The new era of high spectral resolution infrared instruments for atmospheric sounding offers great opportunities for climate change applications. A major issue with most of our existing IR observations from space is spectral sampling uncertainty and the lack of standardization in spectral sampling. The new ultra resolution observing capabilities from the AIRS grating spectrometer on the NASA Aqua platform and from new operational FTS instruments (IASI on Metop, CrIS for NPP/NPOESS, and the GIFTS for a GOES demonstration) will go a long way toward improving this situation. These new observations offer the following improvements: 1. Absolute accuracy, moving from issues of order 1 K to <0.2-0.4 K brightness temperature, 2. More complete spectral coverage, with Nyquist sampling for scale standardization, and 3. Capabilities for unifying IR calibration among different instruments and platforms. However, more needs to be done to meet the immediate needs for climate and to effectively leverage these new operational weather systems, including 1. Place special emphasis on making new instruments as accurate as they can be to realize the potential of technological investments already made, 2. Maintain a careful validation program for establishing the best possible direct radiance check of long-term accuracy--specifically, continuing to use aircraft-or balloon-borne instruments that are periodically checked directly with NIST, and 3. Commit to a simple, new IR mission that will provide an ongoing backbone for the climate observing system. The new mission would make use of Fourier Transform Spectrometer measurements to fill in spectral and diurnal sampling gaps of the operational systems and provide a benchmark with better than 0.1K 3-sigma accuracy based on standards that are verifiable in-flight.

An evaluation of the temperature, water vapor, and ozone profile retrievals from the AIRS data is performed with more than three years of collocated radiosondes (RAOBs) and ozonesonde (O₃SND) measurements. The Aqua-AIRS version 4.0 retrievals, global RAOB and O₃SND measurements, forecast data from the NCEP_GFS, ECMWF, and the NOAA- 16 ATOVS retrievals are used in this validation and relative performance assessment. The results of the inter-comparison of AIRS temperature, water vapor and ozone retrievals reveal very good agreement with the measurements from RAOBs and O₃SND s. The temperature RMS difference is close to the expected product goal accuracies, viz. 1^oK in 1 km layers for the temperature and close to 15% in 2-km layers for the water vapor in the troposphere. The AIRS temperature retrieval bias is a little larger than the biases shown by the ATOVS, NCEP_GFS, and ECMWF forecasts. With respect to the ozone profile retrieval, the retrieval bias and RMS difference with O₃SNDs is less than 5% and 20% respectively for the stratosphere. The total ozone from the AIRS retrievals matches very well with the Dobson/Brewer station measurements with a bias less than 2%. Overall, the analysis performed in this paper show a remarkable degree of confidence in the AIRS retrievals.

The ability to accurately validate high spectral resolution infrared radiance measurements from space using comparisons with a high altitude aircraft spectrometer has been successfully demonstrated (Tobin, et al. 2006). A comparison technique which accounts for the different viewing geometries and spectral characteristics of the two sensors was introduced, and accurate comparisons were made for AIRS channels throughout the infrared spectrum. Resulting brightness temperature differences were found to be 0.2 K or less for most channels. Continuing work on additional cases has shown some channels to have brightness temperature differences larger than 0.2 K. Atmospheric contribution from above the aircraft is a suspected factor in producing the larger differences. The contribution of upper atmosphere HNO3 and O3 are studied as contributors to the brightness temperature differences. Improved forward model calculations are used to understand and compensate for the above aircraft atmospheric contribution. Results of this effort to understand the observed temperature differences are presented. The methodology demonstrated for the NASA AIRS instrument is expected to be used in the validation of the CrIS sensor radiances from the operational NPP/NPOESS platforms and the IASI sensor radiances from the METOP platforms.

For measuring weak radiations with high spectral resolution, the Fourier Transform Spectrometer (FTS) is a powerful tool by virtue of its multiplex advantage. When we use this advantage for measuring Earth-reflected solar radiations from a moving satellite in space, however, we encounter a difficulty that during the acquisition of the interferogram, the optical characteristics of instantaneous filed of view (IFOV) could change. The change of IFOV radiance is caused by, e.g., the fluctuation of line-of-sight of the spectrometer, the change of reflection angle, the glittering of the water surface, or other causes. In this paper, we examine the effects of such pseudo signals contained in the interferograms on resultant spectra and retrieval accuracies of CO₂. Simulations showed that such pseudo signals could generate serious errors in CO₂ retrieval with the FTS of the GOSAT (Greenhouse Gases Observing Satellite). A method is shown to correct these types of disturbances on the interferograms. Together with these topics, we also discuss about other issues such as the ability of the measuring system of GOSAT-FTS to resolve the vertical density profiles of gases or the method to avoid the uncertainty of the existing data for high resolution spectra of solar radiance spectra.

The Greenhouse Gases Observing Satellite (GOSAT) will be launched in 2008 for global observations of greenhouse gases such as CO₂ and methane. This study examines the feasibility of retrieving CO₂ concentrations from the infrared spectra of the GOSAT/Thermal and near infrared Sensor for Carbon Observation (TANSO)-FTS. Retrieval simulations in which the maximum a posteriori (MAP) method was applied to pseudo-spectra at 700-800 cm^-1 from TANSO-FTS ("CO₂ 15-?m band") showed that retrieved CO₂ profiles agreed with true CO₂ profiles to within the total errors throughout the troposphere above 700-800 hPa when atmospheric conditions such as temperature used in the computation of the spectra were known. In contrast, discrepancies between retrieved CO₂ and true CO₂ concentrations increased if temperatures used in the retrieval included random errors; a random scatter of ±0.5 K caused a discrepancy that was 12 times larger at ~750 hPa. However, appropriate channel selection based on CO₂ and temperature information could reduce the effect of temperature uncertainty on CO₂ retrievals in this spectral region: the discrepancy between retrieved and true concentrations at ~750 hPa in the case with channel selection was about one-third of the discrepancy without any channel selection.

We describe an original methodology to account for aerosol and cirrus cloud contributions to reflected sunlight. This method can be applied to the problem of retrieving greenhouse gases from satellite-observed data and is based on the equivalence theorem with further parameterization of the photon path-length probability density function (PPDF). Monte Carlo simulation was used to validate this parameterization for a vertically non-homogeneous atmosphere including an aerosol layer and cirrus clouds. Initial approximation suggests that the PPDF depends on four parameters that can be interpreted as the effective cloud height, cloud relative reflectance, and two additional factors to account for photon path-length distribution under the cloud. We demonstrate that these parameters can be efficiently retrieved from the nadir radiance measured in the oxygen A-band and from the H₂O-saturated area of the CO₂ 2.0 ?m spectral band.

The aim of the study was to explore a fast way of monitoring chlorophyll a concentration in Dianshan Lake of Shanghai, China. Reflection spectra in spring of 2006 were measured and the simultaneous sampling and analysis were performed. The correlations between chlorophyll a concentration and reflection spectra were studied based on which different chlorophyll a algorithms were established. The results indicate that the accuracy of the linear algorithm using normalized reflectance is not high (R²<0.6). The relationship between chlorophyll a concentration and the reflectance ratios R₇₀₈/R₆₆₇ can improve accuracy (R²=0.68). The exponential algorithm between chlorophyll a concentration and the first order differential of the reflectance at 695.5nm is good (R²=0.76). Multivariate regression models with the normalized reflectance at 708nm and 607nm and their logarithm models were also established and the accuracy is higher than the above, in which the best is the model with the logarithm of 708nm and 607nm(R²=0.8). The study demonstrates the potential of monitoring chlorophyll a concentration using hyper-spectral remote sensing technology in Dianshan Lake.

A revolutionary satellite weather forecasting instrument, called the "GIFTS" which stands for the "Geostationary Imaging Fourier Transform Spectrometer", was recently completed and successfully tested in a space chamber at the Utah State University's Space Dynamics Laboratory. The GIFTS was originally proposed by the NASA Langley Research Center, the University of Wisconsin, and the Utah State University and selected for flight demonstration as NASA's New Millennium Program (NMP) Earth Observing-3 (EO-3) mission, which was unfortunately cancelled in 2004. GIFTS is like a digital 3-d movie camera that, when mounted on a geostationary satellite, would provide from space a revolutionary four-dimensional view of the Earth's atmosphere. GIFTS will measure the distribution, change, and movement of atmospheric moisture, temperature, and certain pollutant gases, such as carbon monoxide and ozone. The observation of the convergence of invisible water vapor, and the change of atmospheric temperature, provides meteorologists with the observations needed to predict where, and when, severe thunderstorms, and possibly tornados, would occur, before they are visible on radar or in satellite cloud imagery. The ability of GIFTS to observe the motion of moisture and clouds at different altitudes enables atmospheric winds to be observed over vast, and otherwise data sparse, oceanic regions of the globe. These wind observations would provide the means to greatly improve the forecast of where tropical storms and hurricanes will move and where and when they will come ashore (i.e., their landfall position and time). GIFTS, if flown into geostationary orbit, would provide about 80,000 vertical profiles per minute, each one like a low vertical resolution (1-2km) weather balloon sounding, but with a spacing of 4 km. GIFTS is a revolutionary atmospheric sensing tool. A glimpse of the science measurement capabilities of GIFTS is provided through airborne measurements with the NPOESS Airborne Sounding Testbed - Interferometer (NAST-I).

The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS), developed for the NASA New Millennium Program (NMP) Earth Observing-3 (EO-3) mission, has recently completed a series of uplooking atmospheric measurements. The GIFTS development demonstrates a series of new sensor and data processing technologies that can significantly expand geostationary meteorological observational capability. The resulting increase in forecasting accuracy and atmospheric model development utilizing this hyperspectral data is demonstrated by the uplooking data. The GIFTS sensor is an imaging FTS with programmable spectral resolution and spatial scene selection, allowing spectral resolution and area coverage to be traded in near-real time. Due to funding limitations, the GIFTS sensor module was completed as an engineering demonstration unit that can be upgraded to flight quality. This paper reviews the GIFTS system design considerations and the technology utilized to enable a nearly two order performance increase over the existing GOES sounder and shows its capability. While not designed as an operational sensor, GIFTS EDU provides a flexible and accurate testbed for the new products the hyperspectral era will bring. Efforts to find funding to upgrade and demonstrate this amazing sensor in space are continuing.

The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) represents a revolutionary step in satellite based remote sensing of atmospheric parameters. Using the combination of a Fourier Transform Spectrometer and Large Area Focal Plane Arrays, GIFTS measures incident infrared radiance with an unprecedented combination of spectral, temporal, and spatial resolution and coverage. In its regional sounding mode, it measures the infrared spectrum every 11 seconds at a spectral resolution of ~0.6 cm-1 in two spectral bands (14.6 to 8.8 μm, 6.0 to 4.4 μm) using two 128 × 128 detector arrays. From a geosynchronous orbit, the instrument will have the capability of taking successive measurements of such data to scan desired regions of the globe, from which thermal and gaseous concentration profiles, cloud properties, wind field profiles, and other derived products can be retrieved. Thermal vacuum testing of the GIFTS Engineering Development Unit (EDU) was performed at the Space Dynamics Laboratory in Logan Utah and completed in September 2006. With a focus on spectral characterization of the sensor, analyses of selected thermal vacuum tests are presented here.

The NASA New Millennium Program's Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) instrument was designed to provide 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 the onboard calibration approach used by GIFTS that employs two internal blackbody sources (290 K and 255 K) plus a space view sequenced at regular programmable intervals, this instrument level requirement places tight requirements on the blackbody temperature uncertainty (0.1 K) and emissivity uncertainty (0.001). The blackbody references are cavities that follow the UW Atmospheric Emitted Radiance Interferometer (AERI) design, scaled to the GIFTS beam size. The engineering model blackbody system was completed and fully calibrated at the University of Wisconsin and delivered for integration into the GIFTS Engineering Development Unit (EDU) at the Utah State Space Dynamics Laboratory. This paper presents a detailed description of the methodology used to establish the required temperature and emissivity performance, with emphasis on the traceability to NIST standards. In addition, blackbody temperature data are presented from the GIFTS EDU thermal vacuum tests that indicate excellent temperature stability. The delivered on-board blackbody calibration system exceeds performance goals - the cavity spectral emissivity is better than 0.998 with an absolute uncertainty of less than 0.001, and the absolute blackbody temperature uncertainty is better than 0.06 K.

The NASA New Millennium Program (NMP) Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) instrument was designed to demonstrate new and emerging technologies and provide immense improvements in satellite based remote sensing of the atmosphere from a geostationary orbit [1]. Combining a Fourier Transform Spectrometer (FTS) and Large Area Focal Plane Arrays, GIFTS measures incident infrared radiance with an extraordinary combination of spectral, temporal, and spatial resolution and coverage. Thermal vacuum testing of the GIFTS Engineering Development Unit (EDU) was performed at the Space Dynamics Laboratory and completed in May 2006 [2,3]. The GIFTS noise performance measured during EDU thermal vacuum testing indicates that threshold performance has been realized, and that goal performance (or better) has been achieved over much of both the Longwave Infrared (LWIR) and Short/Midwave Infrared (SMWIR) detector bands. An organizational structure for the division of the noise sources and effects for the GIFTS instrument is presented. To comprehensively characterize and predict the effects of measurement noise on expected instrument performance, the noise sources are categorically divided and a method of combining the independent effects is defined. Within this architecture, the total noise is principally decomposed into spectrally correlated noise and random (spectrally uncorrelated) noise. The characterization of the spectrally correlated noise sources specified within the structure is presented in detail.

A physical retrieval algorithm was developed for the Infrared Atmospheric Sounder Interferometer (IASI), which was launched on board of the METOP A satellite. The retrieval algorithm uses a Principal Component-based Radiative transfer model (PCRTM) and performs retrieval in Empirical Orthogonal Function (EOF) domain. The PCRTM fast radiative transfer model provides the principal component (PC) scores of an IASI radiance spectrum and the derivatives of the PC scores with respect to atmospheric parameters. Since the principal components are orthogonal to each other, relatively small number of PC scores are needed to capture the information content of the radiance spectrum. By performing radiative transfer modeling and retrieval in EOF domain directly; the algorithm deals with much smaller dimension as compared to original radiance domain. The retrieval is very efficient and fast.

Remote sensing with the new generation of highly spectrally resolving instruments like the Atmospheric Research Interferometer Evaluation System (ARIES) or the assimilation of highly resolved spectra from satellites into Numerical Weather Prediction (NWP) systems requires radiative transfer computations that deliver results essentially instantaneous. This paper reports on the development of such a new fast radiative transfer model. The model is based on an Empirical Orthogonal Functions (EOF) technique. The model can be used for the simulation of sensors with different characteristics and in different spectral ranges from the solar to the infrared. For the purpose of airborne remote sensing, the fast model has been designed to work on any altitude and for slant paths whilst looking down or up. The fast model works for situations with diverse temperature and humidity profiles to an accuracy of better than 0.01K for most of the instrument channels. The EOF fast model works for clear-sky atmospheres and is applicable to atmospheres with scattering layers of aerosols or clouds. The fast model is trained with a large set of diverse atmospheric training profiles. In forward calculations corresponding high resolution spectra are obtained. An EOF analysis is performed on these spectra and only the leading EOF are retained (data compression). When the fast model is applied to a new independent profile, only the weights of the EOF need to be calculated (=predicted). Monochromatic radiances at suitable frequencies are used as predictors. The frequency selection is done by a cluster algorithm, which sorts frequencies with similar characteristics into clusters.

Currently the function of operational locust monitor system mainly focused on after-hazards monitoring and assessment, and to found the way effectively to perform early warning and prediction has more practical meaning. Through 2001, 2002 two years continuously field sample and statistics for locusts eggs hatching, nymph growth, adults 3 phases observation, sample statistics and calculation, spectral measurements as well as synchronically remote sensing data processing we raise the view point of Remote Sensing three stage monitor the locust hazards. Based on the point of view we designed remote sensing monitor in three stages: (1) during the egg hitching phase remote sensing can retrieve parameters of land surface temperature (LST) and soil moisture; (2) during nymph growth phase locust increases appetite greatly and remote sensing can calculate vegetation index, leaf area index, vegetation cover and analysis changes; (3) during adult phase the locust move and assembly towards ponds and water ditches as well as less than 75% vegetation cover areas and remote sensing combination with field data can monitor and predicts potential areas for adult locusts to assembly. In this way the priority of remote sensing technology is elaborated effectively and it also provides technique support for the locust monitor system. The idea and techniques used in the study can also be used as reference for other plant diseases and insect pests.

Snow depth, a very significant factor in agriculture and climate research, is one of the most important parameters for snow amount calculation. It is proved there is a good linear relationship between snow depth and snow surface reflectance in visible to short-infrared window channels when snow has a depth within 30cm, which makes it possible to retrieve snow depth using AVHRR or MODIS data and station-measured snow-depth data. This paper mainly introduces the principle theory and process to establish a snow-depth retrieval model within 30cm using EOS/MODIS visible to short-infrared window channels' data and station-measured data, considering snow characteristics in different physical states and various complex underneath conditions including DEM, land cover such as grassland, forest, cropland and so on. Based on snow characteristics and underneath conditions, snow is devided into many types: old dry snow in flat grassland, new dry snow in flat grassland, old dry snow in mountainous grassland, old dry snow in flat cropland and so on. Fourteen kinds of snow have been modeled respectively in this retrieval model. Through 4 years validation in XinJiang Province of China since 2002, the precision of snow-depth retrieval model using MODIS visible to short-infrared channels' data can reach more than 80%. In flat area with single underneath condition, where wind power can be ignored, the model can always get a better precision. On the contrary, in mountainous forests, the precision of the model is not that good.

The Tropospheric Trace Species Sensing Fabry-Perot Interferometer (TTSS-FPI) was a NASA Instrument Incubator Program (IIP) project for risk mitigation of enabling concepts and technology applicable to future NASA Science Mission Directorate atmospheric chemistry measurements. Within IIP an airborne sensor was developed and laboratory-tested to demonstrate the instrument concept and enabling technologies that are also applicable to the desired geostationary-based implementation. 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, and also has applicability to and could simplify designs associated with sensors targeting measurement of other trace species. Results of testing and characterization of enabling subsystems and the overall instrument system are reported; emphasis is placed on recent laboratory testing performed to evaluate system-level radiometric, spatial, and spectral measurement fidelity.

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 national and international strategies for mitigating impact of exposure to elevated concentrations of tropospheric ozone in the US and elsewhere. Spaceflight instrument concept studies presented here show that a spaceborne imaging Fabry-Perot interferometer to measure tropospheric ozone from geosynchronous earth orbit is feasible and can be ready for full scale development starting in 2007.

This presentation discusses a new class of optical devices for observing the earth and its atmosphere that can be used to correct for the loss of image resolution due to earth curvature effects as you approach the edge of the earth disk as viewed from a satellite. These devices are primarily intended for use with two-dimensional CCD imaging arrays, including hyperspectral remote sensing systems viewing the earth from geostationary orbit. In this configuration they offer the possibility of uniform spatial resolution imagery extending across virtually the entire earth disk. The technology, however, can also be adapted to provide data with a uniform sensor resolution over broad sensing swaths using linear sensor arrays on satellites in low earth orbit, or from any of a variety of conical scanning instruments.

This paper gives an overview of the configuration and design of a Compact Hyper spectral imager with feature of having selectable bands in the visible and near infrared spectral region of 0.4 to 0.9?m. The instrument is configured for spatial resolution of 500m and swath of 128Km from 700Km polar orbit with a 12-bit quantization. The instrument will have three selectable modes of operation within the spectral range. Mode-1 will be the full range high resolution (?? ? 6nm) in 512 continuous bands, mode-2 will correspond to full range coarse resolution (?? ? 10nm) in 64 continuous bands and mode-3 will cover any octavo in the full range at high resolution in 64 continuous bands. In mode-1 the data rate will be around 21.5Mbps and in the other two modes the data rate will be one eighth of mode-1. Linear Variable Filter for spectral separation and Active Pixel Sensor area detector are used to achieve the compactness of the instrument, which will be weighing less than 4Kg. Feature of selectable gains by ground commanding to operate at a higher gain is also planned. The expected power dissipation of the instrument is <10W. This single unit compact instrument, which can be launched in any micro satellite mission, shall have application in gathering contiguous ocean-atmosphere data in the VNIR region at variable spectral intervals depending on the chosen mode of operation.

The Japanese Advanced Meteorological Imager (JAMI) was developed by Raytheon and delivered to Space Systems/Loral as the Imager Subsystem for Japan's MTSAT-1R satellite. MTSAT-1R became formally operational on 2005 June 28. This paper reports the first 2-km infrared synoptic imagery ever collected from geosynchronous orbit and provides an update on in-flight performance of JAMI. The performance areas discussed include radiometric sensitivity versus spectral channel, calibration accuracy versus spectral channel derived from comparisons of JAMI and AIRS measurements and scattered light performance around local midnight.

This paper investigates the estimation of modulation transfer function (MTF) and point spread function (PSF) using onorbit data of the first dedicated cartographic mission of ISRO, namely, IRS-Cartosat-1. The Cartosat-1 was launched in May 2005 with a motivation to realize in-track stereo-pair imagery at a ground sampling distance of 2.5 m with one of its two cameras, AFT, kept to view a ground scene at -5^o and the other, FORE, at +26^o with respect to nadir. As with any high-resolution satellite imagery, several factors viz., stray light, optics aberrations, defocusing, satellite motion, atmospheric transmittance etc. can have a strong impact on the observed spatial quality of the Cartosat-1 imagery. These factors are cumulatively accounted by PSF or by the MTF in the spatial frequency domain. The MTF is, thus, of fundamental importance since it provides assessment of spatial response of the overall imaging performance of the system. In this paper, estimation of the PSF and MTF was carried out by capturing imagery over airport runway strip as well as artificial targets laid at two different locations within India. The method adapted here uses a sharp edge from two adjacent uniform dark and bright fields or targets. A super-resolved edge of sub-pixel resolution was constructed from the image edge slanted to satellite path to meet the basic requirement that the target width is much smaller than the spatial resolution width. From the preliminary results, the MTF for the FORE is found to be approximately lesser by about 2% with respect to AFT; this difference may be attributed to relatively a longer traverse of ground signal through the atmospheric column in the case of FORE camera.

Remote sensors were developed and used extensively world over using aircraft and space platforms. India has developed and launched many sensors into space to survey natural resources. The AWiFS is one such Camera, launched onboard Resourcesat-1 satellite by ISRO in 2003. It is a medium resolution camera with 5-day revisit designed for studies related to forestry, vegetation, soil, snow and disaster warning. The camera provides 56m (nadir) resolution from 817 km altitude in three visible bands and one SWIR band. This paper deals with configuration features of AWiFS Camera of Resourcesat-1, its onboard performance and also the highlights of Camera being developed for Resourcesat-2. The AWiFS is realized with two identical cameras viz. AWiFS-A and AWiFS-B, which cover the large field of view of 48°. Each camera consists of independent collecting optics and associated 6000 element detectors and electronics catering to 4 bands. The visible bands use linear Silicon CCDs, with 10μ × 7μ element while SWIR band uses 13μ staggered InGaAs linear active pixels. Camera Electronics are custom designed for each detector based on detector and system requirements. The camera covers the total dynamic range up to 100% albedo with a single gain setting and 12-bit digitization of which 10 MSBs are transmitted. The Camera saturation radiance of each band can also be selected through telecommand. The Camera provides very high SNR of about 700 near saturation. The camera components are housed in specially designed Invar structures. The AWiFS Camera onboard Resourcesat-1 is providing excellent imageries and the data is routinely used world over. AWiFS for Resourcesat-2 is being developed with overall performance specifications remaining same. The Camera electronics is miniaturized with reductions in hardware packages, size and weight to one third.

This paper deals with the salient features of LISS-3* Camera of Resourcesat-1, its onboard performance and also the highlights of Camera being developed for Resourcesat-2. LISS-3* camera is based on linear push-broom technique and contains four independent refractive optics, detectors and associated electronics for each band. The field of view is 10° and is covered with a single 6000 element linear detector in each band. The visible bands use Silicon CCDs, having 10μ x 7μ element size and 10μ pitch. The SWIR band uses 13μ pitch staggered InGaAs linear active detector. Camera Electronics is custom designed for each detector and adopts simultaneous readout mode. The video signal is digitized with 7-bit ADC in VNIR bands and the gain selection of 1:3 is incorporated to cover wide range. In case of SWIR band the video digitized with 12 bits of which 10MSBs are transmitted. Four gains are implemented with bit sliding. The camera components are mounted in a precisely fabricated and stable structure made out of Invar. The LISS-3* Camera onboard Resourcesat-1 is providing excellent imageries and the data is routinely used world over primarily for vegetation monitoring. Similar Camera is being developed for Resourcesat-2 keeping the overall performance characteristics same but minimizing electronic hardware.

Data from multiple sensors must be used together to gain a more complete understanding of land surface processes at a variety of scales. Although higher-level products derived from different sensors (e.g., vegetation cover, albedo, surface temperature) can be validated independently, the degree to which these sensors and their products can be compared to one another is vastly improved if their relative spectroradiometric responses are known. Most often, sensors are directly calibrated to diffuse solar irradiation or vicariously to ground targets. However, space-based targets are not traceable to metrological standards, and vicarious calibrations are expensive and provide a poor sampling of a sensor's full dynamic range. Crosscalibration of two sensors can augment these methods if certain conditions can be met: (1) the spectral responses are similar, (2) the observations are reasonably concurrent (similar atmospheric & solar illumination conditions), (3) errors due to misregistrations of inhomogeneous surfaces can be minimized (including scale differences), and (4) the viewing geometry is similar (or, some reasonable knowledge of surface bi-directional reflectance distribution functions is available). This study extends on a previous study of Terra/MODIS and Landsat/ETM+ cross calibration by including the Terra/ASTER and EO-1/ALI sensors, exploring the impacts of cross-calibrating sensors when conditions described above are met to some degree but not perfectly. Measures for spectral response differences and methods for cross calibrating such sensors are provided in this study. These instruments are cross calibrated using the Railroad Valley playa in Nevada. Best fit linear coefficients (slope and offset) are provided for ALIto- MODIS and ETM+-to-MODIS cross calibrations, and root-mean-squared errors (RMSEs) and correlation coefficients are provided to quantify the uncertainty in these relationships. Due to problems with direct calibration of ASTER data, linear fits were developed between ASTER and ETM+ to assess the impacts of spectral bandpass differences between the two systems. In theory, the linear fits and uncertainties can be used to compare radiance and reflectance products derived from each instrument.

The Indian Remote Sensing Satellites use indigenously developed high resolution cameras for generating data related to vegetation, landform /geomorphic and geological boundaries. This data from this camera is used for working out maps at 1:12500 scale for national level policy development for town planning, vegetation etc. The LISS-4 Camera was launched onboard Resourcesat-1 satellite by ISRO in 2003. LISS-4 is a high-resolution multi-spectral camera with three spectral bands and having a resolution of 5.8m and swath of 23Km from 817 Km altitude. The panchromatic mode provides a swath of 70Km and 5-day revisit. This paper briefly discusses the configuration of LISS-4 Camera of Resourcesat-1, its onboard performance and also the changes in the Camera being developed for Resourcesat-2. LISS-4 camera images the earth in push-broom mode. It is designed around a three mirror un-obscured telescope, three linear 12-K CCDs and associated electronics for each band. Three spectral bands are realized by splitting the focal plane in along track direction using an isosceles prism. High-speed Camera Electronics is designed for each detector with 12- bit digitization and digital double sampling of video. Seven bit data selected from 10 MSBs data by Telecommand is transmitted. The total dynamic range of the sensor covers up to 100% albedo. The camera structure has heritage of IRS- 1C/D. The optical elements are precisely glued to specially designed flexure mounts. The camera is assembled onto a rotating deck on spacecraft to facilitate ± 26° steering in Pitch-Yaw plane. The camera is held on spacecraft in a stowed condition before deployment. The excellent imageries from LISS-4 Camera onboard Resourcesat-1 are routinely used worldwide. Such second Camera is being developed for Resourcesat-2 launch in 2007 with similar performance. The Camera electronics is optimized and miniaturized. The size and weight are reduced to one third and the power to half of the values in Resourcesat-1.

In this paper, we implement a wavelet-modified fringe-adjusted joint transform correlator (JTC) for real-time target recognition applications. In real-time situation the input scene is captured using a CCD/thermal camera. The obtained joint power spectrum is multiplied with a pre-synthesized fringe-adjusted filter and the resultant function is processed with an appropriately scaled wavelet filter. The wavelet-modified fringe-adjusted JTC has been found to yield better results in comparison to the conventional fringe-adjusted JTC. To suppress the undesired strong dc, the resultant function is differentiated. Differential processing the wavelet-modified fringe-adjusted joint power spectrum removes the zero-order spectra and hence improves the detection efficiency. To focus the correlation terms in different planes in order to capture one of the desired autocorrelation peaks and discard the strong dc and another autocorrelation peak, chirp-encoding technique has also been applied. Computer simulation and experimental results are presented.

The development of sensors based on immobilized fluorescent reagent is a matter of growing interest. Chemiluminescence seems to be attractive because light is generated through the chemical reactions. No light source is needed, which makes the experimental set up very simple. In present work, the sensor presented is an optical sensor based on fluorescence quenching. Fluorescence quenching refers to any process, which decreases the fluorescence intensity of a certain fluorophore. Acetone is a commercially used solvent of great importance as it has got wide chemical and biomedical applications. It is on the hazardous substance list as well as on the special health hazard substance list. Hence identification of acetone has an immense importance. Fluorescence quenching of 7-Diethylamino-4-trifluoro methyl Coumarin is reported here. It was found that the quenching observed was of dynamic in nature. It was also observed that quenching of the fluorescence of the indicator had a full reversibility. As it has a full reversibility, an optical sensor for acetone can be constructed on this quenching.

pH of the wetland soil is one of the most important indicators for aquatic vegetation and water bodies. Mount Beigu Wetland, just near the Yangtse River, is under ecological recovery. Visible and near infrared reflectance spectroscopy was adopted to estimate soil pH of the wetland. The spectroradiometer, FieldSpec 3 (ASD) with a full spectral range (350-2500 nm), was used to acquire the reflectance spectra of wetland soil, and soil pH was measured with the pH meter of IQ150 (Spectrum) and InPro 3030 (Mettler Toledo). 146 soil samples were taken with soil sampler (Eijkelkamp) according to different position and depth, which covered the wider range of pH value from 7.1 to 8.39. 133 samples were used to establish the calibration model with the method of partial least square regression and principal component analysis regression. 13 soil samples were used to validate the model. The results show that the model is not good, but the mean error and root mean standard error of prediction are less (1.846% and 0.186 respectively). Spectral reflectancebased estimation of soil pH of the wetland is applicable and the calibration model needs to be improved.

Third World Satellite (TWSAT) is a small satellite of the Indian Space Research Organization (ISRO), weighing approximately 100 kg. This spacecraft will carry a 37-meter ground resolution, four band multispectral optical payload. This is a low cost, quick to develop, payload for studies of coastal regions, forestry, agriculture and related applications. The payload features four identical lens assemblies, each of which is designed to operate in a particular spectral band by using an appropriate band pass filter. The optical design is innovative in being usable over a spectral range of 450 to 860 nm. The design of the lens assembly is very compact, and as a result the payload is also small and commensurate with a small satellite. This payload is expected to reduce cost drastically compared to previous payloads by using qualified, commercial components to a large extent. The mechanical design of the payload features a monolithic, light weighted, aluminum main structure. This structure supports the lens assemblies on one side, and the detector head assemblies on the other side. This paper presents the optical and mechanical design of the electro-optic module, and the various tests proposed to be carried out to qualify the payload for space use.

The Indian Remote Sensing (IRS) P5 spacecraft carried two identical optical payloads (Cartosat-1), each with a different view angle, for acquiring high resolution remote sensing data in stereo mode for the purpose of generation of topographic maps. Information on terrain height derived from these payloads is useful for applications in a number of forms including digital elevation model (DEM) creation, orthoimage, DEM plus thematic data and scientific visualization. Each optical payload features an unobscured, three-mirror anastigmat, design providing high contrast, and wide swath imagery. The mechanical design of the camera structure enabled accurate location of the mirrors while maintaining a very high degree of dimensional stability during launch and in-orbit environment. This paper presents the optical and mechanical design of the camera assembly as well as the alignment and performance optimization carried out in realizing the Cartosat -1 payload.

Presently, unplanned changes of land use have become a major problem. Most land use changes occur without a clear and logical planning with little attention to their environmental impacts. In last four-decade, urban growth in Delhi has occurred rapidly in some unwanted direction and destroyed valuable agriculture lands in its surround. Rapid changes in land use / cover occurring over large areas; remote sensing technology is an essential and useful tool in monitoring of this area. Monitoring of land use/cover change are increasingly reliant on information derived from remotely sensed data. Such information provides the data link to other techniques to understand the human processes behind these changes. Specially, in agricultural area in suburb (or countryside) of a metropolitan city like Delhi. In this paper different change detection approaches (such as Post classification comparison and spectral change detection techniques) were evaluated with available images of National Capital Territory of Delhi during 1973 to 2001. These techniques were analyzed independently, using the concept of well-known procedures to define the best approach/methodology for addressing the change detection issues in this study.

The NASA Atmospheric Infrared Sounder (AIRS) on the EOS Aqua platform was the first of a series of high spectral resolution sensors that includes the operational Infrared Atmospheric Sounding Interferometer (IASI) on Europe's METOP platforms and the Cross-track Infrared Sounder (CrIS) on the U.S. National Polar Orbiting Environmental Satellite System platforms. High latitude polar regions of the Earth provide challenges for the use of infrared observations during the polar winter. A methodology is described for the identification of clear fields of view of the sounder over snow and the estimation of surface infrared emission. An example over the Greenland ice sheet is presented. The effective identification of clear sounder fields of view and the correct interpretation of the surface emission is an important component of making high latitude sounder data over land useable in Numerical Weather Prediction data assimilation.

The future world is a world of city. Spectral characterization of urban reflectance is important. The overall reflectance of the urban mosaic is determined by the spectral reflectance of surface materials and shadows and their spatial distribution. Building materials dominate net reflectance in most cities but in many cases vegetation also has a very strong influence on urban reflectance. In the study, the spectral characterization of urban reflectance properties is analyzed using Landsat TM and ETM+ imagery of a collection of the province capital city in China. The result shows these urban areas have similar mixing space topologies and can be represented by three-component linear mixture models The reflectance of these cities can be described as linear combinations of High Albedo, Dark and Vegetation spectral endmembers within a three dimensional mixing space containing over 80% of the variance in the observed reflectance. The relative proportions of these endmembers vary considerably among different cities but in all cases the reflectance of the urban core lies near the dark end and the new build-up areas near the light end of a mixing line between the High Albedo and Dark endmembers. In spite of the spectral heterogeneity, built-up areas do occupy distinct regions of the spectral mixing space. Based on the above analyzation, the urban spatial extent of 34 cities of China, representing the physical manifestation of a range of social, economic, cultural, and political dimensions associated with urban dynamics, was mapped using Landsat imagery collected of 1990 and 2000.

The surface emissivity effect on the thermodynamic parameters (e.g., the surface skin temperature, atmospheric temperature, and moisture) retrieved from satellite infrared (IR) spectral radiance is studied. Simulation analysis demonstrates that surface emissivity plays an important role in retrieval of surface skin temperature and terrestrial boundary layer (TBL) moisture. NAST-I ultraspectral data collected during the CLAMS field campaign are used to retrieve thermodynamic properties of the atmosphere and surface. The retrievals are then validated by coincident in-situ measurements, such as sea surface temperature, radiosonde temperature and moisture profiles. Retrieved surface emissivity is also validated by that computed from the observed radiance and calculated emissions based on the retrievals of surface temperature and atmospheric profiles. In addition, retrieved surface skin temperature and emissivity are validated together by radiance comparison between the observation and retrieval-based calculation in the "window" region where atmospheric contribution is minimized. Both simulation and validation results have lead to the conclusion that variable surface emissivity in the inversion process is needed to obtain accurate retrievals from satellite IR spectral radiance measurements. Retrieval examples are presented to reveal that surface emissivity plays a significant role in retrieving accurate surface skin temperature and TBL thermodynamic parameters.

These paper present results of the work carried out in the hyperspectral data analysis for mineral mapping. The study presents results on the analysis of hyperspectral data analysis for the Gujarat area. Hyperion data of EO-1 mission of NASA was used for the study. Different processing techniques like minimum noise transform (MNF), Spectral angle mapping (SAM)) etc was applied to separate the end members derived from the Hyperion data set.

With ever-increasing number of spectral channels from space-borne hyperspectral instruments, demand on approaches for fast search schemes for matching hyperspectral pixel vector with standard spectral library database has increased proportionately. The present-day methods are tedious and time consuming to meet the above task. We propose a fast matching scheme based on bivariate short-interval local variance that can be used to capture the essence of reference materials in the spectral library. The variance of each selected window is computed across the spectral curve data and the peak variance above a threshold is taken as a spike. The position and linewidth of the spikes are shown to carry unique signatures of the given material spectral data, which can be stored and used as matching criteria. The choice of appropriate threshold is important; it has been found that the mean value of background variance signal could be used as the threshold value. The proposed method was successfully applied to identify some samples of the AVIRIS hyperspectral imagery to the standard JPL spectral library database.

This paper presents a study about the potential of remote sensing in bauxite exploration in the Kolli hills of Tamilnadu state, southern India. ASTER image (acquired in the VNIR and SWIR regions) has been used in conjunction with SRTM - DEM in this study. A new approach of spectral unmixing of ASTER image data delineated areas rich in alumina. Various geological and geomorphological parameters that control bauxite formation were also derived from the ASTER image. All these information, when integrated, showed that there are 16 cappings (including the existing mines) that satisfy most of the conditions favouring bauxitization in the Kolli Hills. The study concludes that spectral unmixing of hyperspectral satellite data in the VNIR and SWIR regions may be combined with the terrain parameters to get accurate information about bauxite deposits, including their quality.

In this paper, the big coal mining area Yanzhou is selected as the typical research area. According to the special dynamic change characteristic of the environment in the mining area, the environmental dynamic changes are timely monitored with the remote sensing detection technology. Environmental special factors, such as vegetation, water, air, land-over, are extracted by the professional remote sensing image processing software, then the spatial information is managed and analyzed in the geographical information system (GIS) software. As the result, the dynamic monitor and query for change information is achieved, and the special environmental factor dynamic change maps are protracted. On the base of the data coming from the remote sensing image, GIS and the traditional environment monitoring, the environmental quality is appraised with the method of indistinct matrix analysis, the multi-index and the analytical hierarchy process. At last, those provide the credible science foundation for the local environment appraised and the sustained development. In addition, this paper apply the hyper spectrum graphs by the FieldSpec Pro spectroradiometer, together with the analytical data from environmental chemical, to study the growth of vegetation which were seed in the land-over consisting of gangue, which is a new method to study the impact to vegetation that are growing in the soil.

The suitability of visible spectral response of vegetation for remote sensing has been investigated with field and laboratory studies on canopy and chloroplastidial pigments, respectively. To simulate band-spectral and hyperspectral sensing, measurements were taken both in wavebands and with fine resolution of wavelength. Vegetation species and maturity stages were distinguished with average reflectance and characteristic absorption features. The methodology was tried on both land vegetation, viz. jute canopy of West Bengal and marine plant, viz. green algae of the eastern coast of India. The absorbance variation within visible wavelength range was observed with both mixed chlorophyll solution and solutions of chromatographically separated pigments. The different characteristic absorption peaks were identified, which were quite different for higher plants and algae. The gradual changes in spectral response of leaf pigments with senescence in a common higher plant were systematically investigated with both original leaf extracts and artificial mixtures of fresh and decomposed chlorophyll solutions at different ratios. Mathematical models were put forward for both average and hyperspectral absorption features to track the experimental plots and estimate absorption at different wavelengths.

In-situ measurements of the bio-optical properties of the seawater are important to develop algorithms for seawater constituent estimation using satellite remote sensing. A data collection campaign was conducted for bio-optical characterization of the open and coastal waters of the Arabian Sea during April 15-29, 2006. Bio-optical measurements were made using the Satlantic hyper-spectral underwater radiometer (Hyperpro-II) for 13 sampling stations include oligotrophic, Trichodesmium bloom dominated and coastal waters in 400-800 nm spectral range. For open oceans stations 1% light was available at 50 to 70 meter depth, whereas, for coastal waters it varied from 18 to 35 meter. The deep chlorophyll maxima (DCM) was observed at 30 to 42 meter depth during the bloom conditions with surface chlorophyll-a concentration ranging between 0.1 to 0.85 mg m^-3 whereas, for open ocean and non-bloom conditions the DCM depth varied from 35 to 60 m with surface chlorophyll ranging between 0.05 to 0.12 mgm^-3. Particulate back scattering coefficient at 700-nm vary from 0.0011 to 0.0031 for bloom waters and 0.00046 to 0.0012 for open ocean waters. The normalized water leaving radiance computed from these spectra in the spectral bands of IRS-P4, OCM bands were examined. The global ocean chlorophyll-2 (OC2), and 4 (OC4) algorithms performed reasonably well for open ocean waters, however both the algorithms overestimated chlorophyll concentration for bloom dominated waters.

The visible light reflected from a wind-roughened sea surface contains information about the sea state in the form of its polarisation status. Each sea state is characterised by a specific wave-slope distribution depending upon the nature of surface winds. This in turn, imparts unique polarisation characteristics to the light reflected from a wind-roughened sea surface in accordance with Fresnel's reflection laws as established by earlier studies. In this paper, we discuss the significance of surface reflected light in the context of using it for remote sensing of sea state. We propose the design for an instrument that will view the wind-roughened sea surface over a period of time and compute the fraction of plane polarised light received by it. The results then can be related to the sea state and the wind speed prevailing over the sea. The instrument can be made to view the sea surface at any look angle though the angles in the range of 30-40 and 65-70 degrees are found to be preferable for better resolution of sea states. The proposed instrument can be mounted on an observation tower, aircraft or a satellite. The range of wind speeds that can be sensed by the proposed instrument is 0-60 knots.

The rapid growth of impervious land covers within urbanizing regions holds many negative implications for environmental quality. The study region is the drinking water conservation areas of Shanghai, which is very important to the megalopolis. Mapping of imperviousness has shown important potentials to acquire such information in great spatial detail but the actual mapping process has been challenged by the heterogeneity of urban and suburb environment and the spatial and spectra capabilities of the sensor. This study focused on mapping the imperviousness fraction using linear spectral unmixing in the area from Landsat satellite remote sensing data. Development of high-quality fraction images depends greatly on the selection of suitable endmembers. A multi-endmemer linear spectral unmixing were evaculated. In the approach, each of the class hold multi-image-endmember representing the heterogeneity of them. The best fraction images were chosen to determine the imperviousness. An unconstrained least-squares solution was used to unmix the MNF components into fraction images. The multi-endmember linear spectral unmixing is then used to map imperviousness fraction for the years of 1987, 1997 and 2006 in upper region of Huangpu River, respectively. In the water resources reservation of Shanghai, the impervious surface area increases approximately 3 times from 1987 to 2002.

Airborne remote sensing has the characteristics of flexible action, wide coverage area and high space resolution, and the hyper-spectral scanner is of very high spectral resolution with more than two hundreds channels in the visible light domain, containing large amount of information, which has tremendous potential in marine application. In 2005, an airborne hyper spectral system AISA+ made by Specim Co. Finland has been tested onboard the Chinese Marine Surveillance Plane. After experimentation and processing with ENVI and some own algorithms, sea surface suspended material is retrieved plus other water quality parameters, showing its application in ocean remote sensing. In this paper, we describe the system futures and experimentation, and then explain the performing of data processing. Some products, such as sea surface suspended material concentration has been obtained. The preliminary result shows that hyper spectral system AISA+ is of much use for marine surveillance, but more technologies are required to develop for monitoring water quality by AISA+.

For any meaningful analysis of geostationary satellite data images, it is necessary to have accurate geographic locations of each pixel which requires accurate information about the satellite altitude, attitude and scanning geometry. Except above, in general, users are provided with the information about the count values of satellite image, sub-satellite point geographic location, image size and scanning direction. Sometimes, the geographic location data is available at coarse interval which is not adequate for the purpose of geophysical parameter retrieval, validation and other applications. The problem is further compounded by data dropouts and garbling affecting the automated detection of earth disk required for deriving geographic locations of the pixels. An automated procedure has been developed to find the geographic locations of the earth view pixels. For the situations with noisy data and attitude errors in roll and pitch but with correct and stable sub-satellite point geographic location, methods have been developed for space view noise rejection, earth disk detection, proper overlaying of continental boundaries and finally for determining geographic locations of desired pixels. These procedures, except the yaw attitude error, automatically correct other attitude errors for each image. The basic assumption made here is that the sub-satellite point location is correct and stable. The method is useful in the absence of any information except the image specifications. Examples of INSAT and METEOSAT images will be presented.

This paper presents systematic lossless data compression studies conducted at Cooperative Institute of Meteorological Satellite Studies (CIMSS), University of Wisconsin-Madison in support of the real-time rebroadcast of NOAA's future GOES ultraspectral sounders. Ultraspectral sounders provide data with high spectral and spatial resolutions. Since an ultraspectral sounder could be either a grating spectrometer or a Michelson interferometer, we have investigated/developed various 2D and 3D lossless compression techniques for both grating and interferometer data. The lossless compression results are obtained and compared from wavelet/multiwavelt transform-based (e.g. JPEG2000, 3D SPIHT, MWT), prediction-based (e.g. JPEG-LS, CALIC), projection-based (e.g. Lossless PCA, Optimized Orthogonal Matching Pursuit-based Linear Prediction, PLT), and clustering-based (e.g. PPVQ, FPVQ, AVQLP) methods. Robust data preprocessing schemes (e.g. BAR, MST reordering) are also demonstrated to improve compression gains of existing state-of-the-art compression methods such as JPEG2000, 3D SPIHT, JPEG-LS, and CALIC for high-spectral-resolution data compression. Our studies show that high lossless compression gains are achievable for both grating and interferometer data.

With ever increasing demand for high spatial and spectral resolutions, high number of bits of multispectral (MS) sensor imagery from space borne systems, but not compensated by an equivalent increase on onboard data transmission or memory limits, efficient data compression and/or streaming approaches gain importance. This paper discusses about the use of JPEG-Like algorithm, for which hardware and software were well proven from the Cartosat-1 spacecraft, to compress onboard high resolution multispectral imagery for future missions. It studies two possible ways of compressing the multispectral data: (1). Apply JPEG-like algorithm bandwise for all three bands, and decompress in ground processing. This would yield compression ratio (CR) of 1:3.31, (2). Combine IRS-Green and Red (since both are highly correlated bands) in quincunx sampling grid, compress the grid and IRS-NIR data by JPEG algorithm. This approach would have the advantage of a higher CR of 1:4.97. It was found that the JPEG like algorithm used in Cartosat-1 could be directly used for MS data onboard as it would still preserve the spatial and spectral contents of the multispectral information after decompression in ground processing. Further research work is required to improve the image quality in the latter case despite the fact that it offers a better CR.

Texture is the key character of remote sensing image classification and a lot of studies on this have been done. This article analyzes the current study situation of remote sensing image classification methods and extracting textural information. Moreover, it analyzes the theory of geostatistics. Based on the geostatistics theory, the variogram is applied to extracting textural information of remote sensing image in this article. It has been proven that the textural information can be used to classification by means of test. At the same time, this article discusses the size of computation window, computation direction and step according to the practical application and puts forward to an auto-adaptive method to determine the size of computation window. In addition, it advances a new method to compute textural information, weighted variogram. Considering that the neural network classification has no limitation to data, this study adopts the back propagation neural network method to classify and recognize the matter combining the textural information extracted by variogram and spectral information. Then the classification results are compared with those gained by maximum likelihood method. The analysis result shows that this method can improve the classification precision.

IRS-P4(Oceansat-1) is the first in the series of Indian operational ocean remote sensing satellites. The payloads of this mission are tailored for making measurements of the physical and biological oceanographic parameters. IRS-P4 contains two sensors, namely Ocean Colour Monitor (OCM) and MSMR. OCM has 8-bands, in which first band, intermittently shows vertical stripings in the raw data. An algorithm based on Discrete Cosine Transform(DCT), is proposed here to model these vertical stripings. Some of the basis function of the DCT has very high degree of similarity with the vertical strips. This work elliminates the vertical strips present in the image by modelling the appropriate coefficients of the basis functions. Results of our work shows that the approach followed by us is effective in removing the vertical strips. To avoid the computational overheads of application of this algorithm on large image, we have divided the image into smaller blocks, the issues of block based processing in frequency domain has been taken care by handling the boundary conditions by means of smoothening.

Spatial data in the form of thematic maps produced from remote sensing images are widely used in many application areas such as hydrology, geology, disaster management, forestry etc. These maps inherently contain uncertainties due to various reasons. The presence of uncertainty in thematic maps degrades the quality of maps and subsequently affects the decisions based on these data. Traditional way of quantifying quality is to compute the overall accuracy of the map, which however does not depict the spatial distribution of quality of whole map. It would be more expedient to use pixel-wise uncertainty as a means of quality indicator of a thematic map. This can be achieved through a number of mathematical tools based on well known theories of probability, geo-statistics, fuzzy sets and rough sets. Information theory and theory of evidence may also be adopted in this context. Nevertheless, there are several challenges involved in characterizing and providing uncertainty information to the users through these theories. The aim of this paper is to apprise the users of remote sensing about the uncertainties present in the thematic maps and to suggest ways to adequately deal with these uncertainties through proper modeling and visualization. Quantification and proper representation of uncertainty to the users may lead to increase in their confidence in using remote sensing derived products.

In this study, a mechanism for quantifying the uncertainty associated with image classification is suggested. In image classification process, an uncertainty measure can be obtained for each pixel thereby indicating that spatial distribution of quality can also be modelled using uncertainty measures. It thus provides an extended information about the quality of spatial data unlike various accuracy measures which indicate quality on map basis or individual class basis (Steele et al., 1998).

Image registration is a key to many image processing tasks such as image fusion, image change detection, GIS overlay operations, 3D visualization etc. The task of image registration needs to become efficient and automatic to process enormous amount of remote sensing data. A number of feature and intensity based image registration techniques are in vogue. The aim of this study is to evaluate the applicability and performance of the two intensity based similarity metrics, namely mutual information and cluster reward algorithm. Image registration task has been mapped as an optimization problem. A combination of a global optimizer namely Genetic algorithm and a local optimizer namely Nelder Mead Simplex algorithm have been successfully used to search registration parameters from the coarsest to the finest level of the image pyramid formed using wavelet transformation. For sound investigations, registration of remote sensing images acquired with varied spatial, spectral characteristics from the ASTER sensor have been considered. The image registration experiments suggest that both the similarity metrics have the capability of successfully registering the images with high accuracy and efficiency. In general, mutual information has yielded more accurate results than cluster reward algorithm.