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Celestial Mapping System is a virtual library of 3D globes with functionality to support upcoming missions. Built on top of NASA WorldWind Java Library with capabilities to display high-resolution imagery and terrain with a rich toolkit of functionality for visualization and analysis of celestial features. This is a two video set of the demonstration for this mapping system.
Introduction: As NASA expands the mission portfolio on the lunar surface, there is a need for applications with a broad range of analytical and functional capabilities that can be simultaneously deployed onto multiple mobile and desktop platforms to perform in-situ operations and hence enabling extensive Lunar exploration. Celestial Mapping System (CMS) [1,2] is developed to address the need for tools for science investigations, mission planning, operations and support for planetary sciences. Built on top of NASA WorldWind libraries, CMS can be simultaneously deployed onto multiple platforms, has the flexibility to update to the latest imagery and terrain datasets as they are being acquired (in real time) before and/or during the exploration mission and has the potential to enable traverse path planning suited for rovers, EVA and surface mobility units. It can provide critical functionalities such as equipment planning and optimized placement on Lunar surface, line of sight analysis to inform the coverage area for various equipment, powerful measurement tools based on 3D terrain, 3D COLLADA models to represent rovers, humans and equipment, visualization of derived mapping products (e.g. resource maps), and a data engine for hosting new observations that are not available in other contemporary lunar data tools [1]. Visualization of PSRs: The current presentation focuses on the work performed by the authors, to consume a unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool [3]. This tool was developed in direct support of NASA's VIPER and Artemis programs to enhance the extremely low-light images of the interior of PSRs and provide the first-time ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the region near Nobili crater near Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Line of Sight Analysis and Traverse Planning in PSRs: We have developed an in-built line of sight analysis (LOS) tool in CMS that analyzes the terrain profile and obstructions and provides the visibility of a given terrain for a remote observer. This tool was utilized to perform viewshed analysis to investigate the area inside the PSR, a remote observer such as a rover could see without actually crossing the region. Figure 1 shows the viewshed analysis on the PSR in Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. Figure 1: (left) PSR image on top of a high-resolution mosaic of sunlit images of a crater, in Nobile region (right) Viewshed Analysis of the same PSR with observer location shown by yellow pin. This analysis was extended further to set different heights for various observers and then perform the viewshed analysis. Combining the different visibility profiles can help designing improved traverses within the crater. Future plans: Eventually, HORUS datasets will be integrated into CMS as a layer in selected lunar polar regions. Hazard Maps will then be created based on terrain analysis in those regions. This integration will enable multiple scientific and exploration applications, such as designing traverses within PSRs, analyzing potential landing and science mission targets, investigating the meter-scale geomorphology of PSRs, including craters, boulder, surface roughness, mass wasting features and other indications of the presence of water-ice and other volatiles. Acknowledgments: CMS developers team including Kaitlyn J. Dickinson, Tyler A. Lucarz, Tyler W. Choi from USRA, NASA WorldWind Advisory team including Mark Peterson and Guillermo Miguel Del Castillo, HORUS team member V.T. Bickel, Robinson, M., LRO MOON LROC 2 EDR V1.0, LRO-L-LROC-2-EDR-V1.0, NASA Planetary Data System (PDS), 2009. https://doi.org/10.17189/1520643 References: [1] https://celestial.arc.nasa.gov [2] Agrawal et. al. “Celestial Mapping System for Lunar Surface Mapping and Analytics”, Lunar Surface Innovation Consortium, 2021 [3] Bickel V. et al. (2021) Nat Commun 12, 5607
Film positives of ERTS-1 imagery, both as received from NASA and photographically reprocessed, are analyzed by conventional and color additive viewing methods. The imagery reveals bedrock and surficial geological information at various scales. Features which can be identified to varying degrees include boundaries between major tectonic provinces, lithological contacts, foliation trends within massive gneisses, faults, and topographic lineaments. In the present imagery the greatest amount of spectral geology is displayed in the Adirondack region where bedrock geology is strongly linked to topography. Within this basement complex, the most prominantly displayed features are numerous north-northeast trending faults and topographic lineaments, and arcuate east-west valleys developed in some of the weaker metasedimentary rocks. The majority of the faults and lineaments shown on the geologic Map of New York at 1:250,000 appear in the ERTS imagery.
The author has identified the following significant results. Geologic interpretation of ERTS-1 imagery is dependent on recognition of the distribution, continuity, trend, and geometry of key surface features. In the examination of ERTS-1 imagery, lithology must be interpreted largely from the geomorphic expression of the terrain. ERTS-1 imagery is extremely useful in detecting local structures. Most mapped structures are topographically-expressed. Consequently, ERTS-1 imagery acquired during mid-winter, when the solar illumination angle is low, provides the largest amount of structural information. Stereoscopic analyses of ERTS-1 images significantly aid geologic interpretation. Positive transparencies of ERTS-1 images (1:1,000,000) commonly contain more geologic information than can be adequately annotated during geologic interpretation.
Methods have recently been developed for the utilization of remotely sensed image data in the measurement of terrain displacements resulting from geologic processes. In optical imagery, measurements precise to a fraction of a pixel are achieved by statistical image matching.
Generating accurate three dimensional planetary models and albedo maps is becoming increasingly more important as NASA plans more robotics missions to the Moon in the coming years. This paper describes a novel approach for separation of topography and albedo maps from orbital Lunar images. Our method uses an optimal Bayesian correlator to refine the stereo disparity map and generate a set of accurate digital elevation models (DEM). The albedo maps are obtained using a multi-image formation model that relies on the derived DEMs and the Lunar- Lambert reflectance model. The method is demonstrated on a set of high resolution scanned images from the Apollo era missions.
The author has identified the following significant results. LANDSAT 1 and 2 imagery contrast the geology of the Cloncurry-Dobbyn and the Gregory River-Mt. Isa areas very clearly. Known major structural features and lithological units are clearly displayed while, hitherto unknown lineaments were revealed. Throughout this area, similar rock types produce similar spectral signatures, e.g. quartzites produce light signatures, iron rich rocks produce dark signatures. More geological data are discernible at the 1:50,000 scale than on the 1:250,000 scale. Ore horizons may be identified at the 1:50,000 scale, particularly where they are associated with iron rich rocks. On the level plains north of Cloncurry, distinctive spectral signatures produced by the combined reflectances of plant cover, soils, and geology, distinguish different types of superficial deposits. Existing and former channels of the Cloncurry and Williams Rivers are distinguished at the 1:50,000 scale on both the LANDSAT 1 and 2 imagery. On the Cloncurry Plains, fence lines are discernible on the 1:50,000 LANDSAT 2 imagery.
Trials were run on a six degree of freedom combat helicopter simulator to evaluate head-down displays with integrated FLIR imagery for terrain-following, course-steering, and transition to approach and hover helicopter pilot tasks. Three display formats were tested, providing varying levels of symbology for, e.g., the flight path angle, pitch-attitude data, vertical speed, altitude, etc. The pilots were also furnished flight director guidance, i.e., terrain-following, course steering, airspeed hold, and approach to hover. All the displays permitted the pilots to fly satisfactory mission in the CGI scenarios. The results revealed that the pilots preferred a nonconformal FLIR display superposition.
An architecture for object modeling and recognition for an autonomous land vehicle is presented. Examples of objects of interest include terrain features, fields, roads, horizon features, trees, etc. The architecture is organized around a set of data bases for generic object models and perceptual structures, temporary memory for the instantiation of object and relational hypotheses, and a long term memory for storing stable hypotheses that are affixed to the terrain representation. Multiple inference processes operate over these databases. Researchers describe these particular components: the perceptual structure database, the grouping processes that operate over this, schemas, and the long term terrain database. A processing example that matches predictions from the long term terrain model to imagery, extracts significant perceptual structures for consideration as potential landmarks, and extracts a relational structure to update the long term terrain database is given.
The author has identified the following significant results. Series of linears were identified on the March imagery of Lady Annie-Mt. Gordon fault zone area. The series with a WSW-ENE orientation which is normal to the major structural units and also several linears with NNW-SSE orientation appears to be particularly important. Copper mineralization is known at several localities where these linears are intersected by faults. Automated outputs using supervised methods involving the selection of training sets selected by visual recognition of spectral signatures on the color composites obtained from combinations of MSS bands 4, 5 and 7 projected through appropriate filters, were generated.
A prototype legged vehicle is being developed for an exploratory mission on another planet, conceivably Mars, where it is to traverse uncharted areas and collect material samples. The rover can construct from range imagery a geometric terrain representation; i.e., elevation map that includes uncertainty, unknown areas, and local features. An algorithm for constructing an elevation map from a single range image is presented: by virtue of working in spherical-polar space, the algorithm is independent of the desired map resolution and the orientation of the sensor, unlike algorithms that work in Cartesian space. Also presented is a two-stage matching technique (feature matching followed by iconic matching) that identifies the transformation T corresponding to the vehicle displacement between two viewing positions. To support legged locomotion over rough terrain, methods for evaluating regions of the constructed elevation maps as footholds are developed.
In this paper we propose two novel deep learning-based terrain classification methods robust to illumination changes.
The author has identified the following significant results. A comparative evaluation of an ERTS-1 MSS color reconstitution and an Apollo 6 and Gemini 4 color photograph for information content was conducted. A greater variety of image detail was indicated for the Apollo 6 imagery. A study of terrain feature variable-vegetation relationships has been concluded. However, there were no substantial differences among space photo types when macrorelief classes were interpreted. Vegetation distribution is influenced in varying degrees by characteristics of the terrain, some of which are quite apparent on ERTS-1 imagery and, therefore, provide the means for inferring possible vegetation types for a specified location. Spectral signatures have been determined for some natural vegetation systems from the ERTS-1 MSS data. Those signatures have been used to classify ERTS-1 data for a portion of the study area. Work continues on multistage sampling for natural vegetation, terrain feature identification of ERTS-1 photographs, plant phenology, and spectral signature studies.
Simulated stereo radar imagery is used to investigate parameters for a spaceborne imaging radar. Incidence angles ranging from small to intermediate to large are used with three digital terrain model areas which are representative of relatively flat, moderately rough, and mountaneous terrain. The simulated radar imagery was evaluated by interpreters for ease of stereo perception and information content, and rank ordered within each class of terrain. The interpreter's results are analyzed for trends between the height of a feature and either parallax or vertical exaggeration for a stereo pair. A model is developed which predicts the amount of parallax (or vertical exaggeration) an interpreter would desire for best stereo perception of a feature of a specific height. Results indicate the selection of angle of incidence and stereo intersection angle depend upon the relief of the terrain. Examples of the simulated stereo imagery are presented for a candidate spaceborne imaging radar having four selectable angles of incidence.
Simulated stereo radar imagery is used to investigate parameters for a spaceborne imaging radar. Incidence angles ranging from small to intermediate to large are used with three digital terrain model areas which are representative of relatively flat, moderately rough, and mountainous terrain. The simulated radar imagery was evaluated by interpreters for ease of stereo perception and information content, and rank order within each class of terrain. The interpreter's results are analyzed for trends between the height of a feature and either parallax or vertical exaggeration for a stereo pair. A model is developed which predicts the amount of parallax (or vertical exaggeration) an interpreter would desire for best stereo perception of a feature of a specific height. Results indicate the selection of angle of incidence and stereo intersection angle depend upon the relative relief of the terrain. Examples of the simulated stereo imagery are presented for a candidate spaceborne imaging radar having four selectable angles of incidence.
ERS-1 synthetic aperture radar (SAR) imagery was employed for the measurement of the dynamics of the Bagley icefield during a major surge in 1993-1994, the measurement of ice velocities on the Malaspina piedmont glacier during a quiescent phase between surges, and for mapping the snow lines and the position of the terminus of Nabesna glacier on Mount Wrangell (a 4317 m andesitic shield volcano) in the heavily glacierized Saint Elias and Wrangell Mountains of Alaska. An overview and summary of results is given. The methods used include interferometry, cross-correlation of sequential images, and digitization of boundaries using terrain-corrected SAR imagery.
Radar range measurements, basic waveforms of radar systems, and radar displays are initially described. These are followed by backscatter from several types of terrain and vegetation as a function of frequency and grazing angle. Analytical models for this backscatter include the facet models of radar return, with range-angle, velocity-range, velocity-angle, range, velocity, and angular only discriminations. Several side-looking airborne radar geometries are presented. Radar images of Arctic sea ice, fresh water lake ice, cloud-covered terrain, and related areas are presented to identify applications of radar imagery. Volume scatter models are applied to radar imagery from alpine snowfields. Short pulse ice thickness radar for subsurface probes is discussed in fresh-water ice and sea ice detection. Infrared scanners, including multispectral, are described. Diffusion of cold water into a river, Arctic sea ice, power plant discharges, volcanic heat, and related areas are presented in thermal imagery. Multispectral radar and infrared imagery are discussed, with comparisons of photographic, infrared, and radar imagery of the same terrain or subjects.