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NASA NTRS1994

Estimation of Vegetation Aerodynamic Roughness of Natural Regions Using Frontal Area Density Determined from Satellite Imagery

Parameterizations of the frontal area index and canopy area index of natural or randomly distributed plants are developed, and applied to the estimation of local aerodynamic roughness using satellite imagery. The formulas are expressed in terms of the subpixel fractional vegetation cover and one non-dimensional geometric parameter that characterizes the plant's shape. Geometrically similar plants and Poisson distributed plant centers are assumed. An appropriate averaging technique to extend satellite pixel-scale estimates to larger scales is provided. ne parameterization is applied to the estimation of aerodynamic roughness using satellite imagery for a 2.3 sq km coniferous portion of the Landes Forest near Lubbon, France, during the 1986 HAPEX-Mobilhy Experiment. The canopy area index is estimated first for each pixel in the scene based on previous estimates of fractional cover obtained using Landsat Thematic Mapper imagery. Next, the results are incorporated into Raupach's (1992, 1994) analytical formulas for momentum roughness and zero-plane displacement height. The estimates compare reasonably well to reference values determined from measurements taken during the experiment and to published literature values. The approach offers the potential for estimating regionally variable, vegetation aerodynamic roughness lengths over natural regions using satellite imagery when there exists only limited knowledge of the vegetated surface.

Jasinski, Michael F.↗

NASA NTRS1998

Parameterization of Vegetation Aerodynamic Roughness of Natural Regions Satellite Imagery

Parameterizations of the frontal area index and canopy area index of natural or randomly distributed plants are developed, and applied to the estimation of local aerodynamic roughness using satellite imagery. The formulas are expressed in terms of the subpixel fractional vegetation cover and one non-dimensional geometric parameter that characterizes the plant's shape. Geometrically similar plants and Poisson distributed plant centers are assumed. An appropriate averaging technique to extend satellite pixel-scale estimates to larger scales is provided. The parameterization is applied to the estimation of aerodynamic roughness using satellite imagery for a 2.3 sq km coniferous portion of the Landes Forest near Lubbon, France, during the 1986 HAPEX-Mobilhy Experiment. The canopy area index is estimated first for each pixel in the scene based on previous estimates of fractional cover obtained using Landsat Thematic Mapper imagery. Next, the results are incorporated into Raupach's (1992, 1994) analytical formulas for momentum roughness and zero-plane displacement height. The estimates compare reasonably well to reference values determined from measurements taken during the experiment and to published literature values. The approach offers the potential for estimating regionally variable, vegetation aerodynamic roughness lengths over natural regions using satellite imagery when there exists only limited knowledge of the vegetated surface.

Jasinski, Michael F.↗

NASA NTRS2001

Cloud Spatial Structure and 3D Radiative Transfer

Cloud radiative properties are sensitive to drop size and other parameters of cloud micro-structure, but also to cloud shape, spacing, and other parameters of cloud macro-structure, including internal fractal structure. New information on cloud structure is being derived from a variety of cloud radars and lidars. Ongoing field programs such as DoE/ARM are improving the measurement and modelling of physical and radiative properties of clouds. A parallel effort is underway to improve cloud remote sensing, especially from the new suite of EOS (Earth Observing System) instruments which are beginning to provide higher spectral, spatial resolution, and/or angular resolution. Key parameters for improving pixel-scale retrievals are cloud thickness and photon mean-free-path, which together determine the scale of "radiative smoothing" of cloud fluxes and radiances. This scale has been observed as a change in the spatial spectrum of Landsat cloud radiances, and was also recently found with the Goddard micropulse lidar, by searching for returns from directions nonparallel to the incident beam. "Offbeam" Lidar returns are now being used to estimate the cloud "radiative Green's function", (G). G depends on cloud thickness and may be used to retrieve that important quantity. G is also being applied to improving simple estimates of cloud radiative properties that are based on the "Independent Pixel Approximation" or IPA. This and other measurements of 3D transfer in clouds, coupled with Monte Carlo and other 3D transfer methods, are beginning to provide a better understanding of the dependence of radiation on cloud inhomogeneity, and to suggest new retrieval and parameterization algorithms which take account of cloud inhomogeneity. An international "Intercomparison of 3D Radiation Codes" or I3RC, program is underway to coordinate and evaluate the variety of 3D radiative transfer methods now available, and to make them more widely available. Information is on the Web at: http://climate.gsfc.nasa.gov/I3RC. Input consists of selected cloud fields derived from data sources such as radar, microwave and satellite, and from models involved in the GEWEX Cloud Systems Studies. Output is selected radiative quantities that characterize the large-scale properties of the fields of radiative fluxes and heating. Several example cloud fields will be used to illustrate the effects of cloud inhomogeneity and 3D radiation.

Cahalan, Robert F.↗

NASA NTRS2001

Cloud Spatial Structure and 3D Radiative Transfer

Cloud radiative properties are sensitive to drop size and other parameters of cloud micro-structure, but also to cloud shape, spacing, and other parameters of cloud macro-structure, including internal fractal structure. New information on cloud structure is being derived from a variety of cloud radars and lidars. Ongoing field programs such as DoE/ARM (atmospheric radiation measurement) are improving the measurement and modelling of physical and radiative properties of clouds. A parallel effort is underway to improve cloud remote sensing, especially from the new suite of EOS (Earth observing system) instruments which are beginning to provide higher spectral, spatial resolution, and/or angular resolution. Key parameters for improving pixel-scale retrievals are cloud thickness and photon mean-free-path, which together determine the scale of 'radiative smoothing' of cloud fluxes and radiances. This scale has been observed as a change in the spatial spectrum of Landsat cloud radiances, and was also recently found with the Goddard micropulse lidar, by searching for returns from directions nonparallel to the incident beam. 'Offbeam' Lidar returns are now being used to estimate the cloud 'radiative Green's function' (G). G depends on cloud thickness and may be used to retrieve that important quantity. G is also being applied to improving simple estimates of cloud radiative properties that are based on the 'Independent Pixel Approximation' or IPA. This and other measurements of 3D (three dimensional) transfer in clouds, coupled with Monte Carlo and other 3D transfer methods, are beginning to provide a better understanding of the dependence of radiation on cloud inhomogeneity, and to suggest new retrieval and parameterization algorithms which take account of cloud inhomogeneity. An international 'Intercomparison of 3D Radiation Codes' (I3RC) program is underway to coordinate and evaluate the variety of 3D radiative transfer methods now available, and to make them more widely available. Information is on the Web at: http://climate.gsfc.nasa.gov/I3RC. Input consists of selected cloud fields derived from data sources such as radar, microwave and satellite, and from models involved in the GEWEX Cloud Systems Studies. Output is selected radiative quantities that characterize the large-scale properties of the fields of radiative fluxes and heating. Several example cloud fields will be used to illustrate the effects of cloud inhomogeneity and 3D radiation.

Cahalan, Robert F.↗

NASA NTRS1993

Mapping of the Ronda peridotite massif (Spain) from AVIRIS spectro-imaging survey: A first attempt

In both AVIRIS and ISM data, through the use of mixing models, geological boundaries of the Ronda massif are identified with respect to the surrounding rocks. We can also yield first-order vegetation maps. ISM and AVIRIS instruments give consistent results. On the basis of endmember fraction images, it is then possible to discard areas highly vegetated or not belonging to the peridotite massif. Within the remaining part of the mosaic, spectro-mixing analysis reveals spectral variations in the peridotite massif between the well-exposed areas. Spatially organized units are depicted, related to differences in the relative depth of the absorption band at 1 micron, and it may be due to a different pyroxene content. At this stage, it is worth noting that, although mineralogical variations observed in the rocks are at a sub-pixel scale for the airborne analysis, we see an emerging spatial pattern in the distribution of spectral variations across the massif which might be prevailingly related to mineralogy. Although it is known from fieldwork that the Ronda peridotite massif exhibits mineralogical variations at local scale in the content of pyroxene, and at regional scale in different mineral facies, ranging from garnet-, to spinel- to plagioclase-lherzolites, no attempt has been done yet to produce a synoptic map relating the two scales of analysis. The present work is a first attempt to reach this objective, though a lot more work is still required. In particular, for the purpose of mineralogical interpretation, it is critical to relate the airborne observation to field work and laboratory spectra of Ronda rocks already obtained, with the use of image endmembers and associated reference endmembers. Also, the pretty rough linear mixing model used here is taken as a 'black-box' process which does not necessarily apply correctly to the physical situation at the sub-pixel level. One may think of using the ground-truth observations bearing on the sub-pixel statistical characteristics (texture, structural pattern, surface distribution and vegetation contribution (grass,..)) to produce a more advanced mixing model, physically appropriate to the geologic and environmental contexts.

Pinet, P. C.↗

NASA NTRS2021

Land Surface Modeling Over the Dry Chaco: The Impact of Model Structures, and Soil, Vegetation and Land Cover Parameters

In this study, we tested the impact of a revised set of soil, vegetation and land cover parameters on the performance of three different state-of-the-art land surface models (LSMs) within the NASA Land Information System (LIS). The impact of this revision was tested over the South American Dry Chaco, an ecoregion characterized by deforestation and forest degradation since the 1980s. Most large-scale LSMs may lack the ability to correctly represent the ongoing deforestation processes in this region, because most LSMs use climatological vegetation indices and static land cover information. The default LIS parameters were revised with improved soil parameters, satellite-based interannually varying vegetation indices (leaf area index and green vegetation fraction) instead of climatological vegetation indices, and yearly land cover information instead of static land cover. A relative comparison in terms of water budget components and “efficiency space” for various baseline and revised experiments showed that large regional and long-term differences in the simulated water budget partitioning relate to different LSM structures, whereas smaller local differences resulted from updated soil, vegetation and land cover parameters. Furthermore, the different LSM structures redistributed water differently in response to these parameter updates. A time-series comparison of the simulations to independent satellite-based estimates of evapotranspiration and brightness temperature (Tb) showed that no LSM setup significantly outperformed another for the entire region and that not all LSM simulations improved with updated parameter values. However, the revised soil parameters generally reduced the bias between simulated surface soil moisture and pixel-scale in situ observations and the bias between simulated Tb and regional Soil Moisture Ocean Salinity (SMOS) observations. Our results suggest that the different hydrological responses of various LSMs to vegetation changes may need further attention to gain benefits from vegetation data assimilation.

Michiel Maertens↗

NASA NTRS2012

Use of In Situ and Airborne Multiangle Data to Assess MODIS- and Landsat-based Estimates of Surface Albedo

The quantification of uncertainty of global surface albedo data and products is a critical part of producing complete, physically consistent, and decadal land property data records for studying ecosystem change. A current challenge in validating satellite retrievals of surface albedo is the ability to overcome the spatial scaling errors that can contribute on the order of 20% disagreement between satellite and field-measured values. Here, we present the results from an uncertain ty analysis of MODerate Resolution Imaging Spectroradiometer (MODIS) and Landsat albedo retrievals, based on collocated comparisons with tower and airborne multi-angular measurements collected at the Atmospheric Radiation Measurement Program s (ARM) Cloud and Radiation Testbed (CART) site during the 2007 Cloud and Land Surface Interaction Campaign (CLAS33 IC 07). Using standard error propagation techniques, airborne measurements obtained by NASA s Cloud Absorption Radiometer (CAR) were used to quantify the uncertainties associated with MODIS and Landsat albedos across a broad range of mixed vegetation and structural types. Initial focus was on evaluating inter-sensor consistency through assessments of temporal stability, as well as examining the overall performance of satellite-derived albedos obtained at all diurnal solar zenith angles. In general, the accuracy of the MODIS and Landsat albedos remained under a 10% margin of error in the SW(0.3 - 5.0 m) domain. However, results reveal a high degree of variability in the RMSE (root mean square error) and bias of albedos in both the visible (0.3 - 0.7 m) and near-infrared (0.3 - 5.0 m) broadband channels; where, in some cases, retrieval uncertainties were found to be in excess of 20%. For the period of CLASIC 07, the primary factors that contributed to uncertainties in the satellite-derived albedo values include: (1) the assumption of temporal stability in the retrieval of 500 m MODIS BRDF values over extended periods of cloud-contaminated observations; and (2) the assumption of spatial 45 and structural uniformity at the Landsat (30 m) pixel scale.

Roman, Miguel O.↗

DOE OSTI2026

Extremized nonlinear and linearized responses in soft metamaterials enabled by gradient-based design and grayscale digital light processing

In this study, we develop a gradient-based design approach that exploits grayscale digital light processing (DLP) 3D printing for extremizing the nonlinear and linearized response of soft metamaterials — materials that harness engineered geometric instabilities to undergo large and programmable changes in configuration. Grayscale DLP approaches modulate local mechanical properties at the pixel scale by tuning the light intensity within a single grayscale image, unlocking an exceptionally large design space. To effectively navigate this space, we develop smooth mappings between local light intensity values and global quantities of interest that characterize the behavior of soft metamaterials. Enabling these smooth mappings are robust and differentiable nonlinear finite element simulations powered by a trust region solver. A PDE-constrained optimization problem is then solved to invert these mappings and produce light intensity distributions that endow the printed part with varying stiffness and flexibility in distinctive regions. It is shown that optimizing the distribution of soft and stiff phases throughout a metamaterial structure results in markedly different buckling and self-contact configurations to drive extremized nonlinear compression and linearized vibration responses. Optimized light intensity distributions are translated to grayscale images and directly used to print soft metamaterial samples, showing remarkable agreement between the buckling and self-contact response in simulated and measured deformed configurations.

Additive manufacturing↗

NASA NTRS1983

Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

The use of two dimensional Fast Fourier Transforms (FFTs) subjected to pattern recognition technology for the identification and classification of low altitude stratus cloud structure from Geostationary Operational Environmental Satellite (GOES) imagery was examined. The development of a scene independent pattern recognition methodology, unconstrained by conventional cloud morphological classifications was emphasized. A technique for extracting cloud shape, direction, and size attributes from GOES visual imagery was developed. These attributes were combined with two statistical attributes (cloud mean brightness, cloud standard deviation), and interrogated using unsupervised clustering amd maximum likelihood classification techniques. Results indicate that: (1) the key cloud discrimination attributes are mean brightness, direction, shape, and minimum size; (2) cloud structure can be differentiated at given pixel scales; (3) cloud type may be identifiable at coarser scales; (4) there are positive indications of scene independence which would permit development of a cloud signature bank; (5) edge enhancement of GOES imagery does not appreciably improve cloud classification over the use of raw data; and (6) the GOES imagery must be apodized before generation of FFTs.

Logan, T. L.↗

NASA NTRS1992

Registering and resampling images in STSDAS

Registering different images can be difficult, especially if the images to be registered are images at different wavelengths, where features in one image may look entirely different or be absent from the second image. Using two new packages soon to be added to the STSDAS package, REGISTER and RESAMPLE, this job is done automatically. The REGISTER package allows the user to determine the amount of translation, rotation, and/or magnification needed to make two images, spectra, or time series congruent. The methods implemented to compute the registration parameters use: a set of the pixel coordinates of the same features identified in two files, or the FITS coordinate transformation parameters in the headers of two data files, or a single feature identified as the peak of a cross-correlation between two vectors. The coefficients describing the registration are defined by the equations (for a two-dimensional image): x = a + bx + cy, y = d + ex + fy, where (X,Y) are the pixel coordinates of a feature in the reference image, (x,y) are the pixel coordinates of a feature in the secondary image, and the computed coefficients are a, b, c, d, e, and f. Results may be produced by linking the output of REGISTER to RESAMPLE in a command language procedure. The output from REGISTER and the input to RESAMPLE consists of a matrix of coefficients (a through f above) fully specifying the registration. The RESAMPLE package resamples simple vector or image data for a given amount of translation, rotation (images only), and magnification, or reflection of the science data. Specific options included are: image rotation about the FITS reference pixel; scale changes, i.e. magnification or demagnification (for images, independently on both axes); simple translation; reflection (for images, about one or both axes); and resampling and registration to a reference data set. Output from the RESAMPLE task is the resampled image which may then be displayed and compared with the reference image.

Williamson, R. L., II↗

NASA NTRS1996

The First Diffraction-Limited Images from the W. M. Keck Telescope

The first diffraction limited, 0.05s resolution, images on the W. M. Keck Telescope have been obtained at a wavelength of 2.2 micrometers. These images were part of an experiment to test the suitability of the Keck Telescope for speckle imaging. In order to conduct this test, it was necessary to modify the pixel scale of the Keck facility Near Infrared Camera (NIRC) to optimally sample the spatial frequencies made available by the Keck telescope. The design and implementation of the external reimaging optics, which convert the standard fl25 beam from the secondary mirror to fl182, are described here. Techniques for reducing speckle data with field rotation on an alt-az telescope are also described. Three binary stars were observed in this experiment with separations as small as 0.05s. With only 100 frames of data on each, a dynamic range of at least 3.5 mag was achieved in all cases. These observations imply that a companion as faint as 14.5 mag at 2.2 micrometers could be detected around an 11th magnitude point source.

Matthews, K.↗

NASA NTRS1998

A Search for a Near-Infrared Halo Around NGC 4565

We present a near-infrared (3.5-5 micron) search for the integrated emission from low-mass stars and/or brown dwarfs in the halo of the nearby edge-on spiral galaxy NGC 4565. The observation was made with a liquid-helium-cooled rocket-borne telescope using a 256 x 256 InSb array with a pixel scale of 17". Images of NGC 4565 were successfully obtained with sensitivity near the natural background limit. Our search reveals no evidence of a faint halo around the galaxy, in contrast with the previous reports of a halo around NGC 5907. The lower limit of the mass-to-light ratio for the halo of NGC 4565 is 260 (2 delta) in solar units at 3.5-5 microns. This implies that hydrogen-burning stars do not contribute significantly to the mass of the dark halo in NGC 4565.

Uemizu, Kazunori↗

NASA NTRS1998

Characterization of Clouds and the Anisotropy of Emitted and Reflected Radiances for the Purpose of Obtaining the Radiative Heating of the Atmosphere

The goal of the work supported through this grant was to assess the validity of the assumptions underlying the CERES Strategy for determining radiative fluxes. Specifically, the work focused on the determination of scene type and the use of anisotropic factors to derive radiative fluxes from observed broadband radiances. The work revealed a dependence of the anisotropy of reflected and emitted broadband radiances on the spatial resolution of the observations that had been overlooked in the formulation of the CERES strategy. This dependence on spatial resolution coupled with errors in scene identification led to view zenith angle dependent biases in the ERBE derived radiative fluxes. Scene identification will be greatly improved in CERES thereby alleviating somewhat the biases arising from the dependence of the anisotropy of the radiances on spatial resolution. Attention was then focused on the validity of plane-parallel radiative transfer theory which is relied on to characterize the scene types viewed by the CERES scanner. Again, viewing geometry dependent biases were found even for single-layered, overcast cloud systems. Such systems are taken to be the closest examples of plane-parallel clouds. At least some of the departures from plane-parallel behavior were evidently due to relatively small bumps on the tops of extensive stratus layers. The bumps cannot be resolved in the imagery that will be used to characterize the scenes viewed by the CERES scanner. As part of this investigation, the ice sheets of Greenland and Antarctica were shown to provide radiometrically stable targets for determining the visible and near infrared calibrations of radiometers. These targets were used to calibrate the reflected sunlight at visible wavelengths used in this study. Finally, the limitations of plane-parallel theory notwithstanding, the common practice of ignoring fractional cloud cover within the fields of view of imaging radiometers was shown to lead to biases in the retrieved cloud properties. The development of retrievals for pixel-scale cloud cover fraction is an attempt to reduce such bases. Work on these retrievals continues.

Coakley, James A., Jr.↗

NASA NTRS1999

Cloud Spatial Structure and 3D Radiative Transfer

Cahalan, Robert F.↗

NASA NTRS1999

Cloud Spatial Structure and 3D Radiative Transfer

Cloud radiative properties are sensitive to drop size and other parameters of cloud micro-structure, but also to cloud shape,spacing, and other parameters of cloud macro-structure, including internal fractal structure. New information on cloud structure is being derived from a variety of cloud radars. Ongoing field programs such as Department of Energy's Atmospheric Radiation Measurement (DoE/ARM) are improving the measurement and modelling of physical and radiative properties of clouds. A parallel effort is underway to improve cloud remote sensing, especially from the new suite of EOS-AM1 instruments which will provide higher spectral, spatial resolution, and/or angular resolution. Key parameters for improving pixel-scale retrievals are cloud thickness and photon mean-free-path, which together determine the scale of "radiative smoothing" of cloud fluxes and radiances. This scale has been observed as a change in the spatial spectrum of Landsat cloud radiances, and was also recently found with the Goddard micropulse lidar, by searching for returns from directions nonparallel to the incident beam. "Offbeam" Lidar returns are now being used to estimate the cloud "radiative Green's function", G,which depends on cloud thickness and may be used to retrieve that important quantity. G is also being applied to improving simple IPA estimates of cloud radiative properties. This and other measurements of 3D transfer in clouds, coupled with Monte Carlo and other 3D transfer methods, are beginning to provide a better understanding of the dependence of adiation on cloud inhomogeneity, and to suggest new retrieval and parameterization algorithms which take account of cloud inhomogeneity. An international "Intercomparison of 3D Radiation Codes" or I3RC, program is beginning to coordinate and evaluate the variety of 3D radiative transfer methods now available, and to make them more widely available. Information is on the Web at: http://climate.qsfc.nasa.crov/I3RC. Input consists of selected cloud fields derived from data sources such as radar, microwave and satellite, and from models involved in the GEWEX Cloud Systems Studies. Output is selected radiative quantities that characterize the large- scale properties of the fields of radiative fluxes and heating. Several example cloud fields will be used to illustrate.

Cahalan, Robert F.↗

NASA NTRS2000

An Ultraviolet/Optical Atlas of Bright Galaxies

We present wide-field, imagery and photometry of 43 selected nearby galaxies of all morphology types at ultraviolet and optical wavelengths. The ultraviolet images, in two broad bands at 1500 Angstroms and 2500 Angstroms, were obtained by the Ultraviolet Imaging Telescope (UIT) during the Astro-1 Spacelab mission. The UV images have approx. 3" resolution, and the comparison sets of ground-based, CCD images (in one or more of B, V, R, and H alpha ) have pixel scales and fields of view closely matching the UV frames. The atlas consists of multiband images together with plots of UV/optical radial surface brightnesses, colors and other associated photometric parameters such as half-light radii. In an appendix, we discuss the sensitivity of different wavebands to a galaxy's star formation history in the form of "history weighting functions" and the importance of UV observations as probes of evolution during the past 10-1000 Myr. We find that UV galaxy morphologies are usually significantly different from visible band morphologies as a consequence of spatially inhomogeneous stellar populations. Differences are quite pronounced for systems in the middle range of Hubble types, Sa through Sc, but less so for ellipticals or late-type disks. Normal ellipticals and large spiral bulges are fainter and more compact in the UV. They typically exhibit smooth and unresolved far-UV profiles with, however, far-UV/optical color gradients which are larger than any at optical/IR wavelengths. The far-UV light in these cases is probably produced by extreme horizontal branch stars and their descendants in the dominant, low-mass, metal-rich population.

Stecher, Theodore↗

NASA NTRS2005

The First Six Months of Iapetus Observations by the Cassini ISS Camera

Since Saturn arrival in June 2004, Iapetus has been studied intensively by the Cassini ISS camera [1] at various ranges. The first of two relatively close flybys in the primary mission occurred on Dec 31, 2004 at an altitude of approx.123,400 km over the northern leading hemisphere, resulting in images with a minimum pixel scale of 740 m. Detailed results of this flyby are given in [2], while this abstract covers the observations obtained earlier. Among the most important discoveries are: (a) Four giant impact basins with diameters between 390 and 550 km were detected, three of them are located in the dark terrain [3]. (b) Data revealed a >1300 km long ridge that marks exactly Iapetus' equator within the dark terrain. Individual mountains within the western part of the ridge reach heights of approx.20 km over surrounding terrain [3]. (c) Impact craters were confirmed to be the main geological feature within the dark terrain and at high southern latitudes. (d) There are numerous craters with dark walls roughly facing towards the central parts of the dark hemisphere [3]. (e) Almost all parts of Iapetus have been imaged at least at low resolution (< 60 km/pxl).

Denk, T.↗

NASA NTRS2005

First Imaging Results from the Iapetus B/C Flyby of the Cassini Spacecraft

The first of two relatively close Iapetus flybys in Cassini's primary mission occured on Dec 31, 2004 18:49 UTC near apoapsis from orbit "B" to "C" at an altitude of approximately 123,400 km over the northern leading hemisphere, resulting in a minimum pixel scale of 740 m for the ISS narrow angle camera (NAC). Data revealed details of a greater than 1300-km-long ridge that had been discovered just one week earlier in optical navigation images. Individual mountains within the western part of the ridge reach heights of approximately 20 km over surrounding terrain. The data set provides constraints on the origin of the albedo dichotomy. It appears very likely that the dark material is overlying an ice crust, but no evidence for emplacement of dark material via surface flows is apparent. Instead, signs for dark-material emplacement through processes that included ballistic transportation are visible. No bright-floor ("punch-through") craters have been found on the dark hemisphere. The ridge discovery may revive the idea of an endogenic origin of the dark side.

Denk, T.↗