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Imaging of Uranus and Neptune in the deep methane absorption band at 890nm is used to detect high altitude atmospheric hazes and to search for possible undiscovered close in satellites. The appearances of Uranus and Neptune are very different from one another and Uranus seems to be changing with time. The Neptune images show rotation in the direct sense.
Progress to date and intended goals in the development of the Spaceborne Imaging Radar (SIR), a SAR remote sensing instrument targeted for carriage on one of the three polar orbiting earth observation system (EOS) platforms in the 1990s, are described. The Shuttle is the current testbed for the SIR, with spaceborne trials being used for testing continually upgraded versions of the three major components of the SIR: the electronics, the antenna and the digital data system. Experimentation is being performed in X-, K-, C- and P-bands in terms of the SNR, view angle, resolution and specific terrestrial features. The test flights are also serving to identify the most effective orbits, with consideration given to the capabilities of other instrumentation being developed for the EOS.
Surface coatings on volcanic rock assemblages that occur at select tertiary volcanic centers in southern Nevada were investigated using LANDSAT 5 Thematic Mapper imagery. Three project sites comprise the subject of this study: the Kane Springs Wash, Black Mountain, and Stonewall Mountain volcanic centers. LANDSAT 5 TM work scenes selected for each area are outlined along with local area geology. The nature and composition of surface coatings on the rock types within the subproject areas are determined, along with the origin of the coatings and their genetic link to host rocks, geologic interpretations are related to remote sensing units discriminated on TM imagery. Image processing was done using an ESL VAX/IDIMS image processing system, field sampling, and observation. Aerial photographs were acquired to facilitate location on the ground and to aid stratigraphic differentiation.
Methods of applying principal component (PC) analysis to high resolution remote sensing imagery were examined. Using Airborne Imaging Spectrometer (AIS) data, PC analysis was found to be useful for removing the effects of albedo and noise and for isolating the significant information on argillic alteration, zeolite, and carbonate minerals. An effective technique for using PC analysis using an input the first 16 AIS bands, 7 intermediate bands, and the last 16 AIS bands from the 32 flat field corrected bands between 2048 and 2337 nm. Most of the significant mineralogical information resided in the second PC. PC color composites and density sliced images provided a good mineralogical separation when applied to a AIS data set. Although computer intensive, the advantage of PC analysis is that it employs algorithms which already exist on most image processing systems.
The concept of the imaging spectrometer is becoming established as a major new thrust in remote sensing of the earth. For several years, JPL has operated the airborne imaging spectrometer on a NASA C-130; this instrument has demonstrated the direct identification of surface materials using imaging spectrometry. An advanced aircraft instrument, the airborne visible/infrared imaging spectrometer (AVIRIS), began operation on a NASA U-2 in 1987. The Shuttle Imaging Spectrometer Experiment (SISEX) was conceived as the next step in the sequence, and would provide a relatively inexpensive demonstration of the concept in earth orbit. This paper describes the design and development status of SISEX and the status of the enabling technology.
The development of a machine vision system to monitor plant growth and health is one of three essential steps towards establishing an intelligent system capable of accurately assessing the state of a controlled ecological life support system for long-term space travel. Besides a network of sensors, simulators are needed to predict plant features, and artificial intelligence algorithms are needed to determine the state of a plant based life support system. Multispectral machine vision and image processing can be used to sense plant features, including health and nutritional status.
We present a maximum a posteriori (MAP) classifier for classifying multifrequency, multilook, single polarization SAR intensity data into regions or ensembles of pixels of homogeneous and similar radar backscatter characteristics. A model for the prior joint distribution of the multifrequency SAR intensity data is combined with a Markov random field for representing the interactions between region labels to obtain an expression for the posterior distribution of the region labels given the multifrequency SAR observations. The maximization of the posterior distribution yields Bayes's optimum region labeling or classification of the SAR data or its MAP estimate. The performance of the MAP classifier is evaluated by using computer-simulated multilook SAR intensity data as a function of the parameters in the classification process. Multilook SAR intensity data are shown to yield higher classification accuracies than one-look SAR complex amplitude data. The MAP classifier is extended to the case in which the radar backscatter from the remotely sensed surface varies within the SAR image because of incidence angle effects. The results obtained illustrate the practicality of the method for combining SAR intensity observations acquired at two different frequencies and for improving classification accuracy of SAR data.
Advances in imaging spectroscopy have indicated that remotely sensed reflectance measurements of the plant canopy may be used to identify and qualify some classes of canopy biochemicals; however, the manner in which differences in biochemical compositions translate into differences is not well understood. Most frequently, multiple linear regression routines have been used to correlate narrow band reflectance values with measured biochemical concentrations. Although some success has been achieved with such methods for given data sets, the bands selected by multiple regression are not consistent between data sets, nor is it always clear what physical or biological basis underlies the correlation. To examine the relationship between biochemical concentration and leaf reflectance signal we chose to focus on the visible spectrum where the primary biochemical absorbances are due to photosynthetic pigments. Pigments provide a range of absorbance features, occur over a range of concentrations in natural samples, and are ecophysiologically important. Concentrations of chlorophyll, for example, have been strongly correlated to foliar nitrogen levels within a species and to photosynthetic capacity across many species. In addition pigments effectively absorb most of the photosynthetically active radiation between 400-700 nm, a spectral region for which silicon detectors have good signal/noise characteristics. Our strategy has been to sample a variety of naturally occurring species to measure leaf reflectance and pigment compositions. We hope to extend our understanding of pigment reflectance effects to interpret small overlapping absorbances of other biochemicals in the infrared region. For this reason, selected samples were also tested to determine total nitrogen, crude protein, cellulose, and lignin levels. Leaf reflectance spectra measured with AVIRIS bandwidths and wavelengths were compared between species and within species and for differences between seasons, for changes in the the shape of the spectra. We attempt to statistically correlate these shape changes with differences in pigment compositions. In parallel with our comparisons of pigment composition and leaf reflectance, we have modified the PROSPECT leaf reflectance model to test the contributions of pigments or pigment group concentrations. PROSPECT considers a leaf as a multi-layer dielectric plane with an uneven surface. Jacquemoud adapted the basic analysis of Allen for surface effects, a leaf thickness factor, and the absorption of water and chlorophyll (actually all pigments) and the plant matrix. Our modifications to PROSPECT in the forward direction include breaking out the pigment concentration parameter into separate components for chlorophyll a and b and a number of xanthophylls and carotenes, and introducing a shift and convolution function to model the spread and shift from their in vitro measurements to their in vivo state. Further, we have considered how the matrix elements (i.e., all biochemicals and structural effects not modeled explicity) vary with species.
Wentz was the first to convincingly show that satellite microwave radiometers have the potential to measure the oceanic wind vector. The most compelling evidence for this conclusion was the monthly wind vector maps derived solely from a statistical analysis of Special Sensor Microwave Imager (SSM/I) observations. In a qualitative sense, these maps clearly showed the general circulation over the world's oceans. In this report we take a closer look at the SSM/I monthly wind vector maps and compare them to European Center for Medium-Range Weather Forecasts (ECMWF) wind fields. This investigation leads both to an empirical comparison of SSM/I calculated wind vectors with ECMWF wind vectors, and to an examination of possible reasons that the SSM/I calculated wind vector direction would be inherently more reliable at some locations than others.
This NASA Kennedy Space Center (KSC) video release (Part 1 of 2) begins with a presentation given by William J. O'Neil (Galileo Project Manager) describing the status and position of the Galileo spacecraft 7 days prior to the Galileo Earth-2 flyby. Slides are presented including diagrams of the Galileo spacecraft trajectory, trajectory correction maneuvers, and the Venus and asteroid flybys. Torrence Johnson (Galileo Project Scientist) follows Mr. O'Neil with an explanation of the Earth/Moon science activities that will be undertaken during the second Galileo/Earth encounter. These activities include remote sensing, magnetospheric and plasma measurements, and images taken directly from Galileo of the Earth and Moon. Dr. Joseph Veverka (Galileo Imaging Team, Cornell University) then gives a brief presentation of the data collected by the first Galileo/Gaspra asteroid flyby. Images sampled from the 57 photographs taken of Gaspra are presented along with discussions of Gaspra's morphology, shape and size, and surface features. These presentations are followed by a question and answer period given for the benefit of scientific journalists whose subjects include overall Galileo spacecraft health, verification of the Gaspra images timeframe, and the condition of certain scientific spacecraft instruments. Part 2 of this video can be retrieved by using Report No. NONP-NASA-VT-2000001078.
A NASA ER-2 aircraft flight with both Millimeter-wave Imaging radiometer (MIR) and lidar Atmospheric Sensing Experiment (LASE) was made over ocean areas in the eastern United States on September 25, 1995. The water vapor profiles derived from both instruments under both clear and cloudy conditions are compared in this paper. It is shown that good agreement is found between the MIR-derived and the LASE-measured water vapor profiles over the areas of clear-sky condition. In the cloudy areas, the MIR-retrieved values at the altitudes of the cloud layers and below are generally higher than those measured by the LASE.
The NASA/NOAA/AMS Earth Science Electronic Theater presents Earth science observations and visualizations in a historical perspective. Fly in from outer space to Florida and the KSC Visitor's Center. Go back to the early weather satellite images from the 1960s see them contrasted with the latest International global satellite weather movies including killer hurricanes & tornadic thunderstorms. See the latest spectacular images from NASA and NOAA remote sensing missions like GOES, NOAA, TRMM, SeaWiFS, Landsat7, & new Terra which will be visualized with state-of-the art tools.
While the various instruments maintained at the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) Central Facility (CF) provide detailed cloud and radiation measurements for a small area, satellite cloud property retrievals provide a means of examining the large-scale properties of the surrounding region over an extended period of time. Seasonal and inter-annual climatological trends can be analyzed with such a dataset. For this purpose, monthly datasets of cloud and radiative properties from December 1996 through November 1999 over the SGP region have been derived using the layered bispectral threshold method (LBTM). The properties derived include cloud optical depths (ODs), temperatures and albedos, and are produced on two grids of lower (0.5 deg) and higher resolution (0.3 deg) centered on the ARM SGP CF. The extensive time period and high-resolution of the inner grid of this dataset allows for comparison with the suite of instruments located at the ARM CF. In particular, Whole-Sky Imager (WSI) and the Active Remote Sensing of Clouds (ARSCL) cloud products can be compared to the cloud amounts and heights of the LBTM 0.3 deg grid box encompassing the CF site. The WSI provides cloud fraction and the ARSCL computes cloud fraction, base, and top heights using the algorithms by Clothiaux et al. (2001) with a combination of Belfort Laser Ceilometer (BLC), Millimeter Wave Cloud Radar (MMCR), and Micropulse Lidar (MPL) data. This paper summarizes the results of the LBTM analysis for 3 years of GOES-8 data over the SGP and examines the differences between surface and satellite-based estimates of cloud fraction.
The Coastal Research Imaging Spectrometer (CRIS) is an airborne remote-sensing system designed specifically for research on the physical, chemical, and biological characteristics of coastal waters. The CRIS includes a visible-light hyperspectral imaging subsystem for measuring the color of water, which contains information on the biota, sediment, and nutrient contents of the water. The CRIS also includes an infrared imaging subsystem, which provides information on the temperature of the water. The combination of measurements enables investigation of biological effects of both natural and artificial flows of water from land into the ocean, including diffuse and point-source flows that may contain biological and/or chemical pollutants. Temperature is an important element of such measurements because temperature contrasts can often be used to distinguish among flows from different sources: for example, a sewage outflow could manifest itself in spectral images as a local high-temperature anomaly.anomaly. Both the visible and infrared subsystems scan in "pushbroom" mode: that is, an aircraft carrying the system moves along a ground track, the system is aimed downward, and image data are acquired in acrosstrack linear arrays of pixels. Both subsystems operate at a frame rate of 30 Hz. The infrared and visible-light optics are adjusted so that both subsystems are aimed at the same moving swath, which has across-track angular width of 15. Data from the infrared and visible imaging subsystems are stored in the same file along with aircraft-position data acquired by a Global Positioning System receiver. The combination of the three sets of data is used to construct infrared and hyperspectral maps of scanned areas shown.
The Coastal Research Imaging Spectrometer (CRIS) is an airborne remote-sensing system designed specifically for research on the physical, chemical, and biological characteristics of coastal waters. The CRIS includes a visible-light hyperspectral imaging subsystem for measuring the color of water, which contains information on the biota, sediment, and nutrient contents of the water. The CRIS also includes an infrared imaging subsystem, which provides information on the temperature of the water. The combination of measurements enables investigation of biological effects of both natural and artificial flows of water from land into the ocean, including diffuse and point-source flows that may contain biological and/or chemical pollutants. Temperature is an important element of such measurements because temperature contrasts can often be used to distinguish among flows from different sources: for example, a sewage outflow could manifest itself in spectral images as a local high-temperature anomaly.
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The Planetary Data System Imaging Node maintains and distributes the archives of planetary image data acquired from NASA's flight projects with the primary goal of enabling the science community to perform image processing and analysis on the data. The Node provides direct and easy access to the digital image archives through wide distribution of the data on CD-ROM media and on-line remote-access tools by way of Internet services.
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