Producing LROC NAC Dtms in SOCET SET (And SOCET GXP)
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Producing LROC NAC DTMs in SOCET SET (and SOCET GXP) Madeleine Manheim1, Trent Hare2 -- [email protected] 1Arizona State University, 2USGS March 3, 2021 LSIC Workshop on Lunar Mapping for Precision Landing Introduction ● LRO launched June 2009 ○ 50 km circular polar orbit Sept. 2009 – Dec. 2011 ○ Currently in elliptical polar orbit (80 x 108 km) ● 2 Narrow Angle Cameras (NACs) ○ 2 panchromatic linear pushbroom cameras ○ 2.86° FOV / camera ○ 0.5 - 2.0 meters/pixel ● Lunar Orbiter Laser Altimeter (LOLA) ○ Most accurate global positioning data ○ Uncertainty <10 m horizontally, and <1 m vertically ● Digital Terrain Models are produced using: ○ Integrated Software for Imagers and Spectrometers (ISIS) ○ SOCET SET by BAE Systems Stereo pairs acquired from consecutive orbits Data Sources Narrow Angle Cameras (NACs) Lunar Orbiter Laser Altimeter • 2 panchromatic linear pushbroom (LOLA) cameras • time-of-flight altimeter • use targeted stereo observations, • single pulse illuminates a 5-spot pattern on taken on sequential orbits the surface • Provides dense and precise source of ~10 cm nominal precision of 28 Hz pulse topographic data • • precision orbit determination using LOLA profiles and the GRAIL gravity model provides global data with positional uncertainty <10 m horizontally, and <1 m vertically • provides most accurate global positioning data LROC NAC Camera Stereo Pair Acquisition Illumination conditions: ● Incidence angle: ~50° (40°-65°), avoiding deep shadows when possible ● Emission angle: <~45° (can be greater for smoother slopes) ● Stereo pairs acquired on successive orbits to ensure similar illumination Acquisition Geometry: ● Parallax/convergence angle between images ~20°-30° ● May be possible for 5°-45° (reduced precision) Primary Challenges For DTMs • NACs are pushbroom cameras – orientation and position of the spacecraft changes throughout image • Lunar day is ~28 Earth days – can be months before target is appropriately illuminated • Only 5 known ground control points – must rely on other data to ensure accurate DTMs • Limited overlap between images Slope map of NAC_DTM_HPONDS Image Pre-Processing for SOCET SET • Radiometric calibration (based on NAC global photometric solution, Boyd 2014) • Convert SPICE to keywords readable by SOCET SET – SOCET SET 5.5.0 uses generic pushbroom sensor model – USGS pushbroom sensor model (some additional handling relative to generic) used in SOCET SET 5.6.0 -- can deal with images that go over the poles, but has some bugs related to terrain extraction • Convert ISIS cubes to 8-bit Raw for DTM creation and 16-bit GeoTiffs to orthorectify using created DTM (always keep track of stretch parameters from originals) • The complete workflow uses various local scripts and tools for ingesting and exporting created DTMs and Orthos • Warning: Must always be cautious for SOCET SET and SOCET GXP around assumptions of WGS84 Background: Highland Ponds oblique (M1270899163) Relative Alignment ● Tie points added to images (partially automated) ● Multisensor triangulation algorithm: ○ Run using adjustable parameters as inputs: In-track, crosstrack, and radial positional bias; velocity bias; optional roll, twist, and yaw ● Want RMS <0.5 Note: LRO has switched to star-tracker only mode (no inertial measurement unit) - team is still evaluating effect Seed Points: Manually placed points APM Points: Automatically inserted points 7 Registration to LOLA Profiles • LOLA profiles provide the most accurate geodetic reference (<10 m horizontally, <1 m vertically) • Preliminary DTM is co-registered to LOLA profiles using MATLAB optimization toolboX – Control points are selected from profiles and used in triangulation – Process is repeated until offsets from profiles are acceptable • This process allows for maximum customization and accuracy, albeit at the expense of automation • Note: USGS uses pc_align (in ASP) for this process DTM Extraction • Final DTM is extracted with NGATE tool in SOCET SET – From epipolar-rectified 16-bit images – at 2, 3, 4, or 5 m/pixel (3x native resolution) • Users visually inspect DTM and correct any blunders * Numerous dark shadows cut out in – SOCET SET offers interactive editing tools JACKSONPK01 – Stereo setup allows contour lines to be viewed on topography as qualitative check – This can be time consuming • Finally, generate orthophotos * This is really what makes SOCET SET/GXP unique and valuable for landing site analysis DTM edge artifacts Stereo lab at LROC SOC Orthophoto Extraction Once the DTM has been generated, orthorectify the parent NAC stereo images, or correct them for distortion from camera angle and topography ● Corrects for shifts in pixel location based on DTM elevation values (each pixel is projected as though acquired from directly overhead) ● Ensures uniform scale throughout resulting orthophotos ● Generate orthophotos at DTM pixel scale or native image resolution ● Orthorectify images individually and mosaic them later 10 NAC DTM Mosaics • Consist of more than one set of stereo images • Illumination conditions and limited spacecraft slews create unique challenges • Largest mosaic to date is Highland Ponds – 27 sets of stereo images – 108 images NAC_DTM_HPONDS, centered at 167.36°N, 41.75°E NAC DTM Mosaics • Consist of more than one set of stereo images • Illumination conditions and limited spacecraft slews create unique challenges • Largest mosaic to date is Highland Ponds – 27 sets of stereo images – 108 images NAC_DTM_HPONDS, centered at 167.36°N, 41.75°E Understanding DTM Accuracy Evaluating Vertical Precision ● DTMs should have precisions < their pixel scales (2-5 m) ○ Relative Linear Error reported at 90% is calculated as a measure of vertical precision ○ Horizontal Error is < the resolution of the DTM ● Bundle Adjustment Pixel RMS Error (<0.5 px) ○ Value from SOCET SET that represents how well it was able to align all the images. ● Convergence angle has a large influence on our precision > Evaluating Absolute Accuracy ● RMS offset from LOLA should be < DTM pixel scale ● Offsets from LOLA should be within accuracy of LOLA tracks (10 m horizontally, 1 m vertically) ● Reported metrics: ○ RMS offset from LOLA (m) calculated from vertical offsets at each LOLA shot. ○ Calculated Lat/Lon/Elevation offsets from LOLA (m) Jittered Stereo - In early 2019 LRO’s MIMU* was turned off - Slews taken with only the star trackers result in new challenges - More movement during image acquisition -> some DTMs have reduced accuracy/precision - Some issues can be mitigated by - Partially cropping the DTM to remove difficult-to-control areas - Including additional parameters in MST algorithm (requires testing for each project) - Creating DTM at coarser pixel scale only by cropping images *MIMU = Miniature Inertial Measurement Unit DTMs attempted since April 2019 (n=20) Where to find these metrics? Readme DTM Shapefile (http://wms.lroc.asu.edu/lroc/view_rdr/SHAPEFILE_NAC_DTMS) Products • DTM, confidence map, and orthophotos are re-imported into ISIS • ISIS map projection is generated from SOCET SET metadata (equirectangular, centered ~ DTM center) Note: DTM elevation values are relative to the IAU2000 Moon ellipsoid (r=1737400 m) Derived Products • Additional products generated using GDAL – Color-shaded relief map – Slope map – Terrain shade – 32-bit geotiff version of DTM • README (text file) – Error analysis – Notes on product interpretation • DTMs released every 3 months and archived to the PDS (http://wms.lroc.asu.edu/lroc/rdr_product_select) DTMs (530) Stereo (4,614) How to Find Data Topography: http://wms.lroc.asu.edu/lroc/rdr_product_select GIS shapefile for DTM coverage: http://wms.lroc.asu.edu/lroc/view_rdr/SHAPEFILE_NAC_DTMS Note the limited polar coverage -- due to difficulty of making DTMs. Transitioning to Socet GXPTM Socet GXP™ BAE Systems’ new photogrammetric solution. version 3.2 released 2009 • image analysis, • photogrammetry, • remote sensing, • video exploitation, • cartography, • feature extraction, • 3-D visualization and manual editing * ~50 Sensor models: “numerous electro-optical, infrared, multispectral, hyperspectral and synthetic aperture radar (SAR) and LiDAR sensors. Many GXP sensor models are rigorous (i.e., they mathematically model the physical characteristics of the sensor), providing a degree of accuracy far above standard models which generally fit the physical system but don’t replicate its inner structure.” – link GXP™ has established close ties with the Community Sensor Model (CSM) working group, government agencies, … Community Sensor Model (CSM) ● CSM is simply a standardized application programming interface (API) developed by the U.S. Air Force and the National Geospatial Intelligence Agency and now supported by the CSM Working Group. ● “Underlying a CSM is a mathematical model described by equations, an algorithm, and a process that defines a coordinate transformation from a sensor’s image space (2- dimensional) to ground space (3-dimensional).” CSM W.G., 2007 link ○ rigorous method to compute: image_to_ground, ground_to_image ● Our transition started in earnest in 2016 ○ First, required update to CSM standard to allow for non-Earth radii. Implement by CSM W.G. in v3.0.3. ○ Second, open source BAE’s existing pushbroom CSM, update, add new sensor models, test, test, train… paper: Laura et al., 2019, Planetary Sensor Models Interoperability Using the Community Sensor Model Specification: https://doi.org/10.1029/2019EA000713 Community Sensor Model (CSM) Where are we: Jupyter - test, test, train in GXP Instrument Notebooks Production