Hyperspectral remote sounding was introduced with the High spectral resolution Interferometer Sounder (HIS) that flew on the NASA ER-2 aircraft in the mid-1980s. The results from the HIS demonstrated that high vertical resolution sounding information could be achieved using quasi-continuous spectra of the atmosphere’s radiance to space. This has led to a series of research and operational satellite instruments designed to exploit the hyperspectral resolution sounding approach. The experimental versions, the ADEOS IMG (Interferometer for the Measurement of trace Gases) and the Aqua AIRS (Atmospheric InfraRed Sounder) have already been orbited. The IASI (Infrared Atmospheric Sounding Interferometer) and the CrIS (Cross-track Infrared Sounder) instruments are soon to be orbited on the METOP and the NPP/NPOESS operational series of polar orbiting satellites, respectively. Geostationary satellite hyperspectral resolution sounding instrumentation was initiated with the experimental GIFTS (Geostationary Imaging Fourier Transform Spectrometer) instrument whose development is providing risk reduction for the next generation of operational geostationary satellite instruments (e.g., the GOES-R Hyperspectral Environmental Suite, HES). This presentation traces the evolution of the hyperspectral resolution sounding program. Intercomparisons of the different satellite instrument approaches are discussed. Experimental results from the current aircraft and experimental satellite systems are presented to demonstrate the power of the hyperspectral resolution sounding technique.

This paper outlines the requirements, methodologies, and implementation approach for development of the NOAA/NASA GOES-R Hyperspectral Environmental Suite (HES), which is scheduled to fly in the 2012 timeframe. The HES is currently being developed within the framework of the GOES Program to fulfill the future needs and requirements flowed down through the National Environmental Satellite, Data, and Information Service (NESDIS). As an integral component of the GOES-R series satellites, HES will provide measurements of the traditional temperature and water vapor vertical profiles with higher accuracy and finer vertical resolution than the current GOES sounder series as well as coastal water properties. HES will have approximately 1500 spectral channels for sounding in this suite, compared to the current GOES Sounder series with its 18 spectral channels, leading to improved vertical resolution and reducing temperature error. HES will also have approximately five times faster coverage rate. As a suite, HES is planned with new capabilities for coastal ocean coverage with the goal of including open ocean coverage. These new planned imaging applications, which will be either multispectral or hyperspectral, will also be discussed. An overview of the HES requirements will be presented along with how these requirements fit into goals and objectives at an Earth Science level, the GOES-R mission level, the spacecraft level, and the instrument suite level and will include an overview of the GOES-R project methodologies for achieving the advanced functional objectives of the GOES Program partnership(s).

Sensitivity studies of atmospheric temperature and humidity profile retrieval from EOS AQUA/AIRS measurements , that involve spectral coverage sensitivity , channel coverage sensitivity , additional predictors effect , are performed via empirical orthogonal function (eigenvectors of covariance ) expansion , leading to the revealment of new features of high-resolution infrared sounding . Simulation studies on atmospheric temperature profile retrieval based on the channel characteristics and spectral response function of IRAS had also be done In order to investigate the performance of InfRared Atmospheric Sounder (IRAS) which will be onboard the FY-3A satellite.

Tropospheric wind estimation is among the top priorities for the NPOESS Pre-Planned Product Improvement (P3I). This Environmental Data Record (EDR) can be achieved by tracking high spatial resolution altitude-resolved water vapor features at appropriate timescales using humidity imaging sounder observations. A Wedge-filter Imaging Sounder (WIS) can provide the required humidity imagery and has already been studied for application in geostationary orbit. The geostationary WIS would use spatially variable wedge filter spectrometers to collect earth radiances with ~1 km resolution over a broad infrared (710-2900 cm^-1) spectral region at 1% spectral resolution. The proposed sensor is a compact, lightweight, and rugged imaging sounder with better sensitivity, spectral resolution, spatial resolution than the current multispectral GOES imager and with full disk coverage rates. A Wedge-filter Imaging Sounder for Humidity (WISH) incorporates the same Raytheon WIS technology and is being proposed for consideration for flight on the NPOESS 2130 and 1730 LTAN spacecrafts. WISH would take advantage of the payload capacity available for P3I demonstrations in NPOESS and would serve as a risk reduction and technology demonstration for future NOAA environmental satellite missions. In this paper, we present our analysis of WISH performance toward achieving the NPOESS P3I tropospheric wind objective. The practicality of WISH for the current NPOESS LTAN spacecraft configuration and its instrument concept, sensor design, detector performance, measurement calibration, and system specification is discussed in a companion paper.

Development in the mid 80s of the High-resolution Interferometer Sounder (HIS) instrument 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(200?), HES(2013)]. Follow-on developments at the University of Wisconsin that employ Fourier Transform Infrared (FTIR) for Earth observations include the ground-based Atmospheric Emitted Radiance Interferometer (AERI) and the new Scanning HIS aircraft instrument. The Scanning HIS is a smaller version of the original HIS that uses cross-track scanning to enhance spatial coverage. Scanning HIS and its close cousin, the NPOESS Airborne Sounder Testbed (NAST), are being used for satellite instrument validation and for atmospheric research. A novel detector configuration on Scanning HIS allows the incorporation of a single focal plane and cooler with three or four spectral bands that view the same spot on the ground. The calibration accuracy of the S-HIS and results from recent field campaigns are presented, including validation comparisons with the NASA EOS infrared observations (AIRS and MODIS). Aircraft comparisons of this type provide a mechanism for periodically testing the absolute calibration of spacecraft instruments with instrumentation for which the calibration can be carefully maintained on the ground. This capability is especially valuable for assuring the long-term consistency and accuracy of climate observations, including those from the NASA EOS spacecrafts (Terra, Aqua and Aura) and the new complement of NPOESS operational instruments. It is expected that aircraft flights of the S-HIS and the NAST will be used to check the long-term stability of AIRS and the NPOESS operational follow-on sounder, the Cross-track Infrared Sounder (CrIS), over the life of the mission.

We investigate uncertainties in the Atmospheric Infrared Sounder (AIRS) radiances based on in-flight and pre-flight calibration algorithms and observations. The global coverage and spectral resolution (~ 1200) of AIRS enable it to produce a data set that can be used as a climate data record over the lifetime of the instrument. Therefore, we examine the effects of the uncertainties in the calibration and the detector stability on future climate studies. The uncertainties of the parameters that go into the AIRS radiometric calibration are propagated to estimate the accuracy of the radiances and any climate data record created from AIRS measurements. The calculated radiance uncertainties are consistent with observations. Algorithm enhancements may be able to reduce the radiance uncertainties by as much as 7%. We find that the orbital variation of the gain contributes a brightness temperature bias of < 0.01 K. Although this can be removed by algorithm enhancements, it is smaller than uncertainty of the gain for most channels.

The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) sensor has been designed to provide highly accurate radiometric and spectral radiances in order to meet the requirements of remote sensing of atmospheric motion from a geostationary orbit. The GIFTS sensor was developed under NASA New Millenium Program funding to demonstrate the tracking of infrared water vapor features in the atmosphere with high vertical resolution. A calibration concept has been developed for the GIFTS instrument design which meets the top level requirement to measure brightness temperature to better than 1 K. The in-flight radiometric calibration is performed using views of two on-board blackbody sources along with cold space. For the GIFTS design, the spectral calibration is established by the highly stable diode laser used as the reference for interferogram sampling, and verified with comparisons to atmospheric absorption line positions. The status of the GIFTS on-orbit calibration approach is described and accuracy estimates are provided. GIFTS is a collaborative activity among NASA Langley Research Center, Utah State Space Dynamics Laboratory, and the University of Wisconsin Space Science and Engineering Center.

The NASA New Millennium Program's Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) instrument provides enormous advances in water vapor, wind, temperature, and trace gas profiling from geostationary orbit. The top-level instrument calibration requirement is to measure brightness temperature to better than 1 K (3 sigma) over a broad range of atmospheric brightness temperatures, with a reproducibility of ±0.2 K. For in-flight radiometric calibration, GIFTS uses views of two on-board blackbody sources (290 K and 255 K) along with cold space, sequenced at regular programmable intervals. The blackbody references are cavities that follow the UW Atmospheric Emitted Radiance Interferometer (AERI) design, scaled to the GIFTS beam size. The cavity spectral emissivity is better than 0.998 with an absolute uncertainty of less than 0.001. Absolute blackbody temperature uncertainties are estimated at 0.07 K. This paper describes the detailed design of the GIFTS on-board calibration system that recently underwent its Critical Design Review. The blackbody cavities use ultra-stable thermistors to measure temperature, and are coated with high emissivity black paint. Monte Carlo modeling has been performed to calculate the cavity emissivity. Both absolute temperature and emissivity measurements are traceable to NIST, and detailed uncertainty budgets have been developed and used to show the overall system meets accuracy requirements. The blackbody controller is housed on a single electronics board and provides precise selectable set point temperature control, thermistor resistance measurement, and the digital interface to the GIFTS instrument. Plans for the NIST traceable ground calibration of the on-board blackbody system have also been developed and are presented in this paper.

The MODTRAN5(1a, in press) radiation transport (RT) model is a major advancement over earlier versions of the MODTRAN(tm) atmospheric transmittance and radiance model. New model features include (1) finer spectral resolution via the Spectrally Enhanced Resolution MODTRAN(tm) (SERTRAN) molecular band model, (2) a fully coupled treatment of auxiliary molecular species, and (3) a rapid, high fidelity multiple scattering (MS) option. The finer spectral resolution improves model accuracy especially in the mid- and long-wave infrared atmospheric windows; the auxiliary species option permits the addition of any or all of the suite of HITRAN molecular line species, along with default and user-defined profile specification; and the MS option makes feasible the calculation of Vis-NIR databases that include high-fidelity scattered radiances.

Modern Infrared satellite sensors such as AIRS, CrIS, TES, GIFTS and IASI are all capable of providing high spatial and spectral resolution infrared spectra. To fully exploit the vast amount of spectral information from these instruments, super fast radiative transfer models are needed. This paper presents a novel radiative transfer model based on principal component analysis. The model is very accurate and flexible. Its execution speed is a factor of 3-30 times faster than channel-based fast models. Due to its high speed and compressed spectral information format, it has great potential for super fast one-dimensional physical retrievals and for Numerical Weather Prediction (NWP) large volume radiance data assimilation applications. The model has been successfully developed for the NAST-I and AIRS instruments. The PCRTM model performs monochromatic radiative transfer calculations and is suitable to include multiple scattering calculations to account for clouds and aerosols.

With a fast yet accurate infrared radiation transfer model KCARTA, transmittance, radiance and brightness temperature spectra of top of atmosphere (TOA) over thermal infrared region (605-2805cm-1) was simulated. In simulation, the effects of different spectral resolution, response function shape, spectral calibration accuracy, propagation path and surface emissivity were taken into account. The results from forward calculations show: 1) Improvement of spectral resolution changes the probability of present brightness temperature so that more brightness temperature can be observed. Increased observed brightness temperature guarantee atmospheric sounding with better vertical resolution. 2) A small change in response function, spectral calibration, propagation path or surface emissivity will lead in much larger difference on observed brightness temperature for hyperspectral sounding than for low spectral resolution sounding. Therefore, hyperspectral sensor requires more sensitive SNR. Otherwise, the improvement of sounding will be limited. Results here can be taken as a reference in designing future hyperspectral IR sounder and retrieval algorithm.

Reducing temperature and water vapor estimation errors is indispensable for retrieving a CO₂ concentration profile or columnar amount from thermal infrared spectrum data because spectral radiance in the thermal infrared region is much more sensitive to temperature and water vapor concentration changes than it is to CO₂ concentration changes. This study presents a data analysis procedure to estimate the CO₂ columnar amount from the thermal infrared spectrum. The first step retrieves the temperature vertical profile, water vapor vertical profile, and the surface temperature from spectra in the strong absorption bands of CO₂ and H₂O. Then the spectral biases that are attributable to temperature and water vapor retrieval errors are reduced by comparing observed and synthesized radiances in the atmospheric window region. The final step estimates the CO₂ columnar amount from the corrected spectra of a weak absorption band of CO₂ that is located around 940 cm^-1. This method was applied to analysis of spectrum data from IMG sensor aboard the ADEOS satellite. Some preliminary results are shown.

A method has recently been developed to compress the number of channels of trace gas remote sounder preserving almost all the information content that the original data has1. In this method, the weighting function of the original channels is expanded with empirical orthogonal functions (EOFs), and a set of hypothetical radiances, whose weighting functions are the EOFs, are used for the analysis. It has been shown that the radiance data of 240 of original channels of CO₂ spectrum at around 6207 cm^-1 can be compressed to about 3 channels of hypothetical radiances with loosing negligible information content. This means that the information content of the vertical profile of trace gas, which the spectrum of the reflected solar radiation has, is not so much. In the present paper, the information content of the vertical profile is examined for typical two types of spectra of CO₂ and CH₄ absorption bands at around 1.6 and 2.1 μ regions. Another issue of this paper is the correlation between the "measurement error" of the hypothetical channels. Since the hypothetical radiance is generated by the linear combination of radiances of the original channels, it could have the correlation between the radiance errors in hypothetical channels. It is shown that the crrelation rapidly decreases with the decrease of the range of the data that generates the EOFs.

Today, most Numerical Weather Prediction (NWP) centers are assimilating cloud-free radiances. Radiances from the Atmospheric Infrared Sounder have been directly assimilated in NWP models with modest positive impacts. However, since only 5% percentage of AIRS fields of view (fovs) are cloud-free, only very small amounts of the data in the lower troposphere are assimilated. (Note that channels in the mid-upper stratosphere are always assimilated since they are never contaminated by clouds.) The highest vertical resolving power of AIRS is in the lower troposphere. To further improve forecast skill we must increase the use of channels in the lower troposphere. This can be accomplished by assimilating cloud-cleared radiances, which has a yield of about 50%. Since cloud-cleared radiance may have residual cloud contamination and forecast accuracy is very sensitive to the accuracy of the input observations, a technique has been developed to use the 1 km infrared channels on the Moderate Resolution Imaging Spectroradiometer (MODIS) to quality control the cloud-cleared radiances derived from an array of 3 x 3 high spectral infrared sounder AIRS 14 km fovs. This is accomplished by finding MODIS clear radiances values within the AIRS field of view. The MODIS clear radiances are compared to cloud-cleared AIRS radiances that have been convolved to the MODIS spectral resolution. Our studies have found that the cloud-cleared radiances error statistics are very similar to cloud-free (clear) when MODIS data are used to remove potential outliers in the population of AIRS cloud-cleared radiances.

Airborne longwave infrared (LWIR) hyperspectral imagery was utilized to detect and identify gaseous chemical release plumes at sites in southern Texas. The Airborne Hyperspectral Imager (AHI), developed by the University of Hawai’i, was flown over a petrochemical facility and a confined animal feeding operation on a modified DC-3 during April, 2004. Data collected by the AHI system was successfully used to detect and identify numerous plumes at both sites. Preliminary results indicate the presence of benzene and ammonia and several other organic compounds. Emissions were identified using regression analysis on atmospherically compensated data. Data validation was conducted using facility emission inventories. This technology has great promise for monitoring and inventorying facility emissions, and may be used as means to assist ground inspection teams to focus on actual fugitive emission points.

Passive multi-spectral and hyper-spectral optical sensors offer great potential for remote-sensing in general and detection of low-concentration toxic species in particular. Correction for propagation through the intervening atmosphere (with molecular, aerosol and hydrosol constituents) is often the performance-limiting factor, a step which is unavoidably imprecise given uncertainties in the physical description of the atmospheric column. We propose to describe a general approach for mitigating the effects of these uncertainties using spectral sub-space projection, and to apply the technique to the difficult problem of trace-gas detection and quantification for environmental monitoring. While the approach may be applied to data collected by ground, aircraft or space-based sensors, we will illustrate it with hyperspectral off-nadir simulated imagery appropriate to a high-altitude aircraft. In addition to a description of the approach and simulated HSI data, detection/quantification performance using matched-filters for a number of common pollutants with and without sub-space projection will be presented. Use of matched-filters for detection has the additional benefit of quantitatively ranking the spectral weight of measurements for a given trace gas with the specified conditions and uncertainties. Such results bear directly on sensor design issues --spectral extent and resolution--and suggest that data volumes could be dramatically reduced by projection onto the target sub-space (s) prior to down-link.

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. The Tropospheric Trace Species Sensing Fabry-Perot Interferometer (TTSS-FPI) is a NASA Instrument Incubator Program (IIP) project for risk mitigation of enabling concepts and technology applicable to future Office of Earth Science (OES) atmospheric chemistry measurements. While the intended implementation for future science missions is a geostationary based measurement of tropospheric ozone and other trace species, a multispectral imaging airborne sensor system is being developed within IIP to demonstrate the instrument concept and enabling technologies that are also applicable to space-based configurations. 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. An overview of this IIP project addressing the measurement and instrument concepts, enabling technologies, approach for development and demonstration, and a summary of progress-to-date will all be reported. This will include sensor radiometric, spectral, and spatial characterization activities relevant to measurement concept validation. Subsequent manuscripts following in these proceedings will focus on the airborne prototype system under development and a corresponding spaceflight concept study, respectively.

The Tropospheric Trace Species Sounder is a spatially imaging, spectrally tunable airborne sensor focused on demonstrating a new capability to make important measurements of tropospheric ozone. The sensor system is based upon a cryogenically cooled dual etalon infrared Fabry-Perot interferometer. The instrument package is designed to operate autonomously on a high altitude aircraft platform. We present herein details of the airborne instrument's hardware and component test results.

We present results of studies of instrument concepts for a spaceborne imaging Fabry-Perot interferometer to measure tropospheric ozone. Ozone is recognized as one of the most important trace constituents of the troposphere. Tropospheric ozone is responsible for acute and chronic human health problems and contributes toward destruction of plant and animal populations. Furthermore, it is a greenhouse gas and contributes toward radiative forcing and climate change. Tropospheric ozone levels have been increasing and will continue to do so as concentrations of precursor gases (oxides of nitrogen, methane, and other hydrocarbons) necessary for the photochemical formation of tropospheric ozone continue to rise. Space-based detection and monitoring of tropospheric ozone is critical for enhancing scientific understanding of creation and transport of this important trace gas and for providing data needed to help develop strategies for mitigating impacts of exposure to elevated concentrations of tropospheric ozone. Measurement concept details are discussed in a companion paper by Larar et al. Development of an airborne prototype instrument for this application is discussed by Cook et al. in another companion paper.

The radiative balance of the troposphere, and hence global climate, is dominated by the infrared absorption and emission of water vapor, particularly at far-infrared (far-IR) wavelengths from 15-50 &mu;m. Water vapor is the principal absorber and emitter in this region. The distribution of water vapor and associated far-IR radiative forcings and feedbacks are widely recognized as major uncertainties in our understanding of current and the prediction of future climate. Cirrus clouds modulate the outgoing longwave radiation (OLR) in the far-IR. Up to half of the OLR from the Earth occurs beyond 15.4 &mu;m (650 cm^-1). Current and planned operational and research satellites observe the midinfrared to only about 15.4 &mu;m, leaving space or airborne spectral measurement of the far-IR region unsupported. NASA has now developed the sensor required to make regular far-IR measurements of the Earth's atmosphere possible. Far InfraRed Spectroscopy of the Troposphere (FIRST) was developed for NASA's Instrument Incubator Program under the direction of the Langley Research Center. The objective of FIRST is to provide a balloon-based demonstration of the key technologies required for a space-based sensor. The FIRST payload will also be proposed for science flights in support of validation of the various experiments on the Earth Observing System (EOS). We discuss the FIRST Fourier transform spectrometer system (0.6 cm-1 unapodized resolution), along with its radiometric calibration in the spectral range from 10 to 100 µm (1000 to 100 cm^-1). FIRST incorporates a broad bandpass beamsplitter, a cooled (~180 K) high throughput optical system, and an image type detector system. We also discuss the actual performance of the FIRST instrument relative to its performance goal of a NE(delta)T of 0.2 K from 10 to 100 &mu;m.

BATC is developing the Spaceborne Atmospheric Infrared Sounder for Geosynchronous Earth Orbit (SIRAS-G) under NASA's 2002 Instrument Incubator Program. SIRAS-G represents a new approach to infrared imaging spectrometry suitable for Earth observation from geosynchronous orbit. SIRAS-G is an instrument concept with lower mass and power requirements than contemporary instruments that offers enhanced capabilities for measuring atmospheric temperature, water vapor, and trace gas column abundances in a compact package. In addition, the SIRAS-G concept is adaptable to airborne, low-Earth orbit and geosynchronous deployment. SIRAS-G employs a wide field-of-view hyperspectral infrared optical system that splits the incoming radiation to four separate grating spectrometer channels. Combined with large 2-D focal planes, this system provides simultaneous spectral and high-resolution spatial imaging designed to measure infrared radiation in 2048 spectral channels with a nominal spectral resolution (l/Dl) of between 700 and 1400. Design parameters and the associated basic design trades for a SIRAS-G laboratory demonstration instrument are presented in this paper. Results of completed instrument design analyses along with instrument performance predictions are included. Using these performance predictions, we offer a comparison of current technology with SIRAS-G's capabilities for measuring atmospheric temperature, water vapor profiles, and trace gas column abundances.

The Airborne Imaging Radiometer (AIR) is a small, low mass and power sensor being developed by Ball Aerospace for studies of atmospheric and surface processes. AIR is designed to be a well calibrated, high spatial resolution multispectral imaging sensor. It has been proposed to be built and flown as part of a larger compliment of instrumentation for the High-performance Instrumented Airborne Platform for Environmental Research (HIAPER) under development by the National Science Foundation. The sensor design as currently envisaged will fit within the wing pod 18-inch diameter cylindrical envelope. The sensor is configured as a pushbroom-imager with an 8-km swath width at the nominal 12.5-km flight altitude of HIAPER. It will provide 50-meter resolution thermal imagery in ten spectral bands for the determination of surface and cloud top temperature, cirrus cloud properties, and layer averaged distributions of atmospheric temperature, water vapor and column ozone. A companion visible camera provides 25-meter imagery to aid in the analysis of the infrared imagery. AIR is designed around a Raytheon 320x240 element, 25 um pitch uncooled microbolometer detector array. This technology has advantages over other infrared detector technologies for airborne applications because it does not require a mechanical cryocooler or liquid nitrogen-filled dewar to achieve the necessary longwave response simplifying optical, thermal and mechanical design.

There is increasing interest among the user communities for using satellite data products from multiple sensors for improved environmental monitoring. Spectral vegetation indices (VIs) are one of the more important products in observing spatial and temporal variations of vegetation biophysical properties and photosynthetic activities as well as in biogeochemical cycle modeling. To accomplish this goal, VIs from multiple sensors need to be normalized for differences in sensor characteristics and algorithms. In this study, we evaluated several empirical strategies in cross-calibrating VIs from different sensors for the spectral band pass filter differences. A satellite-borne hyperspectral image was obtained with the Earth Observing-1 (EO-1) Hyperion sensor over a tropical forest-savanna transitional area in South America. The image was first spectrally convolved to simulate Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) band passes and corrected for atmospheric effects. Data were then extracted from six land cover types with a wide range of biogeophysical conditions and used to empirically derive cross-calibration (translation) equations for the Normalized Difference Vegetation Index (NDVI). The empirical strategies examined included: cross-calibration at the VI level using the NDVI as a predictor variable, cross-calibration at the reflectance level using the reflectance as a predictor variable, and cross-calibration at the reflectance level using the NDVI as a predictor variable. We also examined a two-steps approach in which the cross-calibrations were performed first at the reflectance level and then at the NDVI level. Overall, all of the cross-calibration methods performed well, resulting in root mean square errors less than .05 NDVI units. In nearly all the cases, however, the translations resulted in large residual bias errors with their values reaching .16 units for dark, little or non-vegetated land targets. Depending on cross-calibration methods used, both the magnitudes and directions of bias errors varied significantly. Although the NDVI-based cross-calibration of the NDVI produced the best results with small RMSE values (< .01 unit), there still existed small bias errors. These results indicate that data continuity studies require a theoretical basis in developing a mechanistic understanding of discontinuity and that cross-calibration results need to be evaluated from a real application point of view in order to assess the impact of persistent bias errors and to establish acceptable difference, or error levels in multi-sensor data sets.

Cross calibration of data products among various satellite sensors has been paid much attention due to ever increasing needs of continuous environmental monitoring by past, current and future sensors. In this context, the studies on the relationships among spectral vegetation indices (VI) of different sensors will put more value on the existing long-term data records, e.g., by the NOAA-AVHRR series of sensors and LANDSAT-MSS, TM, and ETM+ sensors. This study will shade the light on the relationships among vegetation indices in the framework of VI cross calibrations over various optical sensors, including inter-VI relationships of different index formulations. The derivations of equations which describe VI relationships will be introduced based on the recently reported 'vegetation isoline' equations which relate two reflectances sampled at different wavelength regions. A general form of VI relationships will be introduced and then applied to specific cases of two VIs by assuming differences in spectral band-passes and differences in VI formulations to clarify influences of those differences on the inter-VI relationships. The derived expressions imply the necessity of cross calibration activities over various land cover types for the purpose of VI cross-calibrations, which may require major efforts involving both simulation and field activities.

Carbon is one of the most important element on the earth, and it can become with key of the mechanism of earth fluctuation. Also, it is said that vegetation plays an important role of the carbon circulation of biosphere-lithosphere-atmosphere. Therefore, it is needed for environment monitoring to understand plant productivity globally. The Japan Aerospace Exploration Agency (JAXA; former NASDA) has successfully launched a new Advanced Earth Orbiting Satellite (ADEOS-II) aboard an H-2A booster on December 14, 2002. The ADEOS-II satellite is focused on monitoring of global climate change on the Earth. Four disiplinary components of the Earth system, namely atmosphere, ocean, cryosphere, and land, are monitored with five sensors onboard this satellite including the Global Imager (GLI). Unfortunately, the operation of ADEOS II satellite has stopped on October 24 of 2003, but very important VNIR/SWIR/MTIR data has been obtained in northern hemisphere for vegetation dynamics by GLI sensor. These data have enough capability to monitor the density and vigor of green vegetation. GLI data has high potential for vegetation monitoring, and it will contribute to the future satellite sensor. 23 channels are dedicated for land observations in the two spatial resolutions; channels 1, 5, 8, 13, 15, 17, 19, 24, 26, 27, 28(2km), 30, 31, 34, 35, and 36 are for 1 km resolution, and channels 20, 21, 22, 23, 28, and 29 are for 250 m resolution. This paper shows the preliminary evaluation of GLI land products for vegetation monitoring.

Propose of a new Vegetation Index is purposes. Ordinal vegetation Index can show intensity of vegetation on the ground. It can not show structure of vegetation surface or texture. Proposed vegetation index utilizes BRF property. It is generated from data from 2 orbit of satellite and be able to show structure of vegetation surface or texture. Principles of this index is coming from field observation using RC helicopter. Each vegetation canopy has different texture and roughness. New index, named BSI (Bi-directional reflectance Structure Index) shows difference of vegetation canopy. It is calculated by using the data of NOAA/AVHRR, ADEOS OCTS. ADEOS-II GLI can derive BSI.

This project used hyperspectral data set to classify land cover using remote sensing techniques. Many different earth-sensing satellites, with diverse sensors mounted on sophisticated platforms, are currently in earth orbit. These sensors are designed to cover a wide range of the electromagnetic spectrum and are generating enormous amounts of data that must be processed, stored, and made available to the user community. The Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) collects data in 224 bands that are approximately 9.6 nm wide in contiguous bands between 0.40 and 2.45 mm. Hyperspectral sensors acquire images in many, very narrow, contiguous spectral bands throughout the visible, near-IR, and thermal IR portions of the spectrum. The unsupervised image classification procedure automatically categorizes the pixels in an image into land cover classes or themes. Experiments on using hyperspectral remote sensing for land cover classification were conducted during the 2003 and 2004 NASA Summer Faculty Fellowship Program at Stennis Space Center. Research Systems Inc.'s (RSI) ENVI software package was used in this application framework. In this application, emphasis was placed on: (1) Spectrally oriented classification procedures for land cover mapping, particularly, the supervised surface classification using AVIRIS data; and (2) Identifying data endmembers.

The Leica ADS40 is a line scanning sensor that collects stereo panchromatic imagery and 4 discrete multispectral bands in a 12,000 pixel-wide swath. The Z/I Imaging DMC is a frame based sensor that produces 13,824x7,680 pixel panchromatic images and 3072x2048 pixel multispectral images, which are normally pan sharpened to produce high resolution RGB and color infrared products. The suitability of the two systems for multispectral remote sensing and photogrammetric applications are compared, and contrasted with other film and digital alternatives. Results indicate that the DMC has an advantage for large scale photogrammetry applications, and the ADS40 is superior for remote sensing applications.

In snow/ice remote sensing with the thermal infrared (TIR) spectral region, the most important target parameter is surface temperature which is a key parameter in climate process studies. Surface emissivity is usually an uncertain factor in temperature determination, but laboratory measurements indicate that snow/ice emissivity spectra include some information on conditions such as grain size and cementation. We therefore investigate the applicability of a spectral emissivity change to snow/ice condition monitoring. First, snow/ice emissivity spectra extracted from a spectral library are evaluated, and the surface emissivity ratio (SER) of two bands located between 10.5 and 12.5 micro is proposed as a snow/ice condition index. Next, snow/ice emissivity spectra measured on site with a multi-band TIR radiometer are shown to have a spectral behavior almost consistent with the library spectra. Then, two-band temperature/emissivity separation (TES) equations for snow/ice surfaces for AVHRR, ASTER, and MODIS, which can be used for retrieving surface emissivities at two bands, are derived from the spectral library. Finally, the SER images acquired by ASTER and MODIS over snow/ice fields around Abashiri, Japan, and Dry Valley, Antarctica, are evaluated. The results show that the SER has a spatial variation of 1 or 2% over snow/ice surfaces, and also the thermal log residual (TLR) ratio as well as the SER is useful for snow/ice condition monitoring. Consequently, the SER and the TLR ratio will be useful for detecting some difference of snow/ice conditions under clear sky conditions in either daytime or nighttime.

Field experiments were conducted to examine the influence factors of cultivar, nitrogen application and irrigation on grain protein content, gluten content and grain hardness in three winter wheat cultivars under four levels of nitrogen and irrigation treatments. Firstly, the influence of cultivars and environment factors on grain quality were studied, the effective factors were cultivars, irrigation, fertilization, et al. Secondly, total nitrogen content around winter wheat anthesis stage was proved to be significant correlative with grain protein content, and spectral vegetation index significantly correlated to total nitrogen content around anthesis stage were the potential indicators for grain protein content. Accumulation of total nitrogen content and its transfer to grain is the physical link to produce the final grain protein, and total nitrogen content at anthesis stage was proved to be an indicator of final grain protein content. The selected normalized photochemical reflectance index (NPRI) was proved to be able to predict of grain protein content on the close correlation between the ratio of total carotenoid to chlorophyll a and total nitrogen content. The method contributes towards developing optimal procedures for predicting wheat grain quality through analysis of their canopy reflected spectrum at anthesis stage. Regression equations were established for forecasting grain protein and dry gluten content by total nitrogen content at anthesis stage, so it is feasible for forecasting grain quality by establishing correlation equations between biochemical constitutes and canopy reflected spectrum.

Cucumber was selected as the experimental crop in greenhouse, and a spectroradiometer (ASD FieldSpec HH, 325-1075 nm measurable range with 1 nm resolution) was used to acquire hyperspectral reflectance of whole plants and leaves in growing status. The seedlings were grown in compound substrate composed of vermiculite and straw charcoal. In order to create nutrient stress to cucumber, five kinds of compound substrates were prepared with mixing vermiculite and straw charcoal in the ratios of 10:0, 8:2, 6:4, 4:6, and 2:8, respectively. Thirteen measurements were conducted in testing period continued from May to July in 2003. The correlation coefficient between hyperspectral reflectance and N-content of leaves and that between hyperspectral reflectance and growth condition of whole plants were analyzed in all wavelength bands. The results show that the hyperspectral reflectance based on ground-based remote sensing is available to predict N-content of leaves and to determine growth condition of whole plants.

A lab experiment and a field experiment were conducted to develop a method to estimate soil moisture level using a handheld spectroradiometer. In lab experiment, forty-one soil samples with different moisture content were prepared. The hyperspectral reflectance of all soil samples were measured, and the moisture content of all soil samples were analyzed. In field experiment, a 50×300 m² small farm was selected, divided into 150 10×10 m² grids, and the hyperspectral reflectance of each grid was measured. A soil sample (about 1000 g) was collected for subsequent moisture analysis from each grid. The results from lab experiment showed that there was a linear correlation between soil moisture content and soil hyperspectral reflectance when the moisture content was below 19 %db. By comparing the two experiments, we also identified that the soil surface condition and the surrounding temperature can influence the precision of the hyperspectral reflectance measured in the field experiment. Based on the field experiment, several hyperspectral reflectance maps were drawn and they show high correlation with soil moisture content map. All results from both the lab experiment and the field experiment show possibility to estimate soil moisture content with hyperspectral reflectance obtained by ground-based remote sensing.

The National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory, the Arizona State University (ASU), and Raytheon Space and Airborne Systems (SAS) Santa Barbara Remote Sensing (SBRS) have executed a series of successful Mars exploration missions. These have recently been publicized on television and the internet with the early 2004 Mars Exploration Rover (MER) mission geological robots that have revolutionized our detailed knowledge of the planet's geology and atmosphere. This latest mission success has its foundation in missions dating back to 1969. Over the past thirty-five years NASA has demonstrated a long-term commitment to planetary science and solar system exploration that continues with a commitment recently expressed by President Bush and codified in a reorganization of the NASA space sciences mission directorate. This paper reports on a small but exciting aspect of this sweeping NASA program, and illustrates the benefits and efficiency with which planetary and solar system exploration can be accomplished. Key in the success is the vision not only of NASA in general, but of the mission Principal Investigator, in particular. The specific series of missions leading to MER contains an underlying vision of carefully planned geological investigations using remote sensing instrumentation, starting with broad survey, leading to more finely resolved global imaging, and finally to landing instrumentation capable of detailed rock and soil analyses. The mission started with broad and relatively coarse spatial resolution orbital surveys with fine spectral capability focused on identifying the overall geological and atmospheric character of the planet accomplished from 1996 to the present conducted by the Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES). This led to the more detailed global imaging at finer spatial resolution offered by the Mars 2001 Odyssey Mission Thermal Emission Imaging System (THEMIS) which identified specific landing sites of interest for detailed exploration. The mission culminated in the recent MER lander geological analyses conducted by the mini-TES instruments carried by the rovers. This series of remote sensing investigations has set the stage for a new era in solar system exploration.

Through the centuries gem materials have been highly prized and sought after. The varieties of gem materials run into the hundreds if not thousands, characterized by a gamut of material classes running from organic to inorganic and from crystalline to amorphous. All consisting of numerous chemical compositions and characterized by various physical and optical properties. In addition, most gem materials have been subject to numerous modifications to enhance and imitate the most pleasing of esthetic qualities, e.g., dyeing, impregnation, heating, reconstruction, high pressure and temperature, irradiation, and diffusion. Of concern is the ability not only to identify the gem material in question, but if applicable, the treatment. Up until recent, the main instruments utilized to detect these have been simple but quite effective such as a binocular microscope, refractometer, hand spectroscope, dichroscope, and measuring of specific gravity. New gem materials and techniques involved in treatments have become increasingly sophisticated such as ultraviolet-visible-infrared and Raman spectroscopy. In certain cases, some of the most recent techniques have become time consuming and expensive. Here is the opportunity to overview and utilize a powerful technology found in the field of remote sensing, i.e., Hyperspectral Imaging. This technology has been in effect for many years but only recently has it been used to focus on areas similar to the ones in this paper. In particular, hyperspectral imaging technology and its potential application to gem identification and authentication are covered in this paper.

Water environment is associated with many disciplinary fields including sciences and management which makes it difficult to study. Timely observation, data getting and analysis on water environment are very important for decision makers who play an important role to maintain the sustainable development. This study focused on developing a plateform of water environment management based on remote sensing and GIS technology, and its main target is to provide with necessary information on water environment through spatial analysis and visual display in a suitable way. The work especially focused on three points, and the first one is related to technical issues of spatial data organization and communication with a combination of GIS and statistical software. A data-related model was proposed to solve the data communication between the mentioned systems. The second one is spatio-temporal analysis based on remote sensing and GIS. Water quality parameters of suspended sediment concentration and BOD5 were specially analyzed in this case, and the results suggested an obvious influence of land source pollution quantitatively in a spatial domain. The third one is 3D visualization of surface feature based on RS and GIS technology. The Pearl River estuary and HongKong's coastal waters in the South China Sea were taken as a case in this study. The software ARCGIS was taken as a basic platform to develop a water environmental management system. The sampling data of water quality in 76 monitoring stations of coastal water bodies and remote sensed images were selected in this study.

The Cross-track Infrared Sounder (CrIS), an interferometric sounder, is one of the instruments within the National Polar-orbiting Operational Environmental Satellite System (NPOESS) suite. CrIS measures earth radiances at high spectral resolution providing accurate and high-resolution pressure, temperature and moisture profiles of the atmosphere. These profiles are used in weather prediction models to track storms, predict levels of precipitation etc. Each CrIS instrument contains three Focal Plane Array Assemblies (FPAAs): SWIR [λ_c(98 K) ~ 5 mm], MWIR [λ_c(98 K) ~ 9 mm], and LWIR [λ_c(81 K) ~ 16 mm]. Each FPAA consists of nine large (850-mm-diameter) photovoltaic detectors arranged in a 3 x 3 pattern, with each detector having an accompanying cold preamplifier. This paper describes the selection methodology of the detectors that constitute the FPAAs and the performance of the CrIS SWIR, MWIR and LWIR proto-flight FPAAs. The appropriate bandgap n-type Hg_1-xCd_xTe was grown on lattice-matched CdZnTe. 850-mm-diameter photodiodes were manufactured using a Lateral Collection Diode (LCD) architecture. Custom pre-amplifiers were designed and built to interface with these large photodiodes. The LWIR, MWIR and SWIR detectors are operated at 81 K, 98 K and 98 K respectively. These relatively high operating temperatures permit the use of passive radiators on the instrument to cool the detectors. Performance goals are D* = 5.0 x 10¹⁰ cm-Hz^1/2/W at 14.0 mm, 9.3 x 10¹⁰ cm-Hz^1/2/W at 8.0 mm and 3.0 x 10¹¹ cm-Hz^1/2/W at 4.64 mm. Measured mean values for the nine photodiodes in each of the LWIR, MWIR and SWIR FPAAs are D* = 5.3 x 10¹⁰ cm-Hz^1/2/W at 14.0 mm, 1.0 x 10¹¹ cm-Hz^1/2/W at 8.0 mm and 3.1 x 10¹¹ cm-Hz^1/2/W at 4.64 mm. These compare favorably with the following BLIP D* values calculated at the nominal flux condition: D* = 8.36 x 10¹⁰ cm Hz^1/2/W at 14.0 mm, 1.4 x 10¹¹ cm-Hz^1/2/W at 8.0 mm and 4.1 x 10¹¹ cm-Hz^1/2/W at 4.64 mm.

The unprecedented size of ultraspectral sounder data makes its compression a challenging task. Ultraspectral sounder data features strong correlations in disjoint spectral regions affected by the same type of absorbing gases. Previously, we proposed a reordering scheme to better explore these correlations of the ultraspectral sounder data. With this preprocessing scheme, the state-of-the-art compression algorithms such as CALIC, JPEG-LS and JPEG2000 significantly improve the compression ratios up to 15% on average. In this paper, we investigate the effects of different starting channels for spectral reordering on the lossless compression of 3D ultraspectral sounder data obtained from Atmospheric Infrared Sounder (AIRS) observations. It is shown that the compression ratios and reordering indices are dependent on the choice of the starting channel for reordering.

Space-based, multispectral, ocean color measurements of the earth's oceans have significantly added to our understanding of the oceans over the past 25 years. All of these past and current space based sensors have operated in low earth orbit with moderate temporal resolution. We describe a mission concept for improved temporal and spectroscopic measurement of the ocean from geosynchronous orbit. This orbit requires that specific, available technologies be integrated into the instrument and spacecraft. For an instrument and spacecraft configured with these technologies this vantage point offers a unique opportunity when viewing dynamic, low reflectance components of the deep-ocean and coastal areas.

In array signal processing in general, we often wish to fuse the collected data at several sensor elements and implement a given estimation or detection task. This study is a selective treatment of the wideband array processing under some specific assumptions. Shannon Spatial Sampling Limit defines an upper bound for the frequency of transmission given certain element spacings in arrays. Beyond this bound, the exceeded ambiguity, due to spatial aliasing, avoids correct estimation of the signal parameters -e.g. the Direction Of Arrival (DOA), which is of our interest in this study. In another vein, decreasing the element spacing to meet a wider spectral support is difficult to implement due to the electromagnetic mutual coupling of the sensor elements in the array and the reduction of the resolution. This work is an attempt to develop a methodology for resolving this ambiguity or aliasing in the wideband scenario using statistical signal processing. Our approach is heuristic. We consider known implementations, adopt them to meet our scenario and then analyze the performance of our proposed method. Although the models and the formulations presented in this survey can be further generalized, we limit our discussion mainly to the Uniform Linear Arrays (ULA). Many of the topics discussed in this study have a potential for being useful in practical applications, since they would allow a realistic modeling and offer more flexibility than the conventional array processing framework, hence we believe that there are already sufficient interest in this study.

The original approach for the optical information processing for the hyperspectral remote sensing systems is developed on the union basis of the two mathematical tools: fuzzy logic and neural network. The optical information processing includes the complicated calculations and final results can give a large error. It is well known that there are large number of input parameters and some there uncertainty in the case of information processing of hyperspectral remote sensing systems. The using of statistical and determined models give the result having quite a large error of optical information processing and the given calculations take a lot of time to compute. Therefore the neoro-fuzzy logic application can be more expediency for processing of opto-electronic signals.

Investigations have been made on agronomy parameters as leaf area index (LAI), chlorophyll content (Chl), total Nitrogen (TN) and specific leaf weight (SLW) to describe growth status of winter wheat. More comprehensive parameters such as chlorophyll index (CI), projective chlorophyll index (CIp), Nitrogen index (NI) and projective Nitrogen index (NIp) have been developed to describe the dynamic growth information for foliage vertical layers by studying their vertical distribution characteristics along canopy and their spectral reflectance. Results are that from the canopy top to the ground surface, TN and Chl have shown an obvious gradient decreasing trend, while LAI and SLW have shown the ovate distribution. Compared with NI, CI and LAI, the absolute values of NIp, CIp and LAIp are more affected by canopy shape. The ratio of NIp to NI in different layers of erective varieties is significantly lower than that of loose varieties. Correlation analysis between canopy spectral reflectance and those developed parameters in different foliage layers at stage of anthesis shows that foliage Chl in upper layer is very sensitive to 400 nm-750 nm and 1300 nm-1750 nm while that in the middle layer is very sensitive to 750 nm -1300 nm. Higher correlation coefficient between spectral reflectance and TN is found in middle-under layer and it decreases upward.

Winter wheat canopy spectrum is dominated by wheat canopy closures, in this study. Our purpose is to study the quantitative influence of canopy closures on field canopy spectrum by quantitative reduced canopy stem densities. It indicated that canopy reflectance of winter wheat under different canopy stem densities has significant difference in near infrared bands. It has line relationship between spectral reflectance of 100% canopy stem densities and spectral reflectance under canopy stem densities, all the coefficients of determination (R²) for the equations are exceeding 0.8452, and all the results are surprised well. Canopy reflectance difference of winter under different stem densities were also studied, they all have line relationships between canopy reflectance of 100% canopy stem densities and quantitative reduced canopy stem densities, the simulation equations are different for the erective cultivars and loose cultivars. Relationship between canopy closures and canopy stem densities were also studied too, it has positive relationship between canopy closures and canopy stem densities, it reveals a very good agreement between canopy closures and canopy stem densities, with a coefficient of determination (R²) 0.8467, so the canopy stem densities can be simulated by canopy closures.

Polarimetric analysis of solar rays reflected from the Earth's surface is expected to play a particularly important role in future Earth environment observation, and an imaging liquid crystal tunable filter (LCTF) spectropolarimeter for the near-infrared wavelength band has been developed by the Japan Aerospace Exploration Agency(JAXA) over the past several years for such analysis. In order to realize the practical application of the optical sensor, efforts are currently under way to develop it into sensor package for airborne observation system. This paper first presents the concept and architecture of an optical observation system using an LCTF spectropolarimeter which is sensitive to radiation in the 650-1100 nm near-infrared wavelength band. The results of farm and grassland observations using a near-infrared LCTF imaging spectropolarimeter are then presented by spectral images of observed crop specimen and grass, and radiances of solar rays reflected from the crop and grass are shown. The results of a measurement of water-purity conducted using models of a ploughed and irrigated rice field are also presented by the spectral radiances of solar rays reflected from such field models. Finally, the applicability of the LCTF spectropolarimeter to agro-environment observation is summarized based on the results of these outdoor experiments.

Hyperspectral sensing opens up great possibilities for future remote sensing. In particular, high-resolution hyperspectral analysis will be an indispensable tool for agricultural applications, hydrodynamics and ocean physics, and polarimetric analysis of solar radiation reflected from rivers, lakes and marshes is expected to play an important role in environmental observation. In conventional multispectral analysis, detailed information has not been able to be used because each pixel includes much mixed spectral radiometric information, so it is difficult to obtain high classification accuracy in the analysis. To address this problem, the authors have been investigating some experimental analysis schemes using a hyperspectral imaging spectropolarimeter with selectable plane of polarization developed by the Japan Aerospace Exploration Agency (JAXA), and these investigations have yielded some remarkable results in the observation of polluted water in laboratory models and field experiments. These results indicate the possibility of applying the imaging spectropolarimeter to wide area environmental observation. This paper describes preliminary experiments for detecting concentration of suspended solid in water using the hyperspectral imaging spectropolarimeter with multi-polarization. Several hyperspectral analysis schemes for detecting such water pollution and analysis results of the observation data are presented.

This paper analyzed the damaged forest by tomicus piniperda using multiple types of remote sensing data such as TM, CBERS-1, AVHRR and MODIS data. It selected a typical region including heavy damaged and healthy forest. The region was located by GPS (Global Position System). Then the spectral features of the above remote sensing data (March, 2001) were given. It indicates that the values of healthy forest of TM NIR band (0.76-0.9 ) and SWIR band (1.55-1.75 ) are distinctly greater than those of damaged forest. The values of CBERS-1 NIR bands (0.77-0.89 ), AVHRR bands (0.725-1.0 ) and MODIS bands (0.841-0.876 ) behave in the same pattern with TM. Otherwise, the values of MODIS thermal bands (3.929-3.89 , 10.78-11.28 and 11.77-12.27 ) of damaged forest are distinctly greater than those of healthy forest. The AVHRR thermal bands are not so. Finally, two detection models were put forward according to the spectral changing characteristics. One was named Difference Rate (DR) model with NIR and VIR data, which applied for TM, CBERS-1, AVHRR and MODIS. DR is greater, the forest grow healthily. Basis on the typical sample, the different guidelines distinguished healthy and damaged forests are obtained. The other model was named Disaster Index (DI) model with thermal and NIR data, only suitable for MODIS. The guidelines of healthy and damaged forest are determined too. DI is greater the forest is stricken more badly. In conclusion, it will help monitoring and assessing the vermin occurrence and impact by remote sensing detection model.

A long wave infrared (LWIR) hyperspectral imager, the University of Hawaii's Airborne Hyperspectral Imager (AHI), was used to relate systematic changes in LWIR spectral features to weathering trajectories on the surfaces of basaltic rocks. Kahle and others proposed that in relation to the LWIR spectra, that devitrification of chilled glassy margins dominate the first stages of weathering, followed by the accretion of silicate coatings and the oxidation of iron[1-3]. We are using the AHI's higher spectral and special resolution to better constrain this relationship between the LWIR and weathering trajectories. The main study area was along the northern flank of Mauna Loa on the Island of Hawai'i. We collected samples ranging from a few decades to over 8000 years old. Samples a few hours to a few days old were collected from Kilauea. A Nicolet FTIR spectrometer was used to acquire reference spectra in the range of 5 to 15 μm. Three features are readily identifiable: two narrow features (A: ~8.1μm and B: 9.1μm) and one broad feature (C: 9.5 to 13 μm). The most striking change is in the C feature which changes from a large and dominant feature in the fresh Kilauea pahoehoe, to a subtle feature in the 1935 Mauna Loa flow. The only overall age related spectral change observed is the reduction of relative spectral feature intensity with increasing age. We also noted that within samples of the same age, there are some striking differences in the spectral shape.

This study presents an analysis of atmospheric temperature and water vapor using interferometric monitor for greenhouse gases (IMG) spectrum data and its retrieval procedure. The IMG is a high-resolution infrared sensor of the Fourier transform spectrometer (FTS) type that was launched aboard the Advanced Earth Observing Satellite (ADEOS) satellite in August 1996. Upwelling infrared radiation from the Earth was measured to examine the effects of greenhouse gases in the troposphere until June 1997. In the procedure to retrieve trace gas profiles from such satellite-based FTS data, accurate information on temperature, water vapor and surface properties is essential for precise retrieval. The instrument line shape (ILS) function, which generally depends on many factors of its sensor system, must also be determined accurately. In order to estimate the optimal ILS function, the "effective optical path difference (OPD)", which is assumed in retrieval analyses, is tuned to obtain the most optimal retrieved results in comparison with the sonde data. This method was applied to IMG spectrum data.

The demand for airborne remote sensing based on the Earth environment observation has been growing, motivated by the need to protect the Earth's environment. Attention has been focused on hyperspectral sensors as new type of Earth observation sensor for measuring the surface conditions from the air. The Japan Aerospace Exploration Agency (JAXA) has developed an LCTF hyper-spectral imaging spectropolarimeter with selectable plane of polarization which senses radiation in the 400-720 nm visible light wavelength band, and has constructed an airborne optical observation system based on the sensor. Flight evaluation of this sensor using JAXA's Beechcraft 65 research airplane has been continuing over the past few years, and this paper first outlines this flight evaluation. Next, we report on current aerial observations of water contamination in the rivers or lakes and the growth stages of crops are shown, with spectral images taken at various wavelengths and polarization angles presented as the analyzed results of flight experiment data. The flight experiments have confirmed that spectral images of targets with differing characteristics do indeed show different spectropolarimetric properties. Plans for future flight evaluations are also described. Finally it is concluded that the way has been paved for applying the visible light sensor to airborne remote sensing, aiming at the determination of surface conditions.

A field trial was conduct to investigate the relationship between spectral feature of winter wheat canopy and LAI as well as leaf nitrogen (N) under different status of leaf water in field situation. The objective of this study is to investigate effect of water status in plants on the accuracy of estimating leaf area index (LAI) and plant nitrogen. The new defined spectral index, IAFC = (R₂₂₂₄-R₂₀₅₄)/ (R₂₂₂₄+R₂₀₅₄), where R is the reflectance at 2224nm or 2054nm, was significantly (α=0.05) or extremely significantly (α=0.01) correlated with LAI at all the six dates for water insufficient plants, but not significantly correlated for water sufficient plants at five of the six dates and the difference of leaf water content between the water insufficient plants and water sufficient plants was only about 2% at some dates. The study provided strong evidence that leaf water has a strong masking effect on the 2000-2300nm spectral feature, which could be strongly associated with LAI and leaf N even when the leaf water content was as high as about 80% if the water was insufficient for plant growth. The results indicated that the masking effect of leaf water on the 2000-2300nm spectral feature was not only dependent on the absolute plant water content but also on the water status and that remotely sensed data in the 2000-2300nm region could be of potential in monitoring plant canopy biophysics and biochemistry in drought condition.

The presence of propagated molecular gas is one of the most probable causes of on-orbit degradation. The performance of optical sensors would be affected seriously if the strong absorption bands of the contaminants exist in the region of our interest and phase transition of adsorption gas on optical surfaces would induce not only absorption but also scatter. Although there are amount of trials to predict spectral degradation with model calculations, experimental approaches are also necessary to clarify degradation processes occurred in orbit and to improve the on-board calibration reliability. We built up the measurement system in order to evaluate transmittance degradation with various kinds of gases under different temperature and vacuum conditions. In our system, an optical glass, the site of adsorption, is set inside a cryostat and then a certain amount of molecular gas is injected. The amount of injected gas adsorption onto the optical surface is controlled by adjusting the sample surface temperature. Our systems have the capability to control vacuum within the range from 10^-3Pa to 10²Pa and temperature from 150K to 423K. As for the measurement of transmittance change, we adopted commercially available spectrophotometer and FTIR. The optical spectrophotometer covers the wavelength range from 300nm to 2.5um and the FTIR covers from 2um to 25um. We would present the details of our system and discuss about measurement accuracy and preliminary results of our measurements.

This study will present results of an effort to validate the accuracy of the cloud-cleared radiance products of the Atmospheric Infrared Sounder (AIRS) using observations from a variety of aircraft based sensors. The AIRS cloud-clear radiances are a product of the Level 2 ground processing software developed by the NASA AIRS science team. The cloud-clear radiance represents an estimate of the infrared upwelling spectrum at the top of the atmosphere for a cloud free atmosphere. This study concentrates on observations collected during the Pacific THORpex experiment, conducted in February-March 2003. NASA ER-2 aircraft based observations from the Scanning-High Resolution Interferometer Sounder (S-HIS) and the MODIS Airborne Simulator (MAS) are used in this validation effort.

Observations from the high spectral resolution Atmospheric InfraRed Sounder (AIRS) on the NASA EOS AQUA platform are providing improved information on the temporal and spatial distribution of key atmospheric parameters, such as temperature, moisture and clouds. These parameters are important for improving real-time weather forecasting, climate monitoring, and climate prediction. Trace gas products such as ozone, carbon dioxide, carbon monoxide, and methane are also derived. High spectral resolution infrared radiances from AIRS are assimilated into numerical weather prediction models. The soundings and radiances are provided in near real-time by NOAA/NESDIS to the NWP community. A significant component of the NOAA/NESDIS AIRS processing is to apply Principal Component Analysis (PCA) to the original AIRS 2000+ channel radiances. PCA is used for monitoring of the AIRS detectors, dynamic noise estimation and filtering, errant channel recovery, radiance reconstruction, and deriving an initial guess for profiles of temperature, moisture, ozone and other geophysical parameters. Since PCA has the ability to reduce the dimensionality of a dataset while retaining the significant information content, investigations are being done on its applications to AIRS data compression and archiving. Data compression is one of the key issues for the new generation of high spectral resolution satellite sensors. Our current AIRS research will allow us to provide valuable information and real-time experience to the generation of products for future sensors, such as the EUMETSAT IASI and NPOESS CrIS advanced infrared sounders. Examples of each application, along with details on the generation and application of eigenvectors are presented in this paper.

The AERI (Atmospheric Emitted Radiance Interferometer) has served as a primary instrument for the continuous measurement of down welling infrared emission within the DOE-ARM (Department of Energy - Atmospheric Radiation Measurement) program since 1993. AERI instruments have been deployed at ARM measurement sites that include the NSA (North Slope of Alaska), the TWP (Topical Western Pacific), and the SGP (Southern Great Plains). Marine versions of the AERI instrument (M-AERIs) have also operated on board ships by the University of Miami to measure SST (Sea Surface Temperature). The UW-SSEC (University of Wisconsin - Space Science and Engineering Center) operates an AERI instrument that is housed in a mobile vehicle (Winnebago) and that has been used in support of several field campaigns for surface emissivity measurements and for satellite instrument validation. Efforts are now underway to upgrade and modify the AERI systems that will implement a rapid sampling scheme to improve temporal resolution. ARM is in the process of redeploying SGP boundary facility AERIs to additional TWP and NSA field sites. The NSA AERIs are equipped with detectors suitable for extended spectral range (3.3-25 microns) and has been be used in support of the M-PACE (Mixed Phase Cloud Experiment) in the fall of 2004. The UW-SSEC is also undertaking activities to develop an AERI to be part of the AMF (ARM Mobile Facility) and expect to upgrade this instrument to a M-AERI that will be suitable for SST and emissivity measurements during field deployments. This manuscript will summarize the AERI modifications and upgrades that are underway.

The Scanning High-resolution Interferometer Sounder (S-HIS) instrument is a cross track scanning Fourier-transform interferometer with 0.5 wavenumber resolution. It is comprised of three detectors, which are the shortwave (SW), midwave (MW), and longwave (LW). Vibration experienced during flight can cause a significant level of spectrally correlated noise in the calibrated spectra. The S-HIS instrument has a wavefront tilt measurement system that monitors vibration induced optical tilts, which both reduces the interferometric noise and makes it possible to remove it with post processing. This two-axis tilt measurement system records small changes in the wavefront angles during the data collection of both scene and blackbody interferograms. The amplitude-modulation errors dominate the SW band while sample-position errors are found in the LW and MW bands. Here we show that the sample-position errors can be removed from the final calibrated radiances.

To quantify carbon exchange fluxes in subarctic peatlands, new techniques and software for monitoring of methane using high-resolution emission spectra of atmosphere observed from Space have been developed. Neural network technique is promissing for nstantaneous retrieval of methane content in atmosphere from huge amount of data provided by AIRS/AQUA sensor. IMG/ADEOS data, FIRE-ARMS forward simulations and retrieval of methane profiles from IMG spectra on the base of constrained optimization were used for the purposes of validation of the neural network techniques applied to AIRS/AQUA data. Preliminary maps of methane content in atmosphere of the permafrost boundary zone in Western Siberia are obtained from AIRS/AQUA data.

A feedforward neural network has been developed for retrieval of the Deuterium to Hydrogen ratio (D/H) in atmospheric water vapour from high resolution atmospheric radiances observed from space. The learning and test sets for the neural network training were created by forward simulation of atmospheric emission spectra using FIRE - ARMS for a large set of given temperature, humidity and D/H vertical profiles. The D/H profiles were generated using output from an atmospheric GCM including isotope tracers. The developed neural network was applied for retrieval of total atmospheric column D/H from IMG/ADEOS data over the ocean. A latitudinal distribution of D/H was obtained. The results are in agreement with latitudinal distribution of D/H in the atmosphere obtained from the IMG/ADEOS data earlier by using conventional retrieval methodology. However, the neural network has better accuracy. The stability of the neural network retrieval scheme with di®erent noise levels of the sensor is investigated, and we discuss the possibility of applying the neural network technique to the retrieval of D/H vertical profiles from TES/AURA spectra.

This study was to develop the time-specific and time-critical method to overcome the limitations of traditional field sampling methods for variable rate fertilization. Farmers, agricultural managers and grain processing enterprises are interested in measuring and assessing soil and crop status in order to apply adequate fertilizer quantities to crop growth. This paper focused on studying the relationship between vegetation index (OSAVI) and nitrogen content to determine the amount of nitrogen fertilizer recommended for variable rate management in precision agriculture. The traditional even rate fertilizer management was chosen as the CK. The grain yield, ear numbers, 1000-grain weight and grain protein content were measured among the CK, uniform treatments and variable rate fertilizer treatments. It indicated that variable rate fertilization reduced the variability of wheat yield, ear numbers and dry biomass, but it didn't increased crop yield and grain protein content significantly and did not decrease the variety of 1000-grain weight, compared to traditional rate application. The nitrogen fertilizer use efficiency was improved, for this purpose, the variable rate technology based on vegetation index could be used to prevent under ground water pollution and environmental deterioration.

Surface emissivity in the thermal infrared region is an important parameter for the studies of energy budget and surface energy balance. This paper focuses on estimating broadband emissivity using two sensors on NASA's Earth Observing System (EOS) Terra satellite, Advanced Spaceborne Thermal Emission and reflection Radiometer (ASTER) and MODerate resolution Imaging Spectrometer (MODIS). We developed a regression approach to generate infrared broadband emissivity maps from ASTER or MODIS data. The regressions are to relate the broadband emissivity to the emissivities for the ASTER or MODIS channels. The both regressions were calibrated using libraries of spectral emissivities. We applied this approach for ASTER and MODIS data acquired over the North Africa and Australia. The range of the broadband emissivity was found to be between 0.86 and 0.96 for the desert area. The root mean difference between the emissivities from these two sensors is smaller than 0.015. Such emissivity map could be used as an input of climate model and could contribute for improving the simulated surface and air temperature up to 1.1 and 0.8 °C respectively. The method can be applied to any arid regions of the world.

Free energy balance of the Earth is considered in this paper. To drive all meteorological and biotic processes and support own non-equilibrium stationary state the climate system consumes the net free energy, which is determined by difference between incoming free energy flux of solar radiation and total outgoing free energy flux of both reflected solar radiation and emitted to Space thermal radiation of the Earth-atmosphere system. The net free energy at the top of the atmosphere is considered as primary resource of the Earth climate system. Monitoring of the primary resource of the Earth is very important for deeper understanding and prediction of the Global Change. Method for calculation of the free energy fluxes at the top of the atmosphere using spectrometry data (radiances) of the Earth's thermal emitted and reflected solar radiation in entire spectral region from microwave to ultra violet is developed in this paper. Conception of long-term global monitoring of the net free energy flux at the top of the atmosphere using high-resolution spectrometry from Space is considered. Suitable set of sensors and scheme of observations to measure the planet radiances from Space for the monitoring are discussed.

Clouds play an important role in the hydrologic cycle, influence global energy balance, and represent a significant yet poorly understood component of global climate change. As a result, quantitative global observations of liquid and ice cloud microphysical and radiative properties continue to be a focus of a growing number of satellite-based sensors each having an associated suite of retrieval algorithms. While a number of these algorithms have successfully been applied to map clouds, many can only be applied under specific conditions (eg. during the daytime) or over a limited dynamic range (eg. optically thin cirrus) often leading to unphysical discontinuities when one seeks to compile a complete picture of the global distribution of clouds. Furthermore, discrepancies exist between products of different algorithms when they are applied to the same scene by virtue of differences in the information provided by distinct combinations of measurements. This paper revisits the problem of cloud microphysical property retrievals from satellite radiance observations at solar and thermal wavelengths in an effort to quantify their information content with respect to single layer liquid and ice clouds over an oceanic background. Using the channels on the Moderate Resolution Imaging Spectroradiometer (MODIS) as an example, it will be demonstrated that an entropy-based definition of information content provides a useful metric for evaluating the utility of a set of observations in a retrieval problem. This approach is used to objectively determine the subset of wavelengths that provide the greatest amount of information for oceanic microphysical property retrievals from the MODIS instrument. The results show that the combination of a conservative and a non-conservative scattering shortwave channel in concert with a near-infrared channel, an infrared window channel, and one in the wings of the 15 m CO2 band provide the optimal channel combination for the wide variety of liquid and ice clouds examined. With an eye toward developing a coherent representation of the global distribution of cloud microphysical and radiative properties, this combination of channels may be integrated into a suitable multi-channel inversion methodology such as the optimal estimation or Bayesian techniques to provide a means of establishing a common framework for cloud retrievals under varying conditions. Under some circumstances, other channels may provide a small amount of additional information but in most cases the remaining channels only supply redundant information and do not justify the additional computation cost required to integrate them into an algorithm.