This PDF file contains the front matter associated with SPIE Proceedings Volume 7149, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

Ultra-spectral atmospheric remote sounding has been under development since the late 1970's. It has evolved through a series of aircraft experiments into the operational space-borne system that we enjoy today. In this paper the background and evolution of the ultra-spectral remote sounding program is reviewed. Results from airborne and polar satellite ultraspectral instruments are presented to illustrate the improved atmospheric remote sounding capability provided by these instruments. Ground-based measurements with the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) are presented to illustrate the "state of the art" in imaging spectrometry and its potential for greatly improved ultra-spectral remote sounding from future polar and geostationary satellites.

The Atmospheric Infrared Sounder (AIRS) (Chahine et al., 2006) was launched in 2002 on AQUA, the second of the EOS polar-orbiting satellites. The AIRS was the first of a new generation of meteorological advanced sounders able to provide hyperspectral (sometimes referred to as ultraspectral) data for operational and research use. The improved spectral resolution it provided compared to earlier passive infrared sounders, led to a significant increase in vertical resolution and accuracy in determining thermal and moisture fields, increased accuracy in the determination of the concentrations of absorbers such as ozone and improved numerical weather prediction (NWP), (Le Marshall et al. 2006). It was also shown that expanded use of the information content of infrared hyperspectral radiance data resulted in an increase in the benefit of these data to NWP. Experiments which have shown the benefit of improved spatial coverage, spectral coverage and the use of moisture channel data, are summarised in this paper. In addition, an experiment which has recorded the benefit of using hyperspectral radiance data from fields of view containing clouds is also described. Again it is demonstrated that a more complete use of the information content in the observations available from hyperspectral sounders has resulted in improved benefits to numerical weather prediction. This conclusion is also supported by early experiments reporting the benefits from using IASI data. Overall, the results indicate the significant benefits to be derived from hyperspectral data assimilation and the benefits to be gained from an enhanced use of the information content contained in hyperspectral radiance observations.

As the forthcoming launch of the NPOESS Preparatory Project (NPP) nears, pre-launch predictions of onorbit performance are of critical importance to illuminate possible emphasis areas for the intensive calibration/ validation (cal/val) period to follow launch. During this period of intensive cal/val (ICV), quick-look performance assessment tools that can analyze global data over a variety of observing conditions will also play an important role in verifying and potentially improving environmental data record (EDR) quality. In this paper, we present recent work on a fast and accurate sounding algorithm based on neural networks for use with the Cross-track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS) to be flown on the NPP satellite. The algorithm is being used to assess pre-launch sounding performance using proxy data (where observations from current satellite sensors are transformed spectrally and spatially to resemble CrIS and ATMS) from the Atmospheric InfraRed Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU) on the NASA Aqua satellite and the Infrared Atmospheric Sounding Interferometer (IASI) and AMSU/MHS (Microwave Humidity Sounder) on the EUMETSAT MetOp-A satellite. The algorithm is also being developed to provide a highly-accurate quick-look capability during the NPP ICV period. The present work focuses on the cloud impact on the infrared (AIRS/IASI/CrIS) radiances and explores the use of stochastic cloud clearing (SCC) mechanisms together with neural network (NN) estimation. A stand-alone statistical algorithm will be presented that operates directly on cloud-impacted AIRS/AMSU, IASI/AMSU, and CrIS/ATMS (collectively CrIMSS) data, with no need for a physical cloud clearing process. The algorithm is implemented in three stages. First, the infrared radiance perturbations due to clouds are estimated and corrected by combined processing of the infrared and microwave data using the SCC approach. The cloud clearing of the infrared radiances was performed using principal components analysis of infrared brightness temperature contrasts in adjacent fields of view and microwave-derived estimates of the infrared clear-column radiances to estimate and correct the radiance contamination introduced by clouds. Second, a Projected Principal Components (PPC) transform is used to reduce the dimensionality of and optimally extract geophysical profile information from the cloud-cleared infrared radiance data. Third, an articial feedforward neural network (NN) is used to estimate the desired geophysical parameters from the projected principal components. The performance of the method was evaluated using global (ascending and descending) EOS-Aqua and MetOp-A orbits co-located with ECMWF forecasts (generated every three hours on a 0.5-degree lat/lon grid) for a variety of days throughout 2003, 2004, 2005, and 2007. Over 1,000,000 fields of regard (3 × 3/2 × 2 arrays of footprints) over ocean and land were used in the study. The performance of the SCC/NN algorithm exceeded that of the AIRS Level 2 (Version 5) algorithm throughout most of the troposphere while achieving approximately 25-50 percent greater yield. Furthermore, the SCC/NN performance in the lowest 1 km of the atmosphere greatly exceeds that of the AIRS Level 2 algorithm as the level of cloudiness increases. The SCC/NN algorithm requires signicantly less computation than traditional variational retrieval methods while achieving comparable performance, thus the algorithm is particularly suitable for quick-look retrieval generation for post-launch CrIMSS performance validation.

Retrieval of atmospheric profiles from the vertical atmospheric sounding suite aboard the Chinese FY-3A satellite has been investigated. A statistical retrieval approach is used to generate atmospheric temperature and moisture profiles. The statistical retrieval method is only applied to the clear-sky simulated radiances, achieving good retrieval accuracy. For example, in the simulated experiment, the retrieved atmospheric temperature and moisture profiles show good agreement with independent atmospheric samples. The RMS is about 1.2K on the average for temperature profile. The RMS is large for the near surface levels. The RMS of moisture profile is approximately 11%. The temperature and moisture fields agree well with the NWP analyses of NCEP.

3D humidity field is implicated in radiance measurements of multi-spectral satellite imagery and cloud distribution observed different cloud type at vertical and horizontal direction. This paper first addresses the relationship between multispectral satellite information and probed relative humidity in each of standard isobaric surfaces using correlation analysis, least-square fitting and multivariate linear regression separately. In order to improve retrieval precision of lower layer humidity field, and at the same time, the objective analysis field of measured ground humidity data is introduced as a new parameter. Furthermore, based on spectral features of different bands as well as the difference day or night, the statistical retrieval models about humidity field analysis on each standard isobaric surface is established separately by using different spectrum composition, and the method is proposed retrieving 3D humidity fields of satellite imagery pixel resolution (0.1° lat and long) at all weather and all time by using multispectral satellite imagery. The contrast test between retrieval result and radiosonde data shows that the total deviation is about 15%. Generally, the retrieval precision in higher humidity area by using multispectral satellite imagery is superior to the one in lower humidity area and that in high and low layer is superior to that in middle layer. Because of the space-time disagreement between the satellite sounding and radiosonde observation, the retrieval error would be increased, which needs to be taken into account when the retrieved relative humidity field is analyzed and used.

The Geostationary Earth Orbit (GEO) provides a unique opportunity of monitoring tropospheric pollutants on the regional scale. Thermal InfraRed (TIR) observations (from about 620-2300 cm^-1) have two advantages over other spectral domains: firstly, day/night observations are possible; secondly, numerous molecular species can be observed simultaneously. However, the sensitivity of TIR observations may be a critical point for the geostationary orbit geometry. In this study, we present a feasibility study for TIR pollution observations in GEO conditions. The capabilities of measuring the tropospheric abundance of ozone (O₃) and carbon monoxide (CO) are investigated. Limitations of the sensor sensitivity are also discussed.

This work presents clear-sky simulations to study water vapor (H₂O) retrieval from a nadir sounder operating in the TeraHertz (THz) and Far-Infrared (FIR) spectral domains (100-500 cm^-1). The THz/FIR retrieval is compared with retrieval from the mid-InfraRed (IR) 7μm H₂O band (1200-2000 cm^-1). The THz/FIR observations are more sensitive in the upper troposphere and lower stratosphere than the IR measurements. On the other hand, the IR sounder has better performance in the lower troposphere. The retrieval error due to uncertainties on the temperature profile are of the same order of magnitude in the THz/FIR and IR bands. No significant retrieval errors from contaminating species have been found. The calculations for several atmospheric scenarios show that retrieval performances are not only dependent on the H₂O abundance but also on the temperature gradient. Hence, sensitivity in the UT/LS layer, with a low temperature gradient, is poor. The combination of FIR and IR merges the advantages of both bands, and allows to slightly decorrelate temperature and H₂O VMR.

The U.S. National Polar-orbiting Operational Environmental Satellite System (NPOESS) is a satellite system being developed to monitor global environmental conditions and collect and disseminate data related to weather, atmosphere, oceans, land and near-space environment. The NPOESS Preparatory Project (NPP) mission is a joint effort involving the National Aeronautics and Space Administration (NASA) and the NPOESS Integrated Program Office (IPO). The NPP mission is currently scheduled to launch in 2010. NPP has two objectives: to extend the measurement trends begun by the NASA EOS missions and to validate four of the primary NPOESS sensors. The CrIMSS will provide the atmospheric vertical temperature and moisture profiles, two of the NPOESS key Environmental Data Records (EDRs). Two sensors, the Cross-track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS) provide the input data to the CrIMSS retrieval algorithm. This talk will detail the calibration and validation programs being executed for these two sensors, and the retrieval algorithm. The discussion will include prelaunch testing, with a performance summary, validation planning activities and exercises, and post launch validation plan status. The launch ready calibration/validation plan is scheduled to be ready for release November, 2008 and the status of the plan will also be briefed.

Radiometric calibration accuracy of 0.3 K in Tbb is necessary to retrieve CO2 concentration profile with accuracy of 1 % in the upper atmosphere. In case of the thermal infrared (TIR) band (band 4) of GOSAT-TANSO-FTS, interferometric phase correction procedure is very important because the total transmittance of the optics at the band is about 70 % because of opacity of dichroic mirrors of band 1-3 placed obstructing the field of view of band 4, and the mirrors reflect the radiation emitted from inside of the optics. Based on the results from the thermal vacuum tests (TVTs) of the sensor, it is found that interferometric signal is almost zero when the sensor view a target of which temperature is about 280- 300K because the radiation emitted from inside of the spectrometer controlled at about 296 K has completely opposite phase to that of the target. It is also found that the interferometric final phase of the calibrated signal varies when the total signal is almost zero because of weak signals that have phases differ from both of those of targets and calibrators. A candidate phase correction procedure is proposed based on that adopted for a previous space FTS sensor, IMG/ADEOS. Non-linearity correction for the detector and polarization efficiency correction are also desccussed.

The ultimate remote sensing benefits of the high resolution Infrared radiance spectrometers will be realized with their geostationary satellite implementation in the form of imaging spectrometers. This will enable dynamic features of the atmosphere's thermodynamic fields and pollutant and greenhouse gas constituents to be observed for revolutionary improvements in weather forecasts and more accurate air quality and climate predictions. As an important step toward realizing this application objective, the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) Engineering Demonstration Unit (EDU) was successfully developed under the NASA New Millennium Program, 2000-2006. The GIFTS-EDU instrument employs three focal plane arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The GIFTS calibration is achieved using internal blackbody calibration references at ambient (260 K) and hot (286 K) temperatures. In this paper, we introduce a refined calibration technique that utilizes Principle Component (PC) analysis to compensate for instrument distortions and artifacts, therefore, enhancing the absolute calibration accuracy. This method is applied to data collected during the GIFTS Ground Based Measurement (GBM) experiment, together with simultaneous observations by the accurately calibrated AERI (Atmospheric Emitted Radiance Interferometer), both simultaneously zenith viewing the sky through the same external scene mirror at ten-minute intervals throughout a cloudless day at Logan Utah on September 13, 2006. The accurately calibrated GIFTS radiances are produced using the first four PC scores in the GIFTS-AERI regression model. Temperature and moisture profiles retrieved from the PC-calibrated GIFTS radiances are verified against radiosonde measurements collected throughout the GIFTS sky measurement period. Using the GIFTS GBM calibration model, we compute the calibrated radiances from data collected during the moon tracking and viewing experiment events. From which, we derive the lunar surface temperature and emissivity associated with the moon viewing measurements.

Gas adsorption onto optical surfaces installed on satellites is one of the causes of signal degradation that occurs in orbit. To estimate the transmittance degradation caused by gas adsorption, transmittance measurements were carried out within the wavelength range of 200 nm to 14 μm. Five types of glasses, SiO₂, BK7, Al₂O₃, CaF₂ and ZnSe were selected as glass samples and three gas species were chosen as the adsorption gas samples: 2-propanol, ethyl acetate and dichloromethane. These three molecules are typical paint solvents. In the IR wavelength range, several absorption bands corresponding to vibration and/or bending transitions of the functional groups present in the adsorbed molecules were detected. In the UV-VIS wavelength range, there were no local absorption features; however, broad transmittance degradations were detected. The comparison of measured spectral transmittance degradations with sensor output degradations showed that the signal degradations of launched sensors were similar to the transmittance degradation due to 2-propanol or dichloromethane adsorption. Moreover, we estimated the growth rate of the adsorbed molecular film thickness using the degradation data of the orbiting sensor, MODIS/Aqua, under the assumption that the signal degradation was caused by organic gas adsorption. Our estimation showed that the growth rate of an adsorbed molecular film decreased with time after the launch.

Hokkaido Satellite Project was kicked off at April in 2003 by the volunteer group that consists of students, researchers and engineers in order to demonstrate the space business models using nanosatellites of 15kg/50kg in Japan. The Hokkaido satellite named "TAIKI" is characterized by a hyperspectral sensor with a VNIR (visible and near infrared range) and a laser communication instrument for data downlink communication. At the beginning of 2008 we started to develop a space qualified hyperspectral sensor HSC3000 based on the optical design of HSC1700. Last year we developed the hyperspectral camera HSC-3000 BBM funded by New Energy Development Organization (NEDO) as the position of the breadboard model of HSC3000. HSC-3000 BBM is specified by the spectral range from 400nm to 1000nm, 81 spectral bands, image size of 640 x 480 pixels, radiometric resolution of 10 bits and data transfer rate of 200 f/s. By averaging outputs of several adjacent pixels to increase S/N, HSC3000 of the spaceborne is targeted at the specification of 30 m spatial resolution, 61 spectral bands, 10 nm spectral resolution and S/N300. Spin-off technology of the hyperspectral imager is also introduced. We have succeeded to develop a hyperspectral camera as the spin-off product named HSC1700 which installs both the hyperspectral sensor unit and a scanning mechanism inside. The HSC1700 is specified by the spectral range from 400nm to 800nm, 81 spectral bands, image size of 640 x 480 pixels, radiometric resolution of 8 bits and data transfer rate of 30 f/s.

STSAT3, a ~150 kg micro satellite, is the third experimental microsatellite of the STSAT series designated in the Long- Term Plan for Korea's Space Development by the Ministry of Education, Science and Technology of Korea. STSAT3 is being developed for launch into a sun-synchronous orbit of 700 km altitude by the end of 2010. A compact imaging spectrometer (COMIS) is a secondary payload of STSAT3 that will be employed for environmental monitoring, mainly over the Korean peninsula. COMIS was inspired by the success of CHRIS, a previous PROBA payload. The chief function of COMIS is to image the Earth's surface with ground sampling distances of 30m or less at 18~62 spectral bands (4.0~1.05μm) for nadir observation at 700km altitude. COMIS, as its name implies, is very compact in volume, mass, and power. The total mass including optics, housing, and electronics is about 4.3kg and the average power per orbit is less than 5 watt. This paper reports on the prototype development of COMIS.

Due to the complexity of the tropical terrestrial environment present in Pacific islands and the lack of ground data, remote sensing could offer an appropriate tool for obtaining a better understanding and knowledge of the key parameters necessary to many environmental applications. Moreover, recent sensors provide high spatial resolution and good temporal periodicity which is suitable for the study of tropical environments. The potentiality of an oriented-object technique for land-cover mapping will be illustrated in this paper. Unlike traditional pixel-based classification, this technique is based on object-use topology and shape features for the differentiation of target classes. It offers a complex "knowledge base" about classes which can be directly formulated in classification rule sets. The first step applied to images is "segmentation" which enables the improvement of classification accuracy as compared with that achievable using only individual spectral signature pixels. In fact, indices based on spectral, spatial and textural or structural parameters are explored in order to reduce the confusion between classes. The results from the segmentation are then used to produce a classification of objects. The oriented-object classification technique is carried out on a section of Efate Island (Vanuatu republic) using images acquired in 2007/2008 by Formosat-2 sensor. Finally, the accuracy of the oriented-object classification is established with the help of ground control points.

In order to realize cloud classification in all-time, all the spectral information of GMS-5 satellite imagery has been exploited and made full use of in this paper. 2D~5D maximum likelihood algorithm was respectively used to experimental research on cloud classification of multi-spectral GMS imagery. In contrast with 415 surface cloud observation records in analysis region at 0800 local time, July 21,1998, if these cloud reports are strictly regarded as true, the mean accuracy of 15 kinds of 2D~5D cloud classification results is 64.9%. After the similarities and differences of satellite observation and surface cloud observation were surveyed, this paper points out that it is not completely right and reasonable that the results of cloud classification are distinguished between right and wrong absolutely according to surface cloud observation. Because the visual cloud observation from bottom to up on the ground is inevitably unilateral, the two results of different observation is sometimes hard to compare directly, contrasted the visual field observation from up to bottom of satellite. Therefore, the speciality of satellite observation must be fully noted when cloud classification is achieved by using multi-spectral satellite imagery, so in this paper the definition of distinguishing middle cloud and low cloud are put forward mainly according as brightness temperature of cloud top and make full use of multispectral information to differ thin cirrus and thick cirrus from low and middle cloud. To those samples classified as error by the criterion from surface cloud observation, it should be reappraised based on the speciality of visual field observation from up to bottom and the actual situation of satellite observation. The result reappraised to 35.1% of the "error" samples shows that 17.8% of those should be thought reasonable. The mean accuracy of 15 kinds of 2D~5D cloud classification results has been to 82.7% and the maximum accuracy is up to 87.0%, which is obtained from the 4-D maximum likelihood dynamic clustering of four wave band (IR, VIS, WV and T_IR2-IR1 ) GMS imagery data. The accuracy of cloud classification also reaches to 81.4% using the other four band (IR, WV , T _{WV -IR1} and T_IR2-IR1) imagery , especially when there is no VIS imagery at night. The final example shows on condition that multispectral information has been fully used, different spectral bands combination are utilized reasonably day and night respectively, the reasonable cloud classification will be well realized in all-time by using maximum likelihood algorithm.

A method was developed for global monitoring of temporal change of coral reef using pan-sharpened color images with higher accuracy and lower cost. The method consisted of 3 blocks; image co-registration for removing complex discrepancy due to parallax among original color image and panchromatic one, pan-sharpening with preserving color information, and change detection with suppressing noise such as sea waves. The method was successfully applied to an actual FORMOSAT2 multi-temporal data set. After removing the parallax between multi-spectral band images and panchromatic one, the spatial resolution of multi-spectral images was improved from 8 x 8 m² to 2 x 2 m² in the following pan-sharpening block. The pan-sharpening was performed by replacing brightness component of the original multi-spectral pixel with the panchromatic pixel density. In order to normalize the recording gain and offset, the brightness component was estimated by using a linear polynomial model whose coefficients were determined by applying a multiple regression analysis. Linear shapes of density scatter diagram of each spectral band between pansharpened density and original one indicated that the pan-sharpened spectral information was perfectly preserved. The change detection successfully detected some temporal changes with suppressing noise. The method was applicable to other data sets having lower resolution multi-spectral images and panchromatic one covering all spectral bands.

SO₂ emissions from fossil fuel power plants can have significant impacts on human health and ecosystems. Consequently, numerous techniques are in use to monitor these emissions, in order to comply with environmental legislations. Here we highlight the correlation between SO₂ emissions rate and the S contained in fuel used in power plant. We obtained a maximum of 1.3 kg.s^-1 of SO₂ emissions rate and a minimum of 0.4 kg.s^-1 corresponding respectively to 2.9 % and 1.2 % of S contained in fuel. Measurements also indicate that high concentration of S_O2 released from the Noumea 121 MW power plant is rapidly diluted in the first 10 minutes, corresponding to 3-4 km distance from the source downwind. Thus inhabitants living within the 3-4 km radius are potentially exposed to power plant emissions.

We have been developing a coherent "white light" lidar using a terawatt laser system at 800 nm with a 9m length krypton gas cell, which emits a coherent supercontinuum from UV to near infrared regions. Linearly polarized supercontinuum was transmitted to the atmosphere, and backscattered light was collected with a telescope of 31.8 cm in a diameter and the light was separated into 3 to 5 wavelengths using dichroic mirrors and interference filters. Mainly, we used the wavelengths of 450, 550, 700nm and 800 nm with each bandwidth of 10 to 40 nm. Although, the energy of light included in each wavelength range is restricted, the advantage of multi-spectral features on the same optical axis of this system enables us to use preferred spectral lines for various measurements. The system was successfully applied as a depolarization lidar as well as a multi line Mie scattering lidar for cloud particles and Aeolian dusts. By comparing the response for each spectrum, we can determine the size of particles with information on their shapes. Current research is focused to find applications in near infrared region of the white light.

Sea surface temperature (SST) is both an important variable for weather and ocean forecasting, but also a key indicator of climate change. Predicting future SST at different time scales constitutes an important scientific problem. The traditional approach to prediction is achieved through numerical simulation, but it is difficult to obtain a detailed knowledge of ocean initial conditions and forcing. This paper proposes a improved prediction system based on SOFT proposed by Alvarez et al and studies the predictability of SST at different time scales, i.e., 5 day, 10 day, 15 day, 20 day and month ahead. This method is used to forecast the SST in the Yangtze River estuary and its adjacent areas. The period of time ranging from Jan 1st 2000 to Dec 31st 2005 is employed to build the prediction system and the period of time ranging from Jan 1st 2006 to Dec 31st 2007 is employed to validate the performance of this prediction system. Results indicate: The prediction errors of 5 day,10 day,15 day, 20 day and monthly ahead are 0.78°C,0.86°C,0.90°C,1.00°C and 1.45°C respectively. The longer of time scales prediction, the worse of prediction capability. Compared with the SOFT system proposed by Alvarez et al, the improved prediction system is more robust. Merging more satellite data and trying to better reflect the real state of ocean variables, we can greatly improve the predictive precision of long time scale.

The retrieval of MTSAT multi-spectral satellite image rainfall intensity field was studied, with which the "Unit-Feature Spatial Classification (UFSC) method" was proposed to become the foremost basis of the possibility of continuous observation of real-time precipitation from geostationary satellite. In this method, MTSAT multi-spectral satellite measured value and measured precipitation rate from high density ground stations of plum rain season in east china (Jiangsu Province, Zhejiang Province and Anhui Province) in 2007 are combined to conduct the cooperative analysis, and therefore the distribution features of the level of each precipitation probability and each precipitation intensity are well established on different two-dimensional and three-dimensional spectral feature spaces. On the basis, the discrimination matrices, correspondingly, are established for precipitation probability and precipitation intensity of different spectral combinations. Different spectral combinations are used for the construction of the discrimination matrices of the day and the night, respectively. For the day, IR1 (11µm), IR3 (6.7μm), VIS (0.7m), IR12 (T_IR2-IR1) and IR13 (T_IR3-IR1) are available, among which IR1, VIS and IR3 (or IR13) are mainly used ; for the night, IR1, IR3, IR4 (3.7μm), IR12, IR13, IR14 (T_IR4-IR1)and IR24 (T_IR4-IR2) are available and IR1, IR3 and IR24 (or IR14) are mainly used. The contrast test between the observed data of precipitation and the retrieval results based on precipitation data from basic stations and reference stations in China in 2007 shows that, 30% precipitation probability can ideally distinguish precipitation area from non-precipitation area; and the analysis of precipitation intensity category also matches well with the fact. It is well known that the observation of satellite is instantaneous one time per hour while the rain gauge observation is an accumulative process during an hour. The error study further suggests that the difference between the two observation methods is the vital cause of the relative error.

The purpose of this research is to study the effect of nonuniform vertical profiles of chlorophyll concentration on apparent optical properties with Radiative transfer model Hydrolight. The vertical profiles of chlorophyll concentration were approximated according to a Gaussian function(Lewis et al, 1983).The simulated AOPs for nonuniform chlorophyll profiles were compared with those for homogenous ocean whose chlorophyll concentration was identical to the background chlorophyll concentration of inhomogenous cases. The results reveal that the subsurface maximal chlorophyll concentration increase remote sensing reflectance in the blue wavelength and decrease it in the green wavelength, and nonuniform vertical profiles of chlorophyll concentration change the diffuse attenuation coefficient profiles and the angular structure of the light field in the seawater.

Nanji Islands National Natural Reserve is a very representatively marine protected area (MPA) in China. The MPA is built for protecting shellfish, algae and their inhabit environment. The purpose of this paper is to develop a special geographical information system to manage the biodiversity data and environment data. Basic geographic data are collected by topographic maps, chart maps and high resolution remote sensing. More than four times survey data are collected since 1992, including shellfish and macro benthic algae species data, water body and tide flat environment data. All of geographic data and biodiversity data are imported into geodatabase created with ArcGIS. Then some applied function is developed for display, manage and analyze the basic geographic and biodiversity data. Finally, some applications with Nanji Islands biodiversity geographical information system are showed.

The aim of this project is to improve the characterization of radiative and microphysical properties of aerosols and clouds in the atmosphere. These two atmospheric components and their interactions are among the main sources of uncertainty in the numerical forecast of climate change. In this context, we have designed a new airborne polarimeter for measuring directional, total and polarized radiances in the 440 to 2200 nm spectral range. This instrument is based on the POLDER concept, instrument that is currently aboard the PARASOL microsatellite. This new sensor consists in two optical systems for the visible to near infrared range (440 to 940 nm) and the shortwave infrared (940 to 2200 nm). Each optical system is composed of a wide field-of-view optics (114° and 105° respectively) associated to two rotating wheels for interferential filters and analysers respectively, and a 2D array of detectors. For each channel, the total and polarized radiances are computed using the measurements performed with the three analysers shifted by an angle of 60°. Thanks to the large field of view of the optics, any target is seen under several viewing angles during the aircraft motion. This type of instrument has been designed for the retrieval of optical thickness and microphysical properties of aerosols as well as for the determination of microphysical, macrophysical and radiative properties of clouds. In this paper, we will present this new instrument design and some preliminary results recently obtained during the first field campaign in May 2008 over Europe.

The goal of this study is to classify the coconut fields, observed on remote sensing images, according to their spatial distribution. For that purpose, we use a technique of point pattern analysis to characterize spatially a set of points. These points are obtained after a coconut trees segmentation process on Ikonos images. Coconuts' fields not following a Poisson Point Process are identified as maintained, otherwise other fields are characterized as wild. A spatial analysis is then used to establish locally the Poisson intensity and therefore to characterize the degree of wildness.