°). A similar method is applied to derive a model for the diffuse attenuation of photosynthetically usable radiation, KPUR_ZPUR1% , with similar performance.

Based on the analysis of an extensive bio-optical data set, i.e., the NOMAD dataset, the simultaneous stochastic behavior of the marine reflectance and chlorophyll concentration is characterized using nonparametric techniques. A statistical model of the conditional distribution of the marine reflectance given the chlorophyll concentration is proposed, that takes into account the natural correlations between the various optical variables. The model can be used to simulate realistic marine reflectance spectra for a given chlorophyll content, and to define prior distributions for atmospheric correction of satellite ocean-color imagery. It may also help to define bio-optical algorithms for chlorophyll concentration that minimize the influence of phytoplankton type. Conversely, considering a nonparametric regression model to retrieve chlorophyll concentration from marine reflectance leads to an improvement of about 10% on the average relative error over the polynomial OC4v4 algorithm. The prediction error of the nonparametric model provides a lower bound on the possible accuracy of chlorophyll concentration retrievals from in-situ marine reflectance, i.e., 49.2%.

Studying the light field of sea water is important in Ocean Color Remote Sensing (OCRS) because it brings immense information concerning the ocean environmental properties. This magnitude of the Apparent Optical Properties (AOPs) emerges from the sea-surface after incidence light energy has been absorbed and scattered by sea water constituents. In this process, the amount of scattering is a lot smaller than that of absorption relatively. So the understanding of Inherent Optical Properties (IOPs), especially absorption, is very important in OCRS. Many studies have been accomplished in various seas around the world. In optically more complex waters around Korea, we have found only a few investigations on the IOP and AOP. Thus, in this study we analyze the absorption coefficient of sea water constituents, phytoplankton, Suspended Sediment (SS) and Dissolved Organic Matter (DOM) for the IOPs and the remote sensing reflectance for the AOPs. About 1300 water samples have been collected in the Korean waters from 1998 to 2010. It should be noted that sea areas around the Korea have different characteristics separately. So we analyzed the optical properties of each separated sea waters and compared each other results. The absorption spectral shape of SS and DOM showed exponentially decreasing pattern. Each graph's slope includes information of absorption characteristics. Using this results, in the future, we will prompt to develop the ocean environmental algorithms for ocean color satellite images, especially GOCI (Geostationary Ocean Color Imager) which will be launched on June 2010, around the Korean ocean.

A multi-sensor algorithm is applied to MODIS and MERIS satellite data in order to quantify suspended particulate matter (SPM) in the Yangtze River plume (East China Sea). Several atmospheric correction methods are tested; a simple but operational method is finally selected as appropriate for MODIS, MERIS and GOCI satellite data. As most of the methods for atmospheric corrections of satellite data fail over such highly turbid waters, an adaptation of the black pixel assumption is used to correct for the aerosol contribution. The retrieved seawater reflectance at red wavebands appears as the most sensitive to SPM concentrations but tends to saturate at concentrations beyond 100 mg.l-1. By opposition the near-infrared seawater reflectance does not saturate even at extremely high concentrations of 1000 mg.l-1. Overall, the most robust relationship between the SPM concentration and seawater reflectance is obtained considering a spectral ratio between the near-infrared (e.g., 850 nm) and visible (e.g. 550 nm). This relationship is applied to atmospherically corrected ocean color satellite data to retrieve SPM concentrations in the Yangtze River plume. Results show that ocean color satellite data can be used to study the seasonal dynamics of SPM and better understand the role played by the main physical processes involved (river discharge, tidal cycles, wind and regional circulation).

We present data collected as part of ValHyBio- VALidation HYperspectral of a BIOgeochemical model in the South Western Tropical Lagoon of New Caledonia, a PNTS-sponsored program dedicated to chlorophyll satellite imaging and validation as affected by bathymetry. The specific goals of ValHyBio are to: - examine time-dependent oceanic reflectance in relation to dynamic surface processes, - construct field/satellite reflectance-based chlorophyll models, - investigate the feasibility of inverting the model to yield surface chlorophyll and turbidity, - validate the biogeochemical model with field/satellite observations. In situ bio-optical parameters include absorption coefficients by CDOM and particles, Secchi disk depth, backscattering coefficient, pigment concentration, suspended matter concentration, and K_dPAR. They are measured every month at 5 stations, of contrasted bathymetry and bottom reflectance, as well as at a reference station situated 4 miles offshore, and on a station over coral reefs. Remote sensing reflectance is calculated from the absorption and backscattering coefficients and compared with satellite data. SeaWIFS and MODIS AQUA match-ups collected over the period 1997-2010 (ValHySat-VALidation HYperspectral SATellite database) are used. Satellite retrievals are examined as a function of bathymetry. The feasibility of a longterm monitoring program of optical water retrieval with satellite remote sensing technique is examined in the frame of the GOPS (South Pacific Integrated Observatory).

Global warming has significant effect on the sea surface temperature. Sea surface temperature is an important parameter for the quantitative studies of monitoring the Earth's environment changes. Determination and analysis of sea surface temperature from satellite data has been the main focus in oceanographic research and thus needs quantitative analysis in its retrievals. We used EOF method applying SST. Seasonal and interannual variability of Sea surface temperature (SST) and Land surface temperature (LST) concentration in the korea Sea was examined using Empirical Orthogonal Function (EOF) analysis of data obtained by the NOAA from 1999 to 2009. In the result of SST, The first EOF mode explains 55.7% of the variability, the second EOF mode explains 21.5%, and the third EOF mode explains 21.5%. As a result of LST, The first EOF mode explains 99.7% of the variability, the second EOF mode explains 2.5%, and the third EOF mode explains 0.9. It shows commom tendency of interannual variability with the period of 3-4 years at most of the locations. SST was higher in the 2004's and early 2006's and lower in the 2003. The pattern of the interannual variability of SST was similar to that of air temperature. Increasing trend of SST was obvious that it was larger eastern more than western. In the Future, we expect to analyse, collect with a various satellite data and in situ data for long time.

During the winter in later 2009 and early 2010, the Bohai Sea experienced its worst sea ice event in four decades. Sea ice optical properties are derived from MODIS-Aqua measurements using the SWIR atmospheric correction algorithm. The radiance feature of the sea ice in the Bohai Sea shows a strong dependence on ice types. For months of December, January, and February during the winter of 2009-2010, the average sea ice albedo in the Bohai Sea reached about 9.3%, 13.4%, and 12.6%, respectively. A regional sea ice detection algorithm has been developed for monitoring sea ice in the Bohai Sea. During the 2009- 2010 winter, the sea ice covered about 5427, 27414, and 21156 km² for the three winter months, while average values of sea ice coverage between 2002-2010 are about 2735, 11119, and 10287 km², respectively. Anomalously large sea ice event in the Bohai Sea during 2009-2010 winter is attributed to the dominance of a high air pressure system in the northern China and widespread air temperature drops in January and early February of 2010.

The applicability of remotely sensed data to the detection and monitoring of the seasonal variation of microphytobenthos distribution in a tidal flat was examined for the Geunso-bay tidal flat in the west coast of Korean peninsula. The biomass of diatom within the surface sediments was estimated through field campaigns and the seasonal change in the spectral reflectance of the remotely sensed data was investigated. Field spectrum data were acquired monthly at the fixed locations for monitoring the microphytobenthos blooming and comparing with the spectral reflectance of satellite images. Sediments facies was also analyzed along with the spectral reflectance based on the in situ data, and the spectral characteristics of the area where microphytobenthos occupied was examined. A medium to low spatial resolution of satellite image was not suitable for the detection of the surface sediments changes in the study area due to its ambiguity of sediments facies boundary, but the seasonal changes of benthic distribution could be obviously detected. From this, we suggest that the study on the distribution of surface sedimentary facies and detailed ecological mapping in a tidal flat based upon the remote sensing images should consider the seasonal variations of microphytobenthos distribution which would be included in the spectral characteristics of the satellite images.

We examined the relations of the channel distribution with the sedimentary facies in Geunso-bay tidal flat, Korea. The tidal channel networks were extracted from an aerial photograph. The patterns of the channel distribution were compared with one another for several sites in terms of the fractal analysis, channel density. The channels in each sediment facies showed relatively constant meandering patterns, however, the density and the complexity were distinguishable for each facies. The 2nd fractal dimension which indicates the branch pattern of the tidal channel were 1.87 in the mud flat, 1.41 in the mixed flat, and about 1.30 in the sand flat. The channel density in the mud flat was 0.035-0.06 m/m² which was the highest among the three sedimentary facies. Using the differences in fractal dimensions and tidal channel densities in each sedimentary facies, we tried to adjust the sedimentary facies classification which had been generated from the interpolation of the surveyed data. For each grain size sampling site, the percentage of sand particles was compared with the channel density. It was shown that the higher the sand percentage, the lower the tidal channel density except at a few points. The locations showing the exceptional pattern were mainly inside the tidal channel or adjacent to the inland. We suggest that those differentiated features of tidal channels among the different sedimentary facies should be applied to the surface sedimentary facies classification in the tidal flat.

No map of the sea floor is available yet on the whole lagoon of New Caledonia. We tried to validate a method to map it with MeRIS images on the south western part of the lagoon. The non-linear effect of water column light attenuation can then be corrected to obtain the absolute reflectance of the seabed. Light attenuation by the water column can be determined by comparing the radiance of standard features on the seabed at different depth. Bathymetry can also be determined by measuring the relative reflectance of the seabed in green and red light spectral bands. Once the effect of attenuation has been removed, a supervised classification can be applied in order to obtain the location of each item on the sea floor. Validations are operated with ground measurements of depth, spectral profiles and some available maps.

The major part of the New Caledonia (NC) lagoon was classified as UNESCO Natural Site of Humanity Patrimony. Indeed, 22 175 km² of tropical coral lagoon area exhibit high biodiversity. The NC lagoon is semi enclosed and connected to the Coral Sea through a barrier reef segmented by narrow passes. The environment is oligotrophic, due to important flush during trade winds events, and bathymetry is highly variable. In order to predict eutrophication events, we used an extension of a 3D coupled physical-biogeochemical model recently developed on NC south western lagoon. The model is based on the Nitrogen and Carbon cycles, relating the variable stoechiometry of the elements in each biological compartment. The ecological model was developed to include an explicit description of the microbial loop. The resulting coupled model, forced by tide, wind, light, temperature and freshwater inputs, was used to calculate phytoplankton biomass, bacterial production, dissolved organic matter concentrations and nutrient recycling. Here we present results issued from the 3D coupled model ECO3M_LAGOON (biogeochemical, LOPB-IRD) and MARS3D (regional physical model, IFREMER-IRD) describing spatial and temporal interactions between water motion and biology, on larger domain including reef barrier and water exchanges through ocean-lagoon interface. To validate physical processes in the lagoon we used in situ data collected during field cruise (ValHyBio 2008, La Niña episode). Surface chlorophyll concentrations are compared with water color data from ValHyBio cruise and satellite data (MODIS/MERIS) corrected from bathymetry effects.

The spectral reflectance was measured with hand-spectral instrument in Hangzhou Bay, and the water samples were collected in situ and analyzed in the lab. The relationships between chlorophyll-a (CHL) and total suspended matter (TSM) and the measured spectral reflectivity were analyzed, and CHL and TSM concentrations were estimated by using the combination of the field bands and TM image, respectively. The Empirical algorithm and Bio-optical model were applied to analyze the chlorophyll and total suspended matter horizontal distribution in Hangzhou Bay wetland. Comparison of the Empirical algorithm, the bio-optical model were selected and the models have higher precision, which would be validated for the estimation of CHL and TSM content by using the TM images. Finally, the two estimation models were discussed to educe the estimation models. Two of the most precise ones were used to estimate the CHL and TSM concentration. The results showed that TM is one of the appropriate data resources in the multi-spectral remote sensing to estimate the chlorophyll-a (CHL) and total suspended matter (TSM).

The northern coast of Hainan Island was selected as the study area. The object-oriented information extraction technology was used to process the remote sensing data of 1991, 2001, 2008, and processing results were put to the test of the coefficient of Kappa. The results show that: (1) Methods based on object-oriented information extraction technology can turn remote sensing data to integrated geographic information accurately and efficiently. (2) Kappa indexes, used to test the accuracy of classification results, were 0.7984(in 1991), 0.8331(in 2001), and 0.8571(in 2008) and the overall accuracies were 85.2, 88.86 and 89.14, respectively, which indicated the classification technology was more effective. (3) From 1991 to 2008, the area of construction land and water area increased in the study area. The number of construction land significantly increased, rose by 12083.33 hm², an average annual growth of 1.09 percent over the past 18 years. But the area of arable land, forest land, wetland and unused land decreased, among of which the decreasing tendency of arable land was significantly, the area dropped by 8124.75 hm², about 0.73 percent annually on average. (4) During the period, 71.34% of the increased construction land was converted from arable land, which indicated that urbanization has caused a great loss to agricultural land.

The landcover of the northern floodplain around the Tonle Sap Lake involves the various vegetations, lacustrine lands, as well as settlements. In order to understand the contribution of landcover in this area for agricultural, piscicultural activity, and environmental protection, landcover classes should be classified by using remote sensing data. The aim of this study is to increase distinction between landcover classes for classification purpose. To improve the feature texture for pre-classification data, the ALOS PALSAR is fused with ASTER data. Both data are acquired in dry season in which the vegetation is little influenced by flooding. The fused data is created by injecting the feature texture of ALOS PALSAR into ASTER data. However, spectral character is distorted due to mixed spectrum. This is reduced by choosing optimal fused algorithm. The ten landcover classes are selected as signatures to classify and calculate confusion matrixes. Those confusion matrixes reveal that the distinction between the landcover classes in fused data is better than that in ASTER data.

Based on the remote sensing data of Landsat TM and ETM+ (July 1980 and 2000), by using RS and GIS technology, the spatial and temporal change of land use was analyzed in Jiaodong Peninsula coastal zone and its different buffers, apart from the coastline 0-25 km, an interval of 1 km. The result indicated: (1) The coastline had remarkable influence on the land use. Comparing with other regions, arable land covered a relatively small proportion of the land area within 3 km; on the contrary, the area proportion of construction land was significantly high. (2) During 1980 to 2000, the changes of arable land area and the construction land area were most obvious in Jiaodong Peninsula coastal zone, of which, arable land area decreased by 34582 hm², construction land area increased by 41224 hm². (3) The closer to the coastline, the greater the intensity of land use conversion. (4) The main characteristic of land use changing was the conversion of arable land, water area and unused lands into construction land, among which 78.6% was converted from arable land.

The purpose of this study is to develop an algorithm for estimating the chlorophyll-a concentrations of relatively clean coastal waters and highly eutrophic lakes from multispectral satellite images (ALOS/AVNIR-2) and field survey data. Obama Bay has a low chlorophyll-a concentration (<10 mg/m³). In contrast, Lake Kitagata is a brackish, eutrophic lake that is connected to the Japan Sea in the northeast, and it has a chlorophyll-a concentration in the range 10 to 200 mg/m³. For both water areas, the correlation coefficients between various ratios of satellite spectral bands and field survey data are calculated to determine the most suitable algorithm for estimating chlorophyll-a concentration. The preliminary results indicate that an algorithm using visible bands (bands 1, 2, and 3 for ALOS/AVNIR-2) have high correlation coefficients for Obama Bay, whereas an algorithm using the near-infrared band (band 4) is suitable for Lake Kitagata when it is highly eutrophic. These results indicate that water with a low chlorophyll-a concentration has a low near-infrared spectral reflectance, because of the strong absorption of light by water in near-infrared wavelengths.

Poyang Lake is the largest shallow lake wetlands in China, and which vegetation succession is rapid under high changeable hydrological regimes. This study measured the fluxes of carbon dioxide and methane simultaneously by opaque static chamber-gas chromatography technique for typical wetland vegetation ecosystems in the growing season. In view of the advantages both in temporal and spatial, HJ-1 satellite images were chosen as the data source for vegetation cover classification and area estimates. And based on the areas in different vegetation, carbon flux for the entire study area was estimated during the growing season. Results indicated that carbon dioxide flux has closer relationship with vegetation change than methane flux does.

The Changjiang River is the third largest river of the annual flux around the world, which has a great impact on the ecosystem of the East China Sea and adjacent areas. Because of the shallow water, tide mixing and the runoff of the Changjiang River and Qiantang River, the suspended particulate matter (SPM) concentration is extremely high in the Changjiang Estuary, which is ever up to 2000mg/L. Due to the large water-leaving radiance at the near-infrared wavelength, the operational atmospheric correction algorithm for the open ocean can not be applied to this region, and the existing remote sensing algorithms for SPM may not be applicable for this extremely high turbidity waters. In this paper, we firstly apply the blue wavelength atmospheric correction algorithm to MERIS Level-1 data to get the reasonable spectral water-leaving radiances in the Changjiang Estuary. Based on the winter cruise data in 2007, a regional SPM algorithm was developed using the bands ratio of the normalized water-leaving radiances between 779nm and 560nm. This algorithm was validated by the summer cruise data in 2006, and the results show that the performance of the algorithm was very well, and there was good agreement between the retrieved data and in-situ measured concentrations of the SPM in the Changjiang Estuary, with the correlation coefficient of 0.98 in the logarithm form and the averaged absolute relative error of 27.2%, and the standard deviation of 20.8mg/l in the linear form. Finally, the seasonal variations of the SPM in the Changjiang Estuary were analyzed by the MERIS SPM maps retrieved by the algorithms developed in this paper.

SAR change detection techniques have proved to be a precious tool for damaged areas rapid mapping especially after natural disasters. In case of similar acquisition modalities, general framework uses SAR images local statistics to extract efficient change measures. Recent works propose a new technique adapted to different sensors, acquisition modalities or climatic conditions. This technique is based on projecting the statistics of the first image to the acquisition conditions of the second image using the copula theory modelled by a quantile regression. However, this is done without considering the SAR texture behaviour which follows a Rayleigh distribution. In this paper, we present a new method adapted to heterogeneous SAR images. A new copula has been constructed starting fromtwo marginal Rayleigh distributions. Then usual Kullback Leibler (KL) based comparisons are used to validate the proposedmethod and shows its suitability to SAR images. Different climatic conditions ENVISAT SAR images are used to highlight the performances of this technique.

Characteristics of speckle errors of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll-a concentration were analyzed, and its removal process was presented in the East Japan Sea from September 1997 to December 2007. Level-3 data of SeaWiFS chlorophyll-a concentration provided by NASA showed significant speckle errors in the East Japan Sea. The speckles with anomalously high concentrations were randomly distributed and showed remarkably high bias, compared with their neighboring pixels. The speckles tended to appear frequently in winter, which might be related to cloud distribution. Ten-year averaged cloudiness of winter was much higher over the southeastern part, with frequent speckles, than the northwestern part of the East Japan Sea. Statistical analysis results showed that the number of the speckles was increased as cloudiness increased. Herein, we present a methodology of how to remove the speckles with highly anomalous chlorophyll concentration data using Level-2 data and how to composite the chlorophyll-a data to generate Level-3 data. Considering seasonal variations of the speckles and their statistical characteristics, dynamic threshold methods were given. Additional methodology for high values during spring bloom was also developed by considering the chlorophyll-a concentration frontal zone. After applying the methodology to ten-year Level-2 data, data composite of Level-2 was carried out to produce Level-3 product and compared with the NASA product. The results showed that most speckles were disappeared and more than 10% errors of 5°×5° mean values were reduced at speckle regions in the southeast East/Japan Sea. This study raised the issue about speckle errors in chlorophyll-a concentration composite from SeaWiFS data in the East Japan Sea for the first time and presented regionally-optimized composite method for more reliable chlorophyll-a data in oceanic application researches.

Relation between the spring bloom along the Primorye coast and sea ices of the Tatarskiy Strait in the northern East/Japan Sea were investigated using ten-year SeaWiFS chlorophyll-a concentration data and sea ice concentration data DMSP/SSMI for the period of 1998~2007. Year-to-year variations of chlorophyll-a concentration in spring were positively correlated with those of sea ice concentrations at the Tatarskiy Strait in the previous winter. Abrupt increases of nutrients, indispensable for spring bloom at the upper ocean in spring, were supplied from sea-ice melted waters. The water mass from sea ices provided a preferable condition for the spring bloom through changes in vertical stratification structure of water column. Along-coast ratios of stability parameters between the two neighboring months clearly show rapid progress of generation of shallow thermocline due to the ice-originated fresh waters.

Twenty-year Normalized Difference Vegetation Index (NDVI) data on the highest mountain in northeast Asia were analyzed to understand their temporal variability and response to large-scale El Niño-Southern Oscillation (ENSO) events. We demonstrated the first unequivocal evidence that El Niño events have played an important role in determining the ecosystem conditions in the Mt. Baekdu area in northeast Asia. The analysis confirmed that the onset of phenological spring was earlier during ENSO years. This was evident from a negative trend of -0.5158 month per ENSO index between year-to-year variations in spring timing and those in ENSO magnitudes. Over two decades, the phenological phases were negatively correlated with air temperature variations under atmospheric warming at Mt. Baekdu. However, such changes in NDVI are not likely to be affected by changes in the local precipitation, as inferred from forest types determined by land cover classification. On the basis of changes in air temperature during ENSO years, the results of this study indicate a significant remote connection between the local ecology at the highest mountain and the large-scale atmospheric and oceanic phenomena.

East China Seas locate in the East Asia Monsoon region, which have large seasonal variation. In this paper, we use the remote sensing data from AVHRR, SeaWiFS and MODIS to analysis the climatology and long-time change of sea-surface temperature and chlorophyll concentration in the East China Seas. First, the monthly-averaged sea-surface temperature and chlorophyll concentration remote sensing data sets from 1998 to 2009 are generated. Second, the climatology distributions of the sea-surface temperature and chlorophyll concentration in the East China Seas are analyzed both for the seasonal cycle and monthly cycle, and the results show that there is remark seasonal variation in the East China Seas. Finally, based on the long-time data sets we have generated, the annual variation of the sea-surface temperature and chlorophyll concentration in the East China Seas are analyzed, and results shows that sea-surface temperature generally decreases for the whole East China Seas in the last 10 years, but with spatial variation. The chlorophyll concentration increases in the Yellow Sea in the last 10 years; however, it is decreases in the shelf of the East China Sea and the Kuroshio region.

The SIMBADA radiometer was designed to check the radiometric calibration of satellite ocean-color sensors and evaluate the atmospheric correction of ocean-color imagery. It measures marine reflectance and aerosol optical thickness in 11 spectral bands covering the spectral range 350 to 870 nm. Aerosol optical thickness is obtained by viewing the sun disk and marine reflectance by viewing the ocean surface through a vertical polarizer that minimizes sun glint and reflected skylight. The measurements made by SIMBADA during ACE-Asia (March-April 2001, Japan Sea) and AOPEX (July-August 2004, Mediterranean Sea) are compared with those made concomitantly by other ocean radiometers and sun photometers, i.e., MER, PRR, SPMR, Trios, TSRB, and BOUSSOLE instruments for marine reflectance and CIMEL and Microtops for aerosol optical thickness. Agreement is generally good between the various measurements or estimates. The SIMBADA aerosol optical thickness is within ±0.02 of the values obtained by other sun photometers. The SIMBADA marine reflectance, after correction for bi-directional effects (Q factor), does not exhibit biases when compared with estimates by other radiometers, which generally agree within ±10%. In some cases larger discrepancies exist, and they are largely explained by differences in solar irradiance. More accurate SIMBADA estimates may be obtained by improving the radiometric calibration, the correction for angular geometry and water body polarization, the calculation of incident solar irradiance, and the selection of data minimally affected by sky reflection.

It requires frequent and high-resolution measurements of biogeochemical properties of the oceans in order to obtain the status of the ecosystems and evaluate its role in modulating the climate. Because of the limited coverage and high cost, such a task could not be achieved via traditional ship surveys. Satellite sensors, because of its high revisit time and synoptic coverage, can provide key measurements to remedy the weakness of ship surveys. To ensure reliable and consistent measurements from an ocean color satellite, it not only requires the sensor be well designed and calibrated, also requires the processing software be robust for a wide range of ecosystems. All these require adequate data in order to evaluate and characterize the whole system. Such data, however, will not be available until the sensor is functioning properly in the sky. To overcome this dilemma, we developed POCIS (Pseudo Ocean Color Image Simulator), which can generate top-of-atmosphere ocean color images based on sensor specs. Such images, which can be both regional and global, can then be fed into current/future processing system to generate proxy products, thus not only help to ensure the readiness of the processing system, but also help to identify weakness and strengths of such a system before its launch, and setup the bases for eventual improvements. Details of POCIS, along with examples of proxy VIIRS image products, are presented to demonstrate its capabilities and potentials.