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NASA NTRS1992

Mariner 10 multispectral images of the eastern limb and farside of the moon

We present the first analysis of Mariner 10 multispectral image data for the eastern limb and farside of the moon. A new, rigorous calibration of these data is used that provides results that are consistent with independently derived data sets. From these newly calibrated data, a color ratio image (0.48/0.58 micron) is produced to show relative TiO2 abundances in mare units on the eastern limb and farside of the moon. Our results indicate that the farside lunar mare deposits examined have TiO2 contents that are intermediate to low (2.5 pct TiO2) relative to mare deposits on the nearside. We find no evidence for areally extensive deposits of either very low titanium or high to very high titanium basalts in these portions of the moon. Our findings support previous interpretations that the source regions for lunar mare basalts are laterally heterogeneous. Additionally, examination of highland units reveals a relatively blue region that corresponds with a previously proposed cryptomare, suggesting enhanced TiO2 for this unit. Finally, based on these Mariner 10 data, telescopic spectral data, Galileo multispectral image data, and lunar meteorite analyses we speculate that volcanism in farside mare deposits did not include high titanium basalts.

Robinson, Mark S.↗

NASA NTRS1993

Understanding land surface evapotranspiration with satellite multispectral measurements

Quantitative use of remote multispectral measurements to study and map land surface evapotranspiration has been a challenging issue for the past 20 years. Past work is reviewed against process physics. A simple two-layer combination-type model is used which is applicable to both vegetation and bare soil. The theoretic analysis is done to show which land surface properties are implicitly defined by such evaporation models and to assess whether they are measurable as a matter of principle. Conceptual implications of the spatial correlation of land surface properties, as observed by means of remote multispectral measurements, are illustrated with results of work done in arid zones. A normalization of spatial variability of land surface evaporation is proposed by defining a location-dependent potential evaporation and surface temperature range. Examples of the application of remote based estimates of evaporation to hydrological modeling studies in Egypt and Argentina are presented.

Menenti, M.↗

NASA NTRS1992

Multispectral thermal infrared mapping of the 1 October 1988 Kupaianaha flow field, Kilauea volcano, Hawaii

Multispectral thermal infrared radiance measurements of the Kupaianaha flow field were acquired with the NASA airborne Thermal Infrared Multispectral Scanner (TIMS) on the morning of 1 October 1988. The TIMS data were used to map both the temperature and emissivity of the surface of the flow field. The temperature map depicted the underground storage and transport of lava. The presence of molten lava in a tube or tumulus resulted in surface temperatures that were at least 10 C above ambient. The temperature map also clearly defined the boundaries of hydrothermal plumes which resulted from the entry of lava into the ocean. The emissivity map revealed the boundaries between individual flow units within the Kupaianaha field. Distinct spectral anomalies, indicative of silica-rich surface materials, were mapped near fumaroles and ocean entry sites. This apparent enrichment in silica may have resulted from an acid-induced leaching of cations from the surfaces of glassy flows.

Realmuto, Vincent J.↗

NASA NTRS1993

Classification of multispectral image data by the Binary Diamond neural network and by nonparametric, pixel-by-pixel methods

The classification of multispectral image data obtained from satellites has become an important tool for generating ground cover maps. This study deals with the application of nonparametric pixel-by-pixel classification methods in the classification of pixels, based on their multispectral data. A new neural network, the Binary Diamond, is introduced, and its performance is compared with a nearest neighbor algorithm and a back-propagation network. The Binary Diamond is a multilayer, feed-forward neural network, which learns from examples in unsupervised, 'one-shot' mode. It recruits its neurons according to the actual training set, as it learns. The comparisons of the algorithms were done by using a realistic data base, consisting of approximately 90,000 Landsat 4 Thematic Mapper pixels. The Binary Diamond and the nearest neighbor performances were close, with some advantages to the Binary Diamond. The performance of the back-propagation network lagged behind. An efficient nearest neighbor algorithm, the binned nearest neighbor, is described. Ways for improving the performances, such as merging categories, and analyzing nonboundary pixels, are addressed and evaluated.

Salu, Yehuda↗

NASA NTRS1995

For geological investigations with airborne thermal infrared multispectral images: Transfer of calibration from laboratory spectrometer to TIMS as alternative for removing atmospheric effects

This paper describes an empirical method to correct TIMS (Thermal Infrared Multispectral Scanner) data for atmospheric effects by transferring calibration from a laboratory thermal emission spectrometer to the TIMS multispectral image. The method does so by comparing the laboratory spectra of samples gathered in the field with TIMS 6-point spectra for pixels at the location of field sampling sites. The transference of calibration also makes it possible to use spectra from the laboratory as endmembers in unmixing studies of TIMS data.

Edgett, Kenneth S.↗

NASA NTRS1994

The use of multispectral thermal infrared image data to estimate the sulfur dioxide flux from volcanoes: A case study from Mount Etna, Sicily, July 29, 1986

We have found that image data acquired with NASA's airborne Thermal Infrared Multispectral Scanner (TIMS) can be used to make estimates of the SO2 content of volcanic plumes. TIMS image data are most applicable to the study of partially transparent SO2 plumes, such as those released during quiescent periods or nonexplosive eruptions. The estimation procedure is based on the LOWTRAN 7 radiative transfer code, which we use to model the radiance perceived by TIMS as it views the ground through an SO2 plume. The input to the procedure includes the altitudes of the aircraft and ground, the altitude and thickness of the SO2 plume, the emissivity of the ground, and altitude profiles of the atmospheric pressure, temperature, and relative humidity. We use the TIMS data to estimate both ground temperatures beneath a plume and SO2 concentrations within a plume. Applying our procedure to TIMS data acquired over Mount Etna, Sicily, on July 29, 1986, we estimate that the SO2 flux from the volcano was approximately 6700 t d(exp -1). The use of TIMS to study SO2 plumes represents a bridge between highly localized methods, such as correlation spectroscopy or direct sampling, and small-scale mapping techniques involving satellite instruments such as the Total Ozone Mapping Spectrometer or Microwave Limb Sounder. We require further airborne experiments to refine our estimation procedure. This refinement is a necessary preparation for the schedueled 1998 launch of the Advanced Spaceborne Thermal Emission and Reflectance Radiometer, which will allow large-scale multispectral thermal infrared image data to be collected over virtually any volcano on Earth at least once every 16 days.

Realmuto, Vincent J.↗

NASA NTRS1999

Implementation of Multispectral Image Classification on a Remote Adaptive Computer

As the demand for higher performance computers for the processing of remote sensing science algorithms increases, the need to investigate new computing paradigms its justified. Field Programmable Gate Arrays enable the implementation of algorithms at the hardware gate level, leading to orders of m a,gnitude performance increase over microprocessor based systems. The automatic classification of spaceborne multispectral images is an example of a computation intensive application, that, can benefit from implementation on an FPGA - based custom computing machine (adaptive or reconfigurable computer). A probabilistic neural network is used here to classify pixels of of a multispectral LANDSAT-2 image. The implementation described utilizes Java client/server application programs to access the adaptive computer from a remote site. Results verify that a remote hardware version of the algorithm (implemented on an adaptive computer) is significantly faster than a local software version of the same algorithm implemented on a typical general - purpose computer).

Figueiredo, Marco A.↗

NASA NTRS2000

High Spatial Resolution Airborne Multispectral Thermal Infrared Remote Sensing Data for Analysis of Urban Landscape Characteristics

We have used airborne multispectral thermal infrared (TIR) remote sensing data collected at a high spatial resolution (i.e., 10m) over several cities in the United States to study thermal energy characteristics of the urban landscape. These TIR data provide a unique opportunity to quantify thermal responses from discrete surfaces typical of the urban landscape and to identify both the spatial arrangement and patterns of thermal processes across the city. The information obtained from these data is critical to understanding how urban surfaces drive or force development of the Urban Heat Island (UHI) effect, which exists as a dome of elevated air temperatures that presides over cities in contrast to surrounding non-urbanized areas. The UHI is most pronounced in the summertime where urban surfaces, such as rooftops and pavement, store solar radiation throughout the day, and release this stored energy slowly after sunset creating air temperatures over the city that are in excess of 2-4'C warmer in contrast with non-urban or rural air temperatures. The UHI can also exist as a daytime phenomenon with surface temperatures in downtown areas of cities exceeding 38'C. The implications of the UHI are significant, particularly as an additive source of thermal energy input that exacerbates the overall production of ground level ozone over cities. We have used the Airborne Thermal and Land Applications Sensor (ATLAS), flown onboard a Lear 23 jet aircraft from the NASA Stennis Space Center, to acquire high spatial resolution multispectral TIR data (i.e., 6 bandwidths between 8.2-12.2 (um) over Huntsville, Alabama, Atlanta, Georgia, Baton Rouge, Louisiana, Salt Lake City, Utah, and Sacramento, California. These TIR data have been used to produce maps and other products, showing the spatial distribution of heating and cooling patterns over these cities to better understand how the morphology of the urban landscape affects development of the UHI. In turn, these data have been used by government officials, urban planners, and other decision-makers, to make more informed decisions on how to mitigate the UHI and its subsequent impacts.

Quattrochi, Dale A.↗

NASA NTRS1982

Multispectral Photography

Model II Multispectral Camera is an advanced aerial camera that provides optimum enhancement of a scene by recording spectral signatures of ground objects only in narrow, preselected bands of the electromagnetic spectrum. Its photos have applications in such areas as agriculture, forestry, water pollution investigations, soil analysis, geologic exploration, water depth studies and camouflage detection. The target scene is simultaneously photographed in four separate spectral bands. Using a multispectral viewer, such as their Model 75 Spectral Data creates a color image from the black and white positives taken by the camera. With this optical image analysis unit, all four bands are superimposed in accurate registration and illuminated with combinations of blue green, red, and white light. Best color combination for displaying the target object is selected and printed. Spectral Data Corporation produces several types of remote sensing equipment and also provides aerial survey, image processing and analysis and number of other remote sensing services.

Source record↗

NASA NTRS2003

Remote Sensing of Liquid Water and Ice Cloud Optical Thickness and Effective Radius in the Arctic: Application of Airborne Multispectral MAS Data

A multispectral scanning spectrometer was used to obtain measurements of the reflection function and brightness temperature of clouds, sea ice, snow, and tundra surfaces at 50 discrete wavelengths between 0.47 and 14.0 microns. These observations were obtained from the NASA ER-2 aircraft as part of the FIRE Arctic Clouds Experiment, conducted over a 1600 x 500 km region of the north slope of Alaska and surrounding Beaufort and Chukchi Seas between 18 May and 6 June 1998. Multispectral images of the reflection function and brightness temperature in 11 distinct bands of the MODIS Airborne Simulator (MAS) were used to derive a confidence in clear sky (or alternatively the probability of cloud), shadow, and heavy aerosol over five different ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (water, ice, or undetermined phase). Finally, the cloud optical thickness and effective radius were derived for both water and ice clouds that were detected during one flight line on 4 June. This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS data in Alaska, is quite capable of distinguishing clouds from bright sea ice surfaces during daytime conditions in the high Arctic. Results of individual tests, however, make it difficult to distinguish ice clouds over snow and sea ice surfaces, so additional tests were added to enhance the confidence in the thermodynamic phase of clouds over the Beaufort Sea. The cloud optical thickness and effective radius retrievals used 3 distinct bands of the MAS, with the newly developed 1.62 and 2.13 micron bands being used quite successfully over snow and sea ice surfaces. These results are contrasted with a MODIS-based algorithm that relies on spectral reflectance at 0.87 and 2.13 micron.

King, Michael D.↗

NASA NTRS2002

Radiometric Characterization of IKONOS Multispectral Imagery

A radiometric characterization of Space Imaging's IKONOS 4-m multispectral imagery has been performed by a NASA funded team from the John C. Stennis Space Center (SSC), the University of Arizona Remote Sensing Group (UARSG), and South Dakota State University (SDSU). Both intrinsic radiometry and the effects of Space Imaging processing on radiometry were investigated. Relative radiometry was examined with uniform Antarctic and Saharan sites. Absolute radiometric calibration was performed using reflectance-based vicarious calibration methods on several uniform sites imaged by IKONOS, coincident with ground-based surface and atmospheric measurements. Ground-based data and the IKONOS spectral response function served as input to radiative transfer codes to generate a Top-of-Atmosphere radiance estimate. Calibration coefficients derived from each vicarious calibration were combined to generate an IKONOS radiometric gain coefficient for each multispectral band assuming a linear response over the full dynamic range of the instrument. These calibration coefficients were made available to Space Imaging, which subsequently adopted them by updating its initial set of calibration coefficients. IKONOS imagery procured through the NASA Scientific Data Purchase program is processed with or without a Modulation Transfer Function Compensation kernel. The radiometric effects of this kernel on various scene types was also investigated. All imagery characterized was procured through the NASA Scientific Data Purchase program.

Pagnutti, Mary↗

NASA NTRS2000

Monitoring Geothermal Features in Yellowstone National Park with ATLAS Multispectral Imagery

The National Park Service (NPS) must produce an Environmental Impact Statement for each proposed development in the vicinity of known geothermal resource areas (KGRAs) in Yellowstone National Park. In addition, the NPS monitors indicator KGRAs for environmental quality and is still in the process of mapping many geothermal areas. The NPS currently maps geothermal features with field survey techniques. High resolution aerial multispectral remote sensing in the visible, NIR, SWIR, and thermal spectral regions could enable YNP geothermal features to be mapped more quickly and in greater detail In response, Yellowstone Ecosystems Studies, in partnership with NASA's Commercial Remote Sensing Program, is conducting a study on the use of Airborne Terrestrial Applications Sensor (ATLAS) multispectral data for monitoring geothermal features in the Upper Geyser Basin. ATLAS data were acquired at 2.5 meter resolution on August 17, 2000. These data were processed into land cover classifications and relative temperature maps. For sufficiently large features, the ATLAS data can map geothermal areas in terms of geyser pools and hot springs, plus multiple categories of geothermal runoff that are apparently indicative of temperature gradients and microbial matting communities. In addition, the ATLAS maps clearly identify geyserite areas. The thermal bands contributed to classification success and to the computation of relative temperature. With masking techniques, one can assess the influence of geothermal features on the Firehole River. Preliminary results appear to confirm ATLAS data utility for mapping and monitoring geothermal features. Future work will include classification refinement and additional validation.

Spruce, Joseph↗

NASA NTRS2005

Large Multispectral and Albedo Panoramas Acquired by the Pancam Instruments on the Mars Exploration Rovers Spirit and Opportunity

Introduction. The panoramic camera (Pancam) multispectral, stereoscopic imaging systems on the Mars Exploration Rovers Spirit and Opportunity [1] have acquired and downlinked more than 45,000 images (~35 Gbits of data) over more than 700 combined sols of operation on Mars as of early January 2005. A large subset of these images were acquired as part of 26 large multispectral and/or broadband "albedo" panoramas (15 on Spirit, 11 on Opportunity) covering large ranges of azimuth (12 spanning 360 ) and designed to characterize major regional color and albedo characteristics of the landing sites and various points along both rover traverses.

Bell, J. F., III↗

NASA NTRS2007

Morphological Feature Extraction for Automatic Registration of Multispectral Images

The task of image registration can be divided into two major components, i.e., the extraction of control points or features from images, and the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual extraction of control features can be subjective and extremely time consuming, and often results in few usable points. On the other hand, automated feature extraction allows using invariant target features such as edges, corners, and line intersections as relevant landmarks for registration purposes. In this paper, we present an extension of a recently developed morphological approach for automatic extraction of landmark chips and corresponding windows in a fully unsupervised manner for the registration of multispectral images. Once a set of chip-window pairs is obtained, a (hierarchical) robust feature matching procedure, based on a multiresolution overcomplete wavelet decomposition scheme, is used for registration purposes. The proposed method is validated on a pair of remotely sensed scenes acquired by the Advanced Land Imager (ALI) multispectral instrument and the Hyperion hyperspectral instrument aboard NASA's Earth Observing-1 satellite.

Plaza, Antonio↗

NASA NTRS2007

Application of High Resolution Multispectral Imagery for Levee Slide Detection and Monitoring

The objective is to develop methods to detect and monitor levee slides using commercially available high resolution multispectral imagery. High resolution multispectral imagery like IKONOS and QuickBird are suitable for detecting and monitoring levee slides. IKONOS is suitable for visual inspection, image classification and Tasseled Cap transform based slide detection. Tasseled Cap based model was found to be the best method for slide detection. QuickBird was suitable for visual inspection and image classification.

Hossain, A. K. M. Azad↗

NASA NTRS2009

A Multispectral Micro-Imager for Lunar Field Geology

Field geologists routinely assign rocks to one of three basic petrogenetic categories (igneous, sedimentary or metamorphic) based on microtextural and mineralogical information acquired with a simple magnifying lens. Indeed, such observations often comprise the core of interpretations of geological processes and history. The Multispectral Microscopic Imager (MMI) uses multi-wavelength, light-emitting diodes (LEDs) and a substrate-removed InGaAs focal-plane array to create multispectral, microscale reflectance images of geological samples (FOV 32 X 40 mm). Each pixel (62.5 microns) of an image is comprised of 21 spectral bands that extend from 470 to 1750 nm, enabling the discrimination of a wide variety of rock-forming minerals, especially Fe-bearing phases. MMI images provide crucial context information for in situ robotic analyses using other onboard analytical instruments (e.g. XRD), or for the selection of return samples for analysis in terrestrial labs. To further assess the value of the MMI as a tool for lunar exploration, we used a field-portable, tripod-mounted version of the MMI to image a variety of Apollo samples housed at the Lunar Experiment Laboratory, NASA s Johnson Space Center. MMI images faithfully resolved the microtextural features of samples, while the application of ENVI-based spectral end member mapping methods revealed the distribution of Fe-bearing mineral phases (olivine, pyroxene and magnetite), along with plagioclase feldspars within samples. Samples included a broad range of lithologies and grain sizes. Our MMI-based petrogenetic interpretations compared favorably with thin section-based descriptions published in the Lunar Sample Compendium, revealing the value of MMI images for astronaut and rover-mediated lunar exploration.

Nunez, Jorge↗

NASA NTRS2007

Multispectral Imager With Improved Filter Wheel and Optics

Figure 1 schematically depicts an improved multispectral imaging system of the type that utilizes a filter wheel that contains multiple discrete narrow-band-pass filters and that is rotated at a constant high speed to acquire images in rapid succession in the corresponding spectral bands. The improvement, relative to prior systems of this type, consists of the measures taken to prevent the exposure of a focal-plane array (FPA) of photodetectors to light in more than one spectral band at any given time and to prevent exposure of the array to any light during readout. In prior systems, these measures have included, variously the use of mechanical shutters or the incorporation of wide opaque sectors (equivalent to mechanical shutters) into filter wheels. These measures introduce substantial dead times into each operating cycle intervals during which image information cannot be collected and thus incoming light is wasted. In contrast, the present improved design does not involve shutters or wide opaque sectors, and it reduces dead times substantially. The improved multispectral imaging system is preceded by an afocal telescope and includes a filter wheel positioned so that its rotation brings each filter, in its turn, into the exit pupil of the telescope. The filter wheel contains an even number of narrow-band-pass filters separated by narrow, spoke-like opaque sectors. The geometric width of each filter exceeds the cross-sectional width of the light beam coming out of the telescope. The light transmitted by the sequence of narrow-band filters is incident on a dichroic beam splitter that reflects in a broad shorter-wavelength spectral band that contains half of the narrow bands and transmits in a broad longer-wavelength spectral band that contains the other half of the narrow spectral bands. The filters are arranged on the wheel so that if the pass band of a given filter is in the reflection band of the dichroic beam splitter, then the pass band of the adjacent filter is in the longer-wavelength transmission band of the dichroic beam splitter (see Figure 2). Each of the two optical paths downstream of the dichroic beam splitter contains an additional broad-band-pass filter: The filter in the path of the light transmitted by the dichroic beam splitter transmits and attenuates in the same bands that are transmitted and reflected, respectively, by the beam splitter; the filter in the path of the light reflected by the dichroic beam splitter transmits and attenuates in the same bands that are reflected and transmitted, respectively, by the dichroic beam splitter. In each of these paths, the filtered light is focused onto an FPA. As the filter wheel rotates at a constant angular speed, its shaft angle is monitored, and the shaft-angle signal is used to synchronize the exposure times of the two FPAs. When a single narrowband-pass filter on the wheel occupies the entire cross section of the beam of light coming out of the telescope, the spectrum of light that reaches the dichroic beam splitter lies entirely within the pass band of that filter. Therefore, the beam in its entirety is either transmitted by the dichroic beam splitter and imaged on the longer-wavelength FPA or reflected by the beam splitter and imaged onto the shorter-wavelength FPA.

Bremer, James C.↗

NASA NTRS2009

Low-Complexity Lossless and Near-Lossless Data Compression Technique for Multispectral Imagery

This work extends the lossless data compression technique described in Fast Lossless Compression of Multispectral- Image Data, (NPO-42517) NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26. The original technique was extended to include a near-lossless compression option, allowing substantially smaller compressed file sizes when a small amount of distortion can be tolerated. Near-lossless compression is obtained by including a quantization step prior to encoding of prediction residuals. The original technique uses lossless predictive compression and is designed for use on multispectral imagery. A lossless predictive data compression algorithm compresses a digitized signal one sample at a time as follows: First, a sample value is predicted from previously encoded samples. The difference between the actual sample value and the prediction is called the prediction residual. The prediction residual is encoded into the compressed file. The decompressor can form the same predicted sample and can decode the prediction residual from the compressed file, and so can reconstruct the original sample. A lossless predictive compression algorithm can generally be converted to a near-lossless compression algorithm by quantizing the prediction residuals prior to encoding them. In this case, since the reconstructed sample values will not be identical to the original sample values, the encoder must determine the values that will be reconstructed and use these values for predicting later sample values. The technique described here uses this method, starting with the original technique, to allow near-lossless compression. The extension to allow near-lossless compression adds the ability to achieve much more compression when small amounts of distortion are tolerable, while retaining the low complexity and good overall compression effectiveness of the original algorithm.

Xie, Hua↗