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We discuss the DISORT-based radiative transfer pipeline ('CRISM_LambertAlb') for atmospheric and thermal correction of MRO/CRISM data acquired in multispectral mapping mode (~200 m/pixel, 72 spectral channels). Currently, in this phase-one version of the system, we use aerosol optical depths, surface temperatures, and lower-atmospheric temperatures, all from climatology derived from Mars Global Surveyor Thermal Emission Spectrometer (MGS-TES) data, and surface altimetry derived from MGS Mars Orbiter Laser Altimeter (MOLA). The DISORT-based model takes as input the dust and ice aerosol optical depths (scaled to the CRISM wavelength range), the surface pressures (computed from MOLA altimetry, MGS-TES lower-atmospheric thermometry, and Viking-based pressure climatology), the surface temperatures, the reconstructed instrumental photometric angles, and the measured I/F spectrum, and then outputs a Lambertian albedo spectrum. The Lambertian albedo spectrum is valuable geologically since it allows the mineralogical composition to be estimated. Here, I/F is defined as the ratio of the radiance measured by CRISM to the solar irradiance at Mars divided by $\pi$. After discussing the capabilities and limitations of the pipeline software system, we demonstrate its application on several multispectral data cubes: the outer northern ice cap of Mars, Tyrrhena Terra, and near the landing site for the Phoenix mission. For the icy spectra near the northern polar cap, aerosols need to be included in order to properly correct for the CO_2 absorption in the H_{2}O ice bands at wavelengths near 2.0 $\mu$m. In future phases of software development, we intend to use CRISM data directly in order to retrieve the spatiotemporal maps of aerosol optical depths, surface pressure and surface temperature.

The Moon Mineralogy Mapper (M3), a NASA Discovery Mission of Opportunity, was launched October 22, 2008 from Shriharikota in India on board the Indian ISRO Chandrayaan- 1 spacecraft for a nominal two-year mission in a 100-km polar lunar orbit. M3 is a high-fidelity imaging spectrometer with 260 spectral bands in Target Mode and 85 spectral bands in a reduced-resolution Global Mode. Target Mode pixel sizes are nominally 70 meters and Global pixels (binned 2 by 2) are 140 meters, from the planned 100-km orbit. The mission was cut short, just before halfway, in August, 2009 when the spacecraft ceased operations. Despite the abbreviated mission and numerous technical and scientific challenges during the flight, M3 was able to cover more than 95% of the Moon in Global Mode. These data, presented and analyzed here as a global whole, are revolutionizing our understanding of the Moon. Already, numerous discoveries relating to volatiles and unexpected mineralogy have been published [1], [2], [3]. The rich spectral and spatial information content of the M3 data indicates that many more discoveries and an improved understanding of the mineralogy, geology, photometry, thermal regime and volatile status of our nearest neighbor are forthcoming from these data. Sadly, only minimal high-resolution Target Mode images were acquired, as these were to be the focus of the second half of the mission. This abstract gives the reader a global overview of all the M3 data that were collected and an introduction to their rich spectral character and complexity. We employ a Principal Components statistical method to assess the underlying dimensionality of the Moon as a whole, as seen by M3, and to identify numerous areas that are low-probability targets and thus of potential interest to selenologists.

The canonical characterization of the lunar crust is based principally on available Apollo, Luna, and meteorite samples. The crust is described as an anorthosite-rich cumulate produced by the lunar magma ocean that has been infused with a mix of Mgsuite components. These have been mixed and redistributed during the late heavy bombardment and basin forming events. We report a new rock-type detected on the farside of the Moon by the Moon Mineralogy Mapper (M3) on Chandrayaan-1 that does not easily fit with current crustal evolution models. The rock-type is dominated by Mg-spinel with no detectible pyroxene or olivine present (<5%). It occurs along the western inner ring of Moscoviense Basin as one of several discrete areas that exhibit unusual compositions relative to their surroundings but without morphological evidence for separate processes leading to exposure.

India's Chandrayaan-1 successfully launched October 22, 2008 and went into lunar orbit a few weeks later. Commissioning of instruments began in late November and was near complete by the end of the year. Initial data for NASA's Moon Mineralogy Mapper (M3) were acquired across the Orientale Basin and the science results are discussed here. M 3 image-cube data provide mineralogy of the surface in geologic context. A major new result is that the existence and distribution of massive amounts of anorthosite as a continuous stratigraphic crustal layer is now irrefutable.

The largest exposure of phyllosilicates on Mars occurs on the highland plains around Mawrth Vallis. This exposure extends for about 300 km southward from the edge of the dichotomy boundary, covering an area greater than 200 x 300 kilometers over an elevation range of approximately 2000 meters. At least two different types of hydrated phyllosilicates (Fe/Mg-rich and Al-rich phyllosilicates) have been identified in OMEGA data based on absorption bands near 2.3 and 2.2 micrometers, respectively. These clay-bearing units are associated with layered, indurated light-toned units with complex spatial and stratigraphic relationships, and are unconfomably overlain by a darker, indurated, more heavily cratered unit. Ongoing analysis of OMEGA (approximately 1 kilometer/pixel) and CRISM multi-spectral (MSP, 200 meters/pixel) data reveal hydrated minerals with absorptions at approximately 2.2 or 2.3 micrometers in locations up to 300 kilometers away from the borders of the previously identified extent of clay-bearing units. We seek to: 1) further constrain the mineralogy of the hydrated species identified in [5], and 2) understand spatial and stratigraphic relationships between the different hydrated minerals and the cratered plains units in which they are found. In this work we perform mineralogical and stratigraphic comparisons between units to test whether these extended units may be related, in order to establish a broad zone of alteration.

One of the chief scientific objectives of the Clementine mission at the Moon was to acquire global multispectral mapping. A global digital map of the Moon in 11 spectral bandpasses and at a scale of 100 m/pixel is being produced at the U.S. Geological Survey in Flagstaff Arizona Near-global coverage was acquired with the UVVIS camera (central wavelengths of 415, 750, 900, 950, and 1000 nm) and the NIR camera (1102, 1248, 1499, 1996, 2620, and 2792 nary). We expect to complete processing of the UVVIS mosaics before the fall of 1998, and to complete the NIR mosaics a year later. The purpose of this poster is to provide an update on the processing and to show examples of the products or perhaps even a wall-sized display of color products from the UVVIS mosaics.

Several types of noise in remote-sensing systems are treated. The purpose is to provide enhanced understanding of the relationship of noise sources to both analysis results and sensor design. The context of optical sensors and spectral pattern recognition analysis methods is used to enable tractability for quantitative results. First, the concept of multispectral classification is reviewed. Next, stochastic models are discussed for both signals and noise, including thermal, shot and quantization noise along with atmospheric effects. A model enabling the study of the combined effect of these sources is presented, and a system performance index is defined. Theoretical results showing the interrelated effects of the noise sources on system performance are given. Results of simulations using the system model are presented for several values of system parameters, using some noise parameters of the Thematic Mapper scanner as an illustration. Results show the relative importance of each of the noise sources on system performance, including how sensor noise interacts with atmospheric effects to degrade accuracy.

The problem of estimating the overall point-spread function (PSF) of multispectral scanner systems was studied using real scene data and known geometric structures in the scene. A direct solution to an approximate form of the PSF was made along with a method using the derivative of an estimated edge response. Both results agreed closely. The TM scanner system specifications are given in line-spread function width and these values are listed with the experimental results in terms of meters. The estimated values are very reasonable, considering the number of factors which could be influencing the result. The atmosphere will have a blurring effect on the overall PSF as well as on cubic convolution resampling effects and possible electronic effects not accounted for in the specification. Also, the specific definition of the LSF specification is not known nor is the actual altitude at the instant the data were acquired. Thus the nominal overall PSF half-amplitude width of 39 m is reasonable; however, a greater sample of scene objects should be evaluated to furthur verify this result.

A LANDSAT Thematic Mapper (TM) quality evaluation study was conducted to identify geometric and radiometric sensor errors in the post-launch environment. The study began with the launch of LANDSAT-4. Several error conditions were found, including band-to-band misregistration and detector-to detector radiometric calibration errors. Similar analysis was made for the LANDSAT-5 Thematic Mapper and compared with results for LANDSAT-4. Remaining band-to-band misregistration was found to be within tolerances and detector-to-detector calibration errors were not severe. More coherent noise signals were observed in TM-5 than in TM-4, although the amplitude was generally less. The scan direction differences observed in TM-4 were still evident in TM-5. The largest effect was in Band 4 where nearly a one digital count difference was observed. Resolution estimation was carried out using roads in TM-5 for the primary focal plane bands rather than field edges as in TM-4. Estimates using roads gave better resolution. Thermal IR band calibration studies were conducted and new nonlinear calibration procedures were defined for TM-5. The overall conclusion is that there are no first order errors in TM-5 and any remaining problems are second or third order.

LANDSAT-4 thematic mapper (TM) and multispectral scanner (MSS) data were analyzed to obtain information on data quality and information content. Geometric evaluations were performed to test band-to-band registration accuracy. Thematic mapper overall system resolution was evaluated using scene objects which demonstrated sharp high contrast edge responses. Radiometric evaluation included detector relative calibration, effects of resampling, and coherent noise effects. Information content evaluation was carried out using clustering, principal components, transformed divergence separability measure, and supervised classifiers on test data. A detailed spectral class analysis (multispectral classification) was carried out to compare the information content of the MSS and TM for a large number of scene classes. A temperature-mapping experiment was carried out for a cooling pond to test the quality of thermal-band calibration. Overall TM data quality is very good. The MSS data are noisier than previous LANDSAT results.

Experiments to determine overall radiometric resolution are discussed. Scene structures, such as roads and field edges, are used with numerical estimation procedures to predict resolution in LANDSAT 4 Thematic Mapper imagery. A nominal resolution of 39 meters is determined rather than the predicted 30 meter prelaunch estimates.

A detailed spectral analysis is conducted of thematic mapper and MSS data for an area near Des Moines, Iowa. Data are utilized from 7 blocks distributed throughout the area which included agricultural, forest, suburan, urban, and water scene types. The blocks are processed using a clustering algorithm to produce up to 18 cluster groupings for each block. Each cluster class is then identified with a ground-cover class using aerial photography and maps of the area. The clusters from each of the 7 blocks are inspected with regard to separability, mean, and variances. The separability measure used in the transformed divergence function or processor measures the statistical distance between classes based on class means and covariance matrices. The measure has a maximum value of 2,000 and the minimum of 0. Spectrally, very close classes will typically have values as low as 50 to 500.

Landsat-4 Thematic Mapper and Multispectral Scanner data were analyzed to obtain information on data quality and information content. Geometric evaluations were performed to test band-to-band registration accuracy. Thematic Mapper overall system resolution was evaluated using scene objects which demonstrated sharp high contrast edge responses. Radiometric evaluation included detector relative calibration, effects of resampling, and coherent noise effects. Information content evaluation was carried out using clustering, principal components, transformed divergence separability measure, and numerous supervised classifiers on data from Iowa and Illinois. A detailed spectral class analysis (multispectral classification) was carried out on data from the Des Moines, IA area to compare the information content of the MSS and TM for a large number of scene classes.

Satellite-based multispectral imaging systems have been in operation since 1972 and the latest in the Landsat series of sensors was launched in July 1982. One system parameter of interest is resolution and this paper discusses experiments to determine the actual overall resolution after launch. Experimental results for the spatial resolution estimation of bands four and five of the Landsat-D Thematic Mapper are presented here.

Landsat-4 satellite Thematic Mapper (TM) and multispectral scanner (MSS) data have been analyzed in order to ascertain data quality and information content. Geometric evaluations have tested band-to-band registration accuracy, and the TM's overall system resolution was evaluated for the case of image objects with high contrast, sharp edge responses. The information content evaluation employed clustering, principal components, and the transformed divergence separability measured on data from Iowa and Chicago, Illinois. The MSS classification analysis compared MSS and TM information contents for a large number of science classes.

A general approach to identifying the point spread function (PSF) of a remotely sensed scene is demonstrated in terms of a step function for an abrupt change in the gray level along the row or column of the image data. The estimate of the PSF is made in terms of a finite sum of basis functions, employing a sequence of rectangular pulses covering the spatial extent of the PSF. The approximation, if narrow impulses are employed, provides accurate fidelity to the PSF. The method becomes practical when the geometrical structure of the scene elements producing the measured response is known. The field boundary is obtained through consideration of the differing intensities on each side of the boundary, which is a step discontinuity. The mathematical procedure for the technique is provided, together with a sample problem from Landsat-4 Thematic Mapper data. Atmospheric blurring and electronic effects on the overall PSF and the cubic convolution resampling effects are noted.

A stochastic model for the data acquisition system in a multispectral scanner system, like the one utilized by the LANDSAT satellites, is presented. A list of noise sources which are known or presumed to have a significant effect in the information extraction process was constructed. Since the shot noise introduced by the photodetectors in the sensor system is signal level dependent, an atmospheric model was adopted which could adequately describe the amount of radiation that gets into the sensors based on the atmospheric transmittance. An analysis was carried out to find the output spectral statistics in terms of the input signal statistics and the system parameters. This was integrated into a set of FORTRAN programs that when supplied with, the class statistics, the noise levels introduced by the sensor system, the atmospheric transmittance, and the atmospheric path radiance, can be used to estimate the classification performance. In order to show the beneficts of this model a series of runs were performed in which the Thematic Mapper multispectral scanner was the system under consideration.