Ring-Moat Dome Structures (RMDSs) in the Lunar Maria:Statistical, Compositional, and Morphological Characterization and Assessment of Theories of Origin

Ring-moat dome structures (RMDSs) are positive morphologic features found clustered across many mare regions on the Moon, of which only a few isolated examples have been previously reported. Our continuing survey has expanded the known locations of the RMDSs from ~2,600 to over 8,000, indicating that RMDSs are more common geological features than previously thought. This work presents a detailed geomorphological analysis of 532 RMDSs identified in several mare basins. The combination of detailed elemental mapping, morphological and morphometric analyses, spatial distribution relationships with other geologic structures, and comparison with terrestrial analogs lead us to conclude that (1) RMDSs represent low circular mounds with diameters of a few hundred meters (average about 200 m) and a mean height of 3.5 m. The mounds are surrounded by moats ranging from tens to over 100 m in width and up to several meters in depth; (2) there is a wide variation of titanium abundances, although RMDSs are more commonly found in mare regions of moderate-to-high titanium content (>3 wt% TiO2); (3) RMDSs are found to occur on or around fractures, graben, and volcanic edifices (small shields and cones); (4) a spatial association between RMDSs and Irregular Mare Patches (see Braden et al., 2014, https://doi.org/10.1038/ngeo2252) is observed, suggesting that both may form from related lava flows; (5) comparisons between RMDSs and lava inflationary structures on Earth support an inflation-related extrusive nature and a genetic relationship with host lava flow processes; and (6) RMDS embayment relationships with craters of different degradation ages superposed on the host mare, and regolith development models, produces conflicting age relationships and divide theories of RMDS origin into two categories, (1) synchronous with the emplacement and cooling of the host lava flows ~3–4 Ga and (2) emplaced substantially after the host mare lava unit, in the period ~0–3 Ga. We outline the evidence supporting this age conundrum and implications for the different theories of origin and describe future research avenues to help resolve these outstanding questions. ©2020. American Geophysical Union. All Rights Reserved

Shape and albedo from shading (SAfS) for pixel-level DEM generation from monocular images constrained by low-resolution DEM

XXIII International Congress for Photogrammetry and Remote Sensing (ISPRS Congress), Commission IV, Prague, Czech Republic, 12-19 July 20162015-2016 > Academic research: refereed > Refereed conference paper201812_a bcmaVersion of RecordPublishe

SPECTRAL UNMIXING BASED CONSTRUCTION OF LUNAR MINERAL ABUNDANCE MAPS

In this study we apply a nonlinear spectral unmixing algorithm to a nearly global lunar spectral reflectance mosaic derived from hyper-spectral image data acquired by the Moon Mineralogy Mapper (M3) instrument. Corrections for topographic effects and for thermal emission were performed. A set of 19 laboratory-based reflectance spectra of lunar samples published by the Lunar Soil Characterization Consortium (LSCC) were used as a catalog of potential endmember spectra. For a given spectrum, the multi-population population-based incremental learning (MPBIL) algorithm was used to determine the subset of endmembers actually contained in it. However, as the MPBIL algorithm is computationally expensive, it cannot be applied to all pixels of the reflectance mosaic. Hence, the reflectance mosaic was clustered into a set of 64 prototype spectra, and the MPBIL algorithm was applied to each prototype spectrum. Each pixel of the mosaic was assigned to the most similar prototype, and the set of endmembers previously determined for that prototype was used for pixel-wise nonlinear spectral unmixing using the Hapke model, implemented as linear unmixing of the single-scattering albedo spectrum. This procedure yields maps of the fractional abundances of the 19 endmembers. Based on the known modal abundances of a variety of mineral species in the LSCC samples, a conversion from endmember abundances to mineral abundances was performed. We present maps of the fractional abundances of plagioclase, pyroxene and olivine and compare our results with previously published lunar mineral abundance maps

Construction of pixel-level resolution DEMs from monocular images by shape and albedo from shading constrained with low-resolution DEM

201810 bcrcAccepted ManuscriptRGCOthersNational Natural Science Foundation of China;China Academy of Space TechnologyPublishe

Interpreting spectral unmixing coefficients: From spectral weights to mass fractions

It is well known that many common planetary minerals exhibit prominent absorption features. Consequently, the analysis of spectral reflectance measurements has become a major tool of remote sensing. Quantifying the mineral abundances, however, is not a trivial task. The interaction between the incident light rays and particulate surfaces, e.g., the lunar regolith, leads to a non-linear relationship between the reflectance spectra of the pure minerals, the so-called “endmembers”, and the surface’s reflectance spectrum. It is, however, possible to transform the non-linear reflectance mixture into a linear mixture of single-scattering albedos of the Hapke model. The abundances obtained by inverting the linear single-scattering albedo mixture may be interpreted as volume fractions which are weighted by the endmember’s extinction coefficient. Commonly, identical extinction coefficients are assumed throughout all endmembers and the obtained volume fractions are converted to mass fractions using either measured or assumed densities. In theory, the proposed method may cover different grain sizes if each grain size range of a mineral is treated as a distinct endmember. Here, we present a method to transform the mixing coefficients to mass fractions for arbitrary combinations of extinction coefficients and densities. The required parameters are computed from reflectance measurements of well defined endmember mixtures. Consequently, additional measurements, e.g., the endmember density, are no longer required. We evaluate the method based on laboratory measurements and various results presented in the literature, respectively. It is shown that the procedure transforms the mixing coefficients to mass fractions yielding an accuracy comparable to carefully calibrated laboratory measurements without additional knowledge. For our laboratory measurements, the square root of the mean squared error is less than 4.82  wt%. In addition, the method corrects for systematic effects originating from mixtures of endmembers showing a highly varying albedo, e.g., plagioclase and pyroxene

Refinement of Stereo Image Analysis Using Photometric Shape Recovery as an Alternative to Bundle Adjustment

Topographic mapping, e.g. the generation of Digital Elevation Models (DEM), is of general interest to the remote sensing community and scientific research. Commonly, photogrammetric methods, e.g. stereo image analysis methods (SIAM) or bundle adjustment methods (BAM), are applied to derive 3D information based on multiple images of an area. These methods require the detection of control points, i.e. common points within multiple images, which relies on a similarity measure and usually yields a sparse map of 3D points. The full spatial DEM is then obtained by interpolation techniques or imposed restrictions, e.g. smoothness constraints. Since BAM utilizes all images of the area, it is assumed to provide a more accurate DEM than SIAM which utilizes only pairs of images. Intensity-based shape recovery, e.g. shape from shading (SfS), utilizes the reflectance behavior of the object surface and thus provides a dense map of relative height changes, which provide the possibility to refine the photogrammetric DEMs. Based on Rosetta NavCam images of 67P/Churyumov-Gerasimenko we compare intensity-based DEM refinement methods which use DEMs obtained based on SIAM and BAM as a reference. We show that both the SIAM based DEM refinement and the BAM based DEM refinement are of similar quality. It is thus possible to derive DEMs of high lateral resolution by applying the intensity-based refinement to the less complex SIAM