Airborne hyperspectral remote sensing technique has advantages of flexibility, wide coverage and high spatial and spectral resolution, so is suitable for the coastal water environment monitoring. This paper summarizes the techniques and their applications of marine airborne hyperspectral remote sensing in China. As far as the techniques are concerned, the characteristics of PHI, a spectrometer imager fit for marine application are introduced. Concerning applications, with an aim at the difficulties in airborne remote sensing monitoring, such as the identification of red tide organism species, detection of oil film and the calculation of sea ice intensity, a detailed description is given to the application level of airborne hyperspectral remote sensing in China. Based on the requirement of national marine environment and disaster monitoring and the development trend of marine airborne sensing, the operational application prospect of marine airborne hyperspectral remote sensing is given.

The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) is the first hyper-spectral remote sounding system to be orbited aboard a geosynchronous satellite. The GIFTS is designed to obtain revolutionary observations of the four dimensional atmospheric temperature, moisture, and wind structure as well as the distribution of the atmospheric trace gases, CO and O₃. Although GIFTS will not be orbited until 2005, a glimpse at its measurement capabilities has been obtained by analyzing data from a series of aircraft flights of the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Test-bed- Interferometer (NAST-I). In this paper we review the GIFTS experiment and empirically assess measurement expectations based on meteorological profiles retrieved from the aircraft data.

Development in the mid 80s of the High-resolution Interferometer Sounder (HIS) for the high altitude NASA ER2 aircraft demonstrated the capability for advanced atmospheric temperature and water vapor sounding and set the stage for new satellite instruments that are now becoming a reality [AIRS (2002), CrIS (2006), IASI (2006), GIFTS (2005/6)]. Follow-on developments at the University of Wisconsin-Madison that employ interferometry for a wide range of Earth observations include the ground-based Atmospheric Emitted Radiance Interferometer (AERI) and the Scanning HIS aircraft instrument (S-HIS). The AERI was developed for the US DOE Atmospheric Radiation Measurement (ARM) Program, primarily to provide highly accurate radiance spectra for improving radiative transfer models. The continuously operating AERI soon demonstrated valuable new capabilities for sensing the rapidly changing state of the boundary layer and properties of the surface and clouds. The S-HIS is a smaller version of the original HIS that uses cross-track scanning to enhance spatial coverage. S-HIS and its close cousin, the NPOESS Airborne Sounder Testbed (NAST) operated by NASA Langley, are being used for satellite instrument validation and for atmospheric research. The calibration and noise performance of these and future satellite instruments is key to optimizing their remote sensing products. Recently developed techniques for improving effective radiometric performance by removing noise in post-processing is a primary subject of this paper.

This study presents a new technique for the separation of land surface infrared emissivity and surface skin temperature using high spectral resolution infrared observations. High spectral resolution observations of upwelling radiance at 20 km altitude were obtained by the Scanning High-resolution Interferometer Sounder (S-HIS) aboard the NASA ER-2 aircraft during the TX-2001 experiment. These aircraft observations are used in conjunction with complementary ground-based observations of downwelling radiance at the surface to estimate the surface skin temperature and absolute emissivity for a region in north central Oklahoma, USA. Coincident MODIS Airborne Simulator (MAS) observations are used to quantify the land surface variability within the S-HIS scene in the vicinity of the DOE ARM Southern Great Plain central facility. Ground truth data is presented from a ground based Scanning Atmospheric Emitted Radiance Interferometer. This remote sensing technique has application to satellite based observations from the NASA AIRS, the NPOESS CrIS, the EUMETSAT IASI, and the NASA GIFTS instruments.

Air-OPUS is a hyper spectral imaging spectrograph, with 0.34 nm spectral step, 190-455 nm spectral coverage, and 330 spatial channels covering 15 degrees field of view (FOV). It is designed as an airborne instrument for the demonstration of spaceborne-OPUS. After two-demonstration campaign using the Gulfstream-II aircraft, the performances of AIR-OPUS, such as spectral resolution, signal-to-noise ration (SNR) have been evaluated. It is concluded that the performances have agreed with designed value. This paper describes design, the performance, and the first results of Air-OPUS. Concept of next generation Air-OPUS, with wider FOV and visible/near-IR spectral coverage, will be also briefly presented.

Analytical procedure to derive the ozone concentration profile from the analysis of the high-resolution spectrum data as observed by a space FTS sensor such as Interferometric Monitor for Greenhouse gases (IMG) onboard Advanced Earth Observing Satellite (ADEOS) has been presented. In the procedure, Jacobian matrices were re-calculated for each spectrum considering the cloud top temperature in the instantaneous field of view (IFOV) of the FTS sensor. That was because these cloud parameters seriously affect the elements of the Jacobian matrices sometimes causing the change of the sign of the elements. This method has been applied to the analysis of IMG data that were observed during the northern hemispheric ozone hole like event occurred in 1997 spring. It has been found that the usage of the precise instrumental line shape (ILS) of the sensor is very important to improve the vertical resolution of retrieval by loosening the retrieval constrains.

Methodology of the Deuterium/Hydrogen (D/H) ratio retrieval based on high-resolution infrared spectra observed by space sensors has been described. Simulated atmospheric radiance in the spectral range of 650-2500 cm^-1 for the case of nadir observation from satellite with resolution of about 0.1 cm^-1 is investigated aiming to find appropriate signals of isotopes of greenhouse gases. Signals corresponding to an atmospheric water vapor isotopomer, HDO, were selected. These signals were identified in Interferometric Monitor for Greenhouse gases (IMG) spectra observed during Advanced Earth Observing Satellite (ADEOS) mission. The developed method includes the following stages: temperature profile retrieval with aerosol correction, H₂O and HDO profiles and their column amounts retrieval, and D/H ratio determination. The method has been applied to the analysis of the IMG/ADEOS data identified as to be observed under clear sky conditions over an ocean area between 80S-80N and 130-170W to determining D/H column amount ratios. The latitudinal distribution of D/H ratio for a short period in December 1996 was obtained.

This paper presents a comparison of the three forward model computational schemes, namely, Emissivity Growth Approximation (EGA), Curtis-Godson Approximation (CGA), and line-by-line (LBL) approach developed for SAGE III water vapor retrieval. For all three schemes, we have incorporated the most recent laboratory measurements of spectral line parameters to avoid the bias which is known to exist in HITRAN-96 database. Discussions are focused on the strength and weakness of each scheme with respect to accuracy and computational efficiency. The computer time for the LBL has been reduced significantly. The advantage of the LBL is manifest when the dependence of EGA and CGA on a huge pre-calculated lookup table and the breakdown of assumptions for these two schemes at lower altitudes are taken into account.

The Japanese Advanced Meteorological Imager (JAMI) introduces next generation technology geosynchronous earth orbit (GEO) imagers for operational meteorological remote sensing. Raytheon Santa Barbara Remote Sensing is building JAMI for Space Systems/Loral as the imager subsystem for Japan’s MTSAT-1R system. JAMI represents the best balance between heritage and newer space-qualified technology and meets all Japan Ministry of Transport MTSAT requirements from beginning to end of life with considerable margin, using a simple, inherently low risk design. The advanced technology built into this image benefits operational meteorological imaging for Japan, East Asia and Australia by enabling significantly better radiometric sensitivity and absolute accuracy, higher spatial resolution and faster full disk coverage times than available from current GEO imagers.

EarthCARE (Earth Clouds, Aerosol and Radiation Explorer) project is a candidate of the ESA (European Space Agency) Earth Explorer Core Missions. There are many uncertainties mainly caused by aerosols, clouds and their interaction with radiation in predictions of climate change using numerical models. EarthCARE will provide vertical and horizontal distributions and physical characteristics of clouds and aerosols, and also provide the Earth radiation budget. EarthCARE is the joint proposal between ESA, National Space Development Agency of JAPAN (NASDA) and Communications Research Laboratory (CRL). The Phase-A study is going on. The EarthCARE satellite has five sensors, Cloud Profiling Radar (CPR), ATmospheric LIDar (ATLID), Multi-Spectral Imager (MSI), Broad Band Radiometer (BBR) and Fourier Transform Spectrometer (FTS). NASDA is studying FTS design. Main objective of EarthCARE FTS is to provide spectrally resolved outgoing radiance. This spectrum has many useful signatures from the surface/cloud/aerosol/water which can not get from spectrally integrated measurement. Another objective of EarthCARE FTS is a compact Michelson interferometer, which covers from 5.6 µm to 25 µm with 0.5 cm^-1 spectral resolution. The FOV (Field Of View) is 10km so that the data can be used in conjunction with BBR.

The RAMOS program embodies a new direction for cooperative space-based cooperative research and development between the Russian Federation and the United States. The planned system configuration is a constellation of two satellite constellation orbiting in approximately in the same plane and at an altitude of about 500 km. These satellites, equipped with passive electro-optical sensors operating from infrared (IR) to ultraviolet (UV), are designed for near-simultaneous stereo-optical measurement capability. The projected launch date is 2007 with an on-orbit lifetime of two years minimum and five years possible. The environmental objectives are: 1. Measuring cyclones to predict their future strengths and paths, 2. Measuring fires and winds to demonstrate location and assessment capability, 3. Measuring volcanic plumes in three dimensions 3-D measurements of volcanic plumes for to assess aircraft hazards, 4. Measuring global three-dimensional wind velocities, 5. Measuring water vapor profiles at the 100-meter scale, 6. Obtaining a three-dimensional multi-spectral background data base in the mid-wave infrared, visible and ultraviolet wavelength regions and making infrared and visible polarization measurements of solar scattered backgrounds.

Monitoring tropospheric chemistry from space is the next frontier for advancing present-day remote sensing capabilities to meet future high-priority atmospheric science measurement needs. Paramount to these measurement requirements is that for tropospheric ozone, one of the most important gas-phase trace constituents in the lower atmosphere. Such space-based observations of tropospheric trace species are challenged by the need for sufficient horizontal resolution to identify constituent spatial distribution inhomogeneities (that result from non-uniform sources/sinks and atmospheric transport) and the need for adequate temporal resolution to resolve daytime and diurnal variations. Both of these requirements can be fulfilled from a geostationary Earth orbit (GEO) measurement system. The Tropospheric Trace Species Sensing Fabry-Perot Interferometer (TTSS-FPI) was recently selected for funding within NASA’s Instrument Incubator Program (IIP). Within this project we will develop and demonstrate a multispectral imaging airborne system to mitigate risk associated with an advanced atmospheric remote sensor intended for geostationary based measurement of tropospheric ozone and other trace species. The concept is centered about an imaging Fabry-Perot interferometer (FPI) observing a narrow spectral interval within the strong 9.6 micron ozone infrared band with a spectral resolution ~0.07 cm^-1. This concept is also applicable to and could simplify designs associated with atmospheric chemistry sensors targeting other trace species (which typically require spectral resolutions in the range of 0.01 - 0.1 cm^-1), since such an FPI approach could be implemented for those spectral bands requiring the highest spectral resolution and thus simplify overall design complexity. The measurement and instrument concepts, approach for development and demonstration within IIP, and a summary of progress-to-date will all be reported.

Global measurements of atmospheric carbon dioxide (CO₂) are needed to resolve significant discrepancies that exist in our understanding of the global carbon budget and, therefore, man's role in global climate change. The science measurement requirements for CO₂ are extremely demanding (precision <0.3%) No atmospheric chemical species has ever been measured from space with this precision. We are developing a novel application of a Fabry-Perot interferometer to detect spectral absorption of reflected sunlight by CO₂ and O₂ in the atmosphere. Preliminary design studies indicate that the method will be able to achieve the sensitivity and signal-to-noise required to measure column CO₂ at the target specification. We are presently engaged in the construction of a prototype instrument for deployment on an aircraft to test the instrument performance and our ability to retrieve the data in the real atmosphere. In the first 6 months we have assembled a laboratory bench system to begin testing the optical and electronic components. We are also undertaking some measurements of signal and noise levels for actual sunlight reflecting from the ground. We shall present results from some of these ground based studies and discuss their implications for a space based system.

FIRST (a NASA Instrument Incubator Program) is a balloon-based demonstration of a space-based sensor to measure the Earth’s thermal infrared at high spatial and spectral resolution. The radiative balance of the troposphere, and hence climate, is dominated by the infrared absorption and emission of water vapor, particularly at far-infrared (far-IR) wavelengths longer than 15 µm (650 cm^-1), the distribution of water vapor and its far-IR radiative forcings and feedbacks are major uncertainties in understanding and predicting future climate. However, far-IR emission (spectra of band-integrated) has rarely been directly measured from space platforms. FIRST will be a Fourier Transform Spectrometer (FTS) with radiometric calibration in the spectral range from 10 to 100 µm (1000 to 100 cm^-1) at 0.6 cm^-1 unapodized resolution. It will incorporate a broad bandpass beamsplitters and a high-throughput optical and detector system. FIRST has a NEΔT performance goal of 0.2K from 10 to 100 µm. The spectral resolution will allow simultaneous retrievals of temperature and water vapor profiles. A 10 × 10 array of 10 km IFOVs is desired isolate clear and cloudy fields of view, while providing daily global coverage capability.

Stratospheric Platform (SPF) project is an enterprize to develop an airship to float at the altitude of 20 km for the use of earth observations and telecommunications. SPF-II is one of the steps toward realizing SPF to examine the stabilized flight of an airship at the altitude of 4 km, and is planned to be aloft in 2004. The earth observatoin facility on SPF-II will consist of three sensors: a visible-near infrared (VIS-NIR) sensor for the wavelength region 500 -- 1000 nm, a thermal infrared (TIR) sensor, and a trafic-monitoring sensor. In this paper, we present an outline of VIS-NIR and TIR sensors. The VIS-NIR and TIR sensors are planned as wide field (110 degree) imagers with 2-dimensional FPAs. Polarizetion will be measured with the VIS-NIR sensor. FOV of the VIS-NIR sensor is to be 8 km square at the footprint, and horizontal resolution to be 8 m with a 1280 × 1024 pixel Si-CCD FPA. The TIR sensor adopts an uncooled 320 × 240 pixel bolometer array, and has a FOV of 8 km × 6 kmsquare at the footprint, with horizontal resolution of 25 m. It covers three wavelength bands of 8.5, 10.8, and 12.0 μm with the filter wheel device.

In this paper we present an experimental system of miniature imaging spectrometer based on Acousto-Optic Tunable Filter (AOTF). The operating principle of AOTF and the properties of imaging spectrometer based on AOTF are introduced. The configuration of the AOTF device incorporated to the imaging spectrometer is described and the measured performance of the filter is summarized. The single beam configuration of the AOTF device and the utilization of a CMOS imaging IC as the focal plane sensor make the optics of the system very small, simple and compact. The power compensating circuit design of the RF driver of the acousto-optic cell ensures relatively high and consistent diffraction efficiencies over the whole tuning range of the filter. Qualitative experiments are carried out in laboratory. Results of the experiments preliminarily illustrate the capability of the miniature AOTF imaging spectrometer in hyperspectral remote sensing application.

The DOAS technique is currently the developing trend and the main technique of online monitoring of tropospheric air quality measurements. In order to enlarge the scope of monitoring with only one set of instrument, we recently developed an multi-path LP-DOAS system in which we put several sets of retroreflectors at their own appointed remote places, each makes a measuring lightpath when the telescope aligns with it. In this way we can determine high spatial resolution and two or three-dimensional trace gas distributions of a larger region with the telescope as its center. We developed a stepping-motor-based mechanics-electrical device to drive the telescope. Under the control of a PC the telescope can automatically scan these retroreflectors one by one in continuous measure cycles.

An imaging spectrometer (IS) can get continuous spectrum and acquire the image of the observed object, and it is used widely in the fields of remote sensing, industrial inspecting, etc. A compact imaging spectrometer system based on computed-tomography principle by using a special designed binary phase grating is described in this paper. The computed tomography imaging spectrometer (CTIS) records the projection data of different direction at the same time. The data cube of the object is acquired by reconstruction of the projection data. The instrument can record both spectral and spatial information of a dynamic scene. As only a 2-D binary phase grating is used as splitter and disperser, there are no moving parts, the system of CTIS becomes very compact. As the key component, the characteristics of grating are important to system stability and accuracy of reconstruction. In our work, the grating is designed and fabricated, and the whole system is set up. The configuration of the system is presented and the method of the spectral and spatial calibration is introduced. The mapping matrix of system is established by the results of calibration. The real object such as a colorful doll or a cluster of flower is imaged by the CTIS. The data cube of the real object is reconstructed by the EM algorithm. The size of the image of the object is about 200*200pixel, and the spectral range is from 410nm to 700nm. The spectral resolution is 10nm which depends on the step of spectral calibration. The accuracy of reconstruction and SNR is analyzed. The experimental results are presented, and the work is proven to be encouraging.

Some correlation analysis between hyperspectral data and chlorophyll-a, chlorophyll-b and carotenoid contents of leaves in different sites of rice were reported in this paper. Hyperspectral data of late rice in whole growing stage between 1999 and 2000 have been measured by using the ASD FieldSpec UV/VNIR (350-1050nm) Spectroradiometer with resolution of 3nm. The pigment contents of rice leaves, including chlorophyll-a, chlorophyll-b and carotenoid content in different nitrogen levels, have been measured. There are strong correlation among the pigments. The correlation coefficient between chlorophyll and carotenoid reaches the extremely significance level. The chlorophyll-a content of upper leaf was well correlated with the spectral variables. The potential of hyperspectral data for estimating chlorophyll-a of upper leaves was evaluated using univariate correlation and multivariate regression analysis methods with different types of predictors. Results show that the best prediction of chlorophyll-a of upper leaves was obtained with some hyperspectral variables such as SDr, SDb and their integration.

To improve our understanding of photon transporting inside leaves, and hence improve the accuracy of yield estimating and growth monitoring of rice by remotely sensed data, we simulated rice leaf reflectance by PROSPECT model. The experiment, which were referred to as the late rice experiment, were conducted at Zhejiang University in 1999 and 2000 with one species of rice (which is called Xiushui 63); In 1999 the rice was planted normally, but in 2000 it was fertilized in three different levels (low, medium and high). Leaf spectrum (reflectance and transmittance), biochemical concentration such as chlorophyll, protein, cellulose, lignin and water content, and leaf area were measured during the experiment. By the PROSPECT model, we simulated leaf reflectance on four days’ data set in 1999 and one day’s data set of three fertilizations in 2000. The correlation coefficients between actual and simulated values are more than 0.995, the RMSE values are less than 0.0212. On the other hand, the model has been inversed to estimate chlorophyll concentration. Compared with actual value, the comparative errors are less than 10%.

The shift of the reflectance red edge parameters is a known phenomenon documenting changes in the biological status and biochemical concentration of plants. In this paper, firstly, the inverted-gaussian (IG) reflectance model was analyzed, and the related reflectance red edge parameters, such as red edge position, λ_p, absorption peak position λ_o and absorption width σ, were derived. It is absolutely reliable to simulate wheat canopy reflectance red edge by IG model, because the coefficients of determination, R², between the 403 reflectance red edges (sampled from winter wheat tillering stage to milking satage) and the fitted IG models are large than 0.98. Secondly, red-shifted was found with an early slow increase in the value of λ_p, λ_o in winter wheat’s tillering, jointing, booting and heading stages; Blue-shifted was found with a late decrease in the value of λ_p, λ_o in the seed forming and milking stage. Finally, strong correlations were observed between the reflectance red edge parameters and foliar biochemical contents, such as chlorophyll, total nitrogen, sugar, water, from field spectra. The results demonstrated the use of remotely sensed estimates of red edge parameters for estimating biochemical contents, and also indicated the potential of hyperspectral data for precision agriculture.

The hyperspectral image used in this study was acquired by the airborne operative modular imaging spectrometer (OMIS) in Xiaotangshan area, Beijing, on April 26th, 2001. Accurate geometry correction and reflectance transformation was conducted on this image so that 43 image spectra were extracted to match with the canopy-level total nitrogen concentration (TN) of wheat precisely. By using methods of stepwise regression and spectrum feature analysis, characteristic bands and parameters were selected and developed for TN retrieval from the image spectra. Nitrogen distribution map was obtained by applying the best estimation equation to all wheat pixels. It turned out, the absorption depths and areas within spectral ranges 590-756nm,1096-1295nm and 1295-1642nm could be used to estimate TN. NDVI(NRCA1175.8,NRCA733.9) and NDVI(dr745,dr699.2) was the best estimator of TN (R2 = 0.8145 and 0.769 respectively). In addition, the value and distribution of TN map was quite consistent with the field measurements and growth status.

The direct broadcast Terra/MODIS data has been utilized in Korea Meteorological Administration (KMA) since February 2001. This study introduces utilizations of this data, especially for the derivation of sea surface temperature (SST). For an operational production of the MODIS SST, we have derived a new set of MCSST coefficients by using a simple cloud mask algorithm and by assumption of NOAA daily SST as a true SST. The current NASA’s PFSST and new MCSST algorithms are analyzed by using the collocated buoy observations in the East Asia region. Although the number of collocated data was limited, both algorithms have high correlation with the buoy SST, but somewhat bigger bias and RMS difference than we expected. And PFSST uniformly underestimated the SST. Through more analyzing the archived and future-received data, we plan to derive better MCSST coefficients and apply to MODIS data of Aqua. To use the MODIS cloud mask algorithm to get better SST coefficients is going to be prepared.

The Spectral Identification Tree (SIT) based on diagnostic absorption spectra of minerals was designed and developed to extract minerals directly. The spectral absorption features of different ions or bonds such as CO₃²⁺, Fe²⁺, Fe³⁺, Mn²⁺, Al-Oh and Mg-Oh and so on, of some minerals were summarized. Some spectral identification trees (SIT) and decision rules from various ions to minerals were established using IF-THEN rules which based on some spectral absorption features. Various spectral absorption features which were combine by logistic relationship were used to extract and discriminate different levels’ minerals (e.g. mineral group and mineral) in SIT technique. Information of ions, such as CO₃²⁺, Fe²⁺, Fe³⁺, Mn²⁺, Al-OH and Mg-OH, and of some minerals, such as alunite, montmorillonite, muscovite, halloysite, smect-kaolinite and illite were identified and extracted effectively by SIT technique using AVIRIS data at Cuprite, Nevada of USA, which was a test area.

Vegetation indices have been widely used by the remote sensing community to monitor vegetation from space, both on regional and global scales. However, vegetation indices are sensitive to the illumination and viewing geometry. In order to assess this sensitivity, spectra of the five species of plant leaves were collected under the different illumination and viewing geometry. It was demonstrated that when the illumination angles were altered, the leaf spectral amplitudes would change; the vegetation indices would increase with the illumination angles. But the influences of the illumination angle alterations on the vegetation indices were different with the different sensors. For the vegetation index NDVI, the influences on AVHRR were the least, the largest of MODIS. But for the vegetation index SR, the influences on MODIS were the least, the largest of AVHRR. The vegetation index NDVI was also proved to be the more reliable than the vegetation index SR.

Measurement of spectral remote sensing reflectance is essential to characterize water color, and to further estimate various water constituents with bio-optical algorithms. The measurement is critical to satellite data calibration/validation as well as to bio-optical algorithm development. Unfortunately, commercial instruments for such measurement are expensive, and they are either not capable of displaying data in real-time or not easy to use in coastal environment where large vessels are not applicable. In this paper we describe a simple instrument for such measurement. The fiber-optic Ocean Optics S2000 spectrometer, originally designed for lab use, was further developed to measure remote sensing reflectance. Compared with concurrent measurements from other expensive commercial instruments over different water bodies, the measured spectral reflectance is nearly identical (mean RMS difference < 2%). Through linearity and sensitivity analysis we found that it is capable of characterizing a variety of water types, even though the sensitivity is not as high as its commercial counterparts. The instrument substantially reduces the cost; it has real-time display and is easy to operate (< 0.5 kg) on small vessels. Further, combined with a liquid waveguide and a light source it is also capable of measuring Gelbstoff absorption with sufficient accuracy.

Nansihu lakes are important water conservancy hinge on the east line project of Translating South Water to North. In this paper, associating with the environment investigation and estimation on the south west of Shandong, we have a dynamic detection on their water quality and water areas with remote sensing covering more than 1300 kilometers. Using the data getting at low water time (Mar.28.2001 CBERS-CCD) as well as at abundant water time (Sep.6.1994 TM), combining with sampling test data on the spot and other remote sensing information, we have an iterative classification on images getting at different time. The result shows that the difference of regional water areas above the Second Level Dams of Nansihu lakes is about 169 square kilometers between low water time and abundant water time. From the images, three classes of water can be separated, including great area wet land. The area of the first class water is 13.3 square kilometers, the second class is 102.7 square kilometers, and the third class is 345.5 square kilometers. All these classes have an obvious relativity with the chemical indexes of water pollution, such as Biology Oxygen Demand (BOD) and Dissolved Oxygen (DO) and Suspended Substance (SS), etc.

Through the spectrum energy as its base, marine remote sensing technique can transfer the existing forms and variety information of seawater medium and energy. With the development of remote sensing technique especially quantitative analysis, the research of spectrum characteristic is appealing more and more attention. Surface feature information is becoming much abundant when the data, from the previous AVHRR data, CZCS data to nowadays SeaWiFS data and MODIS data, are available. And the extraction, interpretation and model establishment of remote sensing information depend on marine spectrum characteristics. Marine remote sensing acquires data in many very narrow, continuous spectral bands throughout the visible, near-IR, mid-IR, and thermal IR portions of the spectrum, which fuse the information of image and spectrum. Each pixel has an associated continuous spectrum that can be used to identify and inverse the surface materials. The spectrum data is decided by complicated aggregation which is composed of many materials, for example pure water, inorganic salt, soluble organic material, phytoplankton, chipping, mineral suspend material and so on. Various overlapped information interfere with each other, so that reflected model and spectrum curve of various surface feature is different. The interpretation of surface feature and energy is uncertain, random and changed. It is impossible to consider these factors quantificational and set a whole analysis model therefore it is important to confirm the offered portion of various material in seawater spectrum information. In marine hyperspectral research, material can show diagnostic absorption and reflectance characteristics to confirm parameter and qualification of remote sensing model. The paper reviews the characteristics to confirm parameter and qualification of remote sensing model. The paper reviews the characteristics of marine hyperspectrum technique presently, such as spectral absorb index, spectral derivative, spectral matching, spectral classification et al.

Principle Component Analysis (PCA) is first applied to the optical spectral bands of ETM+ to estimate Suspended Sediment Concentration (SSC). The rationality is analyzed for employing band 1,2,3 to monitor SSC and the limitation of single band is discussed. Based on the spectral feature space images (scatter diagram) of the three bands, we provide the approach of estimation of SSC utilizing PCA. Case study shows that the first and the second principle components are suitable to estimate SSC. Especially the first principle component is a potential variable for the fine estimation of SSC.

The conventional method used to measure the total suspended solids (TSS) in seawater is by collecting samples and analysing them in the lab. This method is not efficient and cannot provide a real-time result, whereas, digital image processing and remote sensing techniques have been widely used in estimating and mapping the concentration of the TSS in vast areas. Various algorithms have been developed and used for the measurement of TSS concentration. In this work, an algorithm developed for remote sensing techniques is used. The technique employed involves radiating the samples with a laser and then correlating the back-scattering with the concentration of the total suspended solids in the water sample. A laser emitting multiple wavelengths are radiated into the water sample and back-scattering radiations for every wavelength are analysed and correlated with the total suspended solids concentration. The back-scattering radiation is then analysed and the proposed water quality algorithm is calibrated for measuring the total suspended solids level in the water. In this work the total suspended solids concentration is correlated with the ratio of back scattering radiation of wavelengths 780nm and 633nm. The linear correlation coefficient square (R²) between the spectrometer reading and the laboratory analysis produced in this work is 0.98.

The paper quantitatively analyzed the relationship between suspension sediment (soil) content and water spectral reflectance with the data tested with FieldSpec FR spectrometer. Then discussed the factors influencing water reflectance. After comparing the results from regressing analysis of reflectance and contents of soil at each wavelength from 350nm to 2500nm, the optimum band (wavelength) was found. The results were proved by another group of data. The conclusion would be helpful in estimating soil content of sea, river or flood with hyperspectral remote sensing, and evaluating soil erosion within water system.

RS/GIS/GPS is a series of efficient techniques for acquiring, managing and analyzing geographic information. This paper describes the using of these techniques in the Entironment investigation of Minjiang Upriver, based on national 863 projects 308 mission Xibujinjinxingdong sub-mission. With the help of forestry, water resource and agrology techniques, a main routine of work flow are introduced. It mainly comprises seven steps: (1) Collect related data, thematic maps, such as Land Use Maps and Forest Maps, were gathered; (2) Select the raw remote sensing images with thinking of the vegetation properties and the scale of target map. A red, green and blue (RGB) colors composite of Landsat TM’s band 432 is selected as the information sources;(3) Process and interpret the remote sensing images with ortho-image technique and interactive working method. As a result, 46 digital maps of 1:100,000 scale was produced;(4) perform field work or inspect on the spot with the help of GPS. More than 2000 kilometers routine and 294 patches was validated,;(5) Second time Interpretation;(6) Design and create the geodatabase. Not less than 20 layers was designed to contain necessary geo-information; and (7) Acquire, edit and store spatial data with the help of GIS software. After all these works, some spatial analysis is made. It clearly reveals large changes between 1990 and 2000: Nature forest area has decreased about 65000 ha; Manually planted forest has increased about 60000 ha; Grassland and plow land have been decreasing in various level; Arid valley has the tendency to enlarge. According to some forestry study, main reason such as over felling the forest, tillage on steep mountain slopes in upper river and government behavior is discussed to interpret these large changes in the end of this paper.

This paper study considers the effects of oil exploration and development in the oilfields of Evenkiya, Central Siberia (60°30^’N/96°30^’E). The drilling in this area was initiated in 1970, and the first oil was extracted in 1977. Image data from the US’ Landsat-7, the Russian “Resours”, and the European ERS-2 remote sensing satellites were analyzed. The information value of the Landsat-7 channels was evaluated. In particular, the fresh oil drilling sites effectively differ from old ones in the third (0.63-0.69 µm) and fourth (0.75-0.90 µm) channels. Recently burned areas are detectable in the middle IR (1.55-1.75, 2.08-2.35 µm). The classification accuracy depends on the number of channels used, but does not improve greatly using more than 4 or 5 channels. Landsat-7 scenes enable the detection of patterns for parallel strips (5-10 m in width) of cut forest, the first sign of the oil reconnaissance. Alongside the direct impacts of oil-exploitation, fire frequency was increased. The “big” fires (area>200 ha) caused ~90% of the total damage, but only accounted for 10% of total firescars. The area of human-caused impact is ~20% of territory, which is ~2.5 higher than average for known oil development areas within the Landsat scene. The ERS-2 scenes were found to be effective for mapping fresh drilling sites only. The comparative analysis of “Resours” KFA-1000 camera scene (June 1984) and Landsat-7 (October 1999) showed that during this period the number of oilrigs increased nearly 5 times. Generally, the Landsat-7 data are effective for early detection of the anthropogenic impact on the Siberian larch-dominated communities.

Usually the spectral unmixing and endmember extraction were based on the spectral statistics algorithm. In this paper, spatial knowledge, such as field patch information, was involved in the pure pixel selecting. In this way, endmember extraction was not only carried out in spectral space but also considering the spatial location of pixels. In addition, these known background information can also improve the accuracy of image classification, and also can be used to intellectually separate pixels and evaluate each sub-pixels different attributes.

Given the unprecedented volume of data (>72 Megabits per second) that will be generated by the future NOAA Geostationary Operational Environmental Satellite (GOES-R and beyond), the use of innovative data compression techniques will be essential if continuous downlink and re-broadcast from geo-orbit are to be economically feasible. A team of scientists and engineers from the Cooperative Institute for Meteorological Satellite Studies (CIMSS) of the University of Wisconsin-Madison, Offices of Research and Applications and Systems Development of NOAA/NESDIS, NASA/GSFC, and The Aerospace Corporation (a Federally Funded Research and Development Center) has been assembled to study the development of data compression for the next generation GOES sounder. This study is intended to define some feasible approaches for achieving both on-board (lossless) and ground-based (lossy or lossless) data compression. In general, on-board systems have substantially limited processing and storage capabilities, and modest compression ratios, compared with those of ground-based systems. Both highly efficient lossless and lossy algorithms therefore need to be developed to meet both on-board and ground processing objectives. In particular, innovative compression techniques for optimal quantization, transformation, coding, and decoding in interferogram or spectral domains will be essential for practical NOAA real-time operational data processing and distribution. In this presentation we will clearly define testing data sets (real and simulated), approaches, performance and feasibility of achieving hyperspectral data compression to provide a manageable data rate.

An IKONOS image was used to examine the spatial complexity of the band spectra of remote sensing. Triangular prism method and double blanket method were applied to calculate the fractal dimensions of all bands for each land cover type. The results show the image texture characteristics of the images by bands and land cover types. As the conclusions, the fractal dimensions of all bands of each land type range between 2.0 and 3.0. But different type sub-images show different complexities, thus different dimensions. Dimension values reflect spectral characters and spatial characters of sub-images. Thus, it is believed that the measurement and analysis of land cover can be more effectively and efficiently realized using fractal characterization of high spatial and spectral resolution remote sensing data.

CBERS-1 images are assessed in this paper with image information capacity and power spectrum. Through comparison the same areas of CBERS-1 image and TM image, the CBERS-1 image quality is reflected impersonality. Experiments result shows that CBERS-1 image have the approximately same image quality as TM image both in information abundance and in texture feature, and it has fine image quality in comparison.

The canopy spectra of rice under different nitrogen levels were studied. Some red edge parameters in the first derivative reflectance curve (wavelength, amplitude and area of the red edge peak) were used to evaluate rice leaf chlorophyll, LAI. Red edge positions move to longer wave bands till booting stage and move to short bands after booting stage. A high correlation was found between chlorophyll content of top leaves and the wavelength of the red edge position and between LAI and the red edge parameter. Then, the red edge was found valuable for assessment of carotenoid or albumen-nitrogen or non-albumen-nitrogen and the wavelength of the red parameters. Some red edge parameters are one of the best remote sensing descriptors.

An imaging spectroscopy with new principle is presented in this paper. We call this imaging spectroscopy as LASIS (large aperture static imaging spectroscopy). The LASIS possesses the advantages of lighter weight and higher sensitivity. It can be widely used for the mitigation of natural disasters such as forest fire, earthquake and flood, for the general survey of crops distribution, insect pests and estimation the yield of crops. First, a brief depiction of Imaging Spectroscopy and its application is introduced in this paper. Second, Principle of LASIS is presented along with its main innovations and characteristics. Third, an instrument designed for testing its principle is introduced, which have 85 millimeters focal length, 4.2 degrees field of view, 1:8F number. At last, the experimental results with 100 numbers of spectral bands are given. We can conclude form the results that the LASIS can solve the energy problem of Dispersive imaging spectroscopy because it really have the advantages of high throughput and high sensitivity.

In the hyperspectral remote sensing, the continuum-removed method is used only with the spectrum of a single pixel to analyze spectrum and extract the feature bands useful with the classification. While in this paper, based on the continuum-removed algorithm, we programmed with Visual C++ to fulfill the functions of the continuum removed to the whole hyperspectral image, normalizing and extracting the feature space for the classification. At last, aiming at the former image and the after-continuum removed image, the classification results of the MLC and SAM are compared.

Satellite temperature will fluctuate during the circle from the Sun light to the Earth shadow, which may disturb the focusing job of the camera. That's the reason for positive thermal control been chosen for some satellites, particularly for the camera system. While for a micro satellite, considering the constraints of it, passive thermal control was preferred. The temperature range of camera will be a main consideration during micro satellite design. Hangtian-Tsinghua-1 (HT-TH-1) micro satellite, launched at Jun 28, 2000, is a joined mission of Tsinghua University and Surrey Space center. The imaging system on board, which has three cameras with 40-meter resolution, has been working perfectly after launch and a lot of pictures have been acquired. In view of the thermal design, HT-TH-1 has provided a comfortable environment for the satellite: the average temperature was about 25ºC in the past two years. It will be very constructive to study the temperature environment and the thermal design if a high-resolution imaging system is built on micro satellite platform. The telemetry data of temperature of solar panels and subsystem modules since lunched was analyzed in order to understand the main factors for the fluctuation. Finally, a conclusion of passive thermal design for camera is given.

Band selection work is mainly focused on various kinds of vegetables. Two kinds of data are used in this work project. One is the spectral data measured with ASD spectrometer; the other is airborne Push-broom Hyperspectral Imager (PHI) data. The band selection work consists of three parts, bandwidth selection, wavelength range selection, and center wavelength selection. Bandwidths of filters should be in the range 25nm to 50nm because of the angle effect of the bandpass interference filters. Two factors, light source characteristics and the CCD spectral responsivity, confine the filter center wavelength range in the range from 410nm to 810nm.. Methodology used in the center wavelength selection work is spectral correlation-based approaches, maximum relative technique and the linear forward stepwise regression technique. Those two kinds of method have almost the same result. And they are relatively well distributed over the whole spectral domain.

A methodology is considered for the construction of a validation site with reference natural media to study scattering and radiation characteristics of underlying surfaces. The meteorological mast (310-m height) of SPA “Typhoon” was used to locate the spectral scanning instrumentation. The capabilities were discussed of the high meteorological mast and the spectroradiometric equipment developed specially to solve the problems of remote sensing. Presented are the specifications of the equipment and investigation results of some natural media obtained with a high spatial resolution under severely controlled meteorological and illumination conditions.

The objective of this paper was to determine hyperspectral narrow wavebands that are best suited for estimating rice biophysical characteristics. The paper studied the variational process of leaf area index (LAI), leaf chlorophyll density (CH.D) and hyperspectral data during the period of rice growing season. Correlation between hyperspectral data and LAI, CH.D of rice was analyzed. Spectral derivatives technique was used to suppress the effects of low frequency spectral noises on background. Stepwise regression method was used to create multivariate linear equations for predicting LAI and CH.D of rice with the data of reflectance and the first-order derivatives of reflectance as forecast factors. Results show that: 1) The first order derivatives of reflectance spectrum can enhance the correlation and improve the precision of predicting LAI and CH.D; 2) The first order derivatives of reflectance and CH.D more markedly correlate than LAI at some wavelength, CH.D is more available to express crop canopy spectrum information than leaf area index.

Oil spills are very serious marine pollution in many countries. In order to detect and identify the oil-spilled on the sea by remote sensor, scientists have to conduct a research work on the remote sensing image. As to the detection of oil spills on the sea, edge detection is an important technology in image processing. There are many algorithms of edge detection developed for image processing. These edge detection algorithms always have their own advantages and disadvantages in the image processing. Based on the primary requirements of edge detection of the oil spills’ image on the sea, computation time and detection accuracy, we developed a fusion model. The model employed a BP neural net to fuse the detection results of simple operators. The reason we selected BP neural net as the fusion technology is that the relation between simple operators’ result of edge gray level and the image’s true edge gray level is nonlinear, while BP neural net is good at solving the nonlinear identification problem. Therefore in this paper we trained a BP neural net by some oil spill images, then applied the BP fusion model on the edge detection of other oil spill images and obtained a good result. In this paper the detection result of some gradient operators and Laplacian operator are also compared with the result of BP fusion model to analysis the fusion effect. At last the paper pointed out that the fusion model has higher accuracy and higher speed in the processing oil spill image’s edge detection.

We present matrix expression of convex geometry analysis method of hyperspectral data by linear mixing model and establish a mathematic model of endmembers. A 30-band remote sensing image is applied to testify the model. The results of analysis reveal that the method can analyze mixed pixel questions. The targets that are smaller than earth surface pixel can be identified by applying the method.

Atmospheric InfraRed Sounder (AIRS) is a hyper-spectral infrared instrument on the EOS-Aqua satellite. Principal Component Analysis (PCA) of realistic simulations of AIRS radiances, which includes the effects of variable clouds and surface parameters, can be used to estimate and filter AIRS instrumental noise. The PCA uses noise scaled radiance, i.e. radiance divided by noise (R/N). Since the square root of the eigenvalues is equivalent to the standard deviation of the principal component score of the dependent ensemble, the square root of the eigenvalues in the R/N domain can be interpreted as a signal to the noise ratio for the new principal components (PC) or say "abstract channels". New PCs are arranged from the largest to the smallest eigenvalues. Once the R/N ratio is below unity, the signal has less contribution than noise for that PC and all the remaining PCs. This physical meaningful fact can be a criterion for radiance noise filtering. Using the linearity of PCA to the pure signal S plus ideal noise N in the R/N domain, PCA(N/N) becomes PCA(I). I is the identity matrix and hence eigenvalues of I are all equal. If reconstructing I, only k/m information can be recovered by k eigenvectors, where k = 1 .... m eigenvectors. Thus, it is easy to know how much noise merged into the reconstructed radiance and how many eigenvectors are needed for filtering noise when performing PCA in R/N domain. The number of eigenvectors to be used for noise estimating is around 60 in all sky conditions. 60 eigenvectors can filter over 97% of noise. Only 3% noise remains in the reconstructed data. Signal information can be recovered with accuracy in noise level. In addition, there is less than 5% error using PCA to estimate noise. Preliminary results from the real AIRS observation are discussed briefly.

This paper introduces the approach and application of the investigation of the geological hazards using remote sensing images in Northwestern Hebei. How to select the types of remote sensing images and what method of remote sensing technique should be adopted for different kinds of the geological hazards are described in great detail in the paper. The investigation results of the geological hazards by remote sensing are evaluated in briefly. It is of important real value that the hidden danger areas and geological hazard’s trends are obtained by remote sensing to preventing and harnessing the geological hazards.

Differential optical absorption spectroscopy (DOAS) is the method widely used to measure trace gases in the atmosphere. The key procedures in the retrieval algorithms of the recorded DOAS spectra are the separation of the absorption into two parts that represent respectively broad and narrow spectral features and the evaluation of absorption spectra. The linear least-squares fitting routines were used to evaluate absorption spectra in the past when the atmospheric spectra were modeled with a linear combination of known laboratory reference spectra to derive the concentrations. In this paper, a new analysis method to derive the concentrations was developed. The method is based on the data correlation and can get the simultaneous linear equations with unknowns of the concentrations (formula available in paper). Solving this n order linear equations can determinate the concentrations of trace gases. This new method considers the fingerprint features of the various trace gases in the same range of wavelength and reduces the influence caused by the detector noise and photon statistics.

Vegetation fraction, the ratio of vegetation occupying a unit area, as a significant parameter in the development of climate and ecological models, is indispensable information of many global and regional climate numerical models. It is also an important basic data of describing ecosystem. However, It is also a wasting manpower and financial resources with low-precision work to measure the vegetation fraction by fieldwork, especially in large areas. This study explores the potential of deriving vegetation fraction from normalized difference vegetation index (NDVI) using the TM data. Under the assumption that the pixel of TM image is a mosaic structure, sub-pixel models for vegetation fraction estimation have been introduced firstly. Then the idea of utility of different sub-pixel model for vegetation fraction estimation based on land cover classification is proposed. The model for vegetation fraction estimation has been established under many assumptions, and there is the complex relationship of vegetation index vegetation fraction and leaf area index, so it is unrealistic to obtain vegetation fraction with high precision. But it is helpful to improve estimation precision to some extent by probing into application of assistant information and finery parameters of model.

High resolution satellite data were used to assess the hazardous heavy metals seeping into potable water sources from refuse resulting from the coal cleaning and refining process. Remote sensing data from different NASA Earth Observing Satellite and instruments aboard these satellites were utilized in developing a three-dimensional visualization (flythrough). These were mapped on the specialized graphics of the West Virginia region to detect metal concentrations in the water bodies around coal impoundments. An integration of EDGE Viewer, ArcView Geological Information Systems (GIS), and Bryce 5 software were used to construct the visualization. The communities surrounding the particular geographical locations will be able to use this tool for posting an alert of unusually high and potentially harmful concentrations of heavy metals in the water reservoir.

A simulation model is designed for imaging and calculation of polarization components in underlying surface and cloud radiation during stereo observation from space. The model makes it possible to take into consideration both engineering methods of analysis and optical effects caused by solar and nighttime illumination and observed in various seasons and spectral bands. It allows imitation of any illumination and observation geometry, sensor parameters, dynamics of scene fragments and spacecraft movement.