Evaluation of close-range stereo matching algorithms using stereoscopic measurements

The performance of binocular stereo reconstruction is highly dependent on the quality of the stereo matching result. In order to evaluate the performance of different stereo matchers, several quality metrics have been developed based on quantifying error statistics with respect to a set of independent measurements usually referred to as ground truth data. However, such data are frequently not available, particularly in practical applications or planetary data processing. To address this, we propose a ground truth independent evaluation protocol based on manual measurements. A stereo visualization tool has been specifically developed to evaluate the quality of the computed correspondences. We compare the quality of disparity maps calculated from three stereo matching algorithms, developed based on a variation of GOTCHA, which has been used in planetary robotic rover image reconstruction at UCL-MSSL (Otto and Chau, 1989). From our evaluation tests with the images pairs from Mars Exploration Rover (MER) Pancam and the field data collected in PRoViScout 2012, it has been found that all three processing pipelines used in our test (NASA-JPL, JR, UCL-MSSL) trade off matching accuracy and completeness differently. NASA-JPL's stereo pipeline produces the most accurate but less complete disparity map, while JR's pipeline performs best in terms of the reconstruction completeness

Preliminary Observations on New Images of the Elysium Frozen Sea Deposits from HRSC Mars Express

Abstract not available

Mapping Arctic Sea-Ice Surface Roughness with Multi-Angle Imaging SpectroRadiometer

Sea-ice surface roughness (SIR) is a crucial parameter in climate and oceanographic studies, constraining momentum transfer between the atmosphere and ocean, providing preconditioning for summer-melt pond extent, and being related to ice age and thickness. High-resolution roughness estimates from airborne laser measurements are limited in spatial and temporal coverage while pan-Arctic satellite roughness does not extend over multi-decadal timescales. Launched on the Terra satellite in 1999, the NASA Multi-angle Imaging SpectroRadiometer (MISR) instrument acquires optical imagery from nine near-simultaneous camera view zenith angles. Extending on previous work to model surface roughness from specular anisotropy, a training dataset of cloud-free angular reflectance signatures and surface roughness, defined as the standard deviation of the within-pixel lidar elevations, from near-coincident operation IceBridge (OIB) airborne laser data is generated and is modelled using support vector regression (SVR) with a radial basis function (RBF) kernel selected. Blocked k-fold cross-validation is implemented to tune hyperparameters using grid optimisation and to assess model performance, with an R2 (coefficient of determination) of 0.43 and MAE (mean absolute error) of 0.041 m. Product performance is assessed through independent validation by comparison with unseen similarly generated surface-roughness characterisations from pre-IceBridge missions (Pearson’s r averaged over six scenes, r = 0.58, p < 0.005), and with AWI CS2-SMOS sea-ice thickness (Spearman’s rank, rs = 0.66, p < 0.001), a known roughness proxy. We present a derived sea-ice roughness product at 1.1 km resolution (2000–2020) over the seasonal period of OIB operation and a corresponding time-series analysis. Both our instantaneous swaths and pan-Arctic monthly mosaics show considerable potential in detecting surface-ice characteristics such as deformed rough ice, thin refrozen leads, and polynyas

Elevation Extraction from Spaceborne SAR Tomography Using Multi-Baseline COSMO-SkyMed SAR Data

SAR tomography (TomoSAR) extends SAR interferometry (InSAR) to image a complex 3D scene with multiple scatterers within the same SAR cell. The phase calibration method and the super-resolution reconstruction method play a crucial role in 3D TomoSAR imaging from multi-baseline SAR stacks, and they both influence the accuracy of the 3D SAR tomographic imaging results. This paper presents a systematic processing method for 3D SAR tomography imaging. Moreover, with the newly released TanDEM-X 12 m DEM, this study proposes a new phase calibration method based on SAR InSAR and DEM error estimation with the super-resolution reconstruction compressive sensing (CS) method for 3D TomoSAR imaging using COSMO-SkyMed Spaceborne SAR data. The test, fieldwork, and results validation were executed at Zipingpu Dam, Dujiangyan, Sichuan, China. After processing, the 1 m resolution TomoSAR elevation extraction results were obtained. Against the terrestrial Lidar ‘truth’ data, the elevation results were shown to have an accuracy of 0.25 ± 1.04 m and a RMSE of 1.07 m in the dam area. The results and their subsequent validation demonstrate that the X band data using the CS method are not suitable for forest structure reconstruction, but are fit for purpose for the elevation extraction of manufactured facilities including buildings in the urban area

Combination of MRO SHARAD and deep-learning-based DTM to search for subsurface features in Oxia Planum, Mars

Context. Oxia Planum is a mid-latitude region on Mars that attracts a great amount of interest worldwide. An orbiting radar provides an effective way to probe the Martian subsurface and detect buried layers or geomorphological features. The Shallow radar orbital radar system on board the NASA Mars reconnaissance orbiter transmits pulsed signals towards the nadir and receives returned echoes from dielectric boundaries. However, radar clutter can be induced by a higher topography of the off-nadir region than that at the nadir, which is then manifested as subsurface reflectors in the radar image. Aims. This study combines radar observations, terrain models, and surface images to investigate the subsurface features of the ExoMars landing site in Oxia Planum. Methods. Possible subsurface features are observed in radargrams. Radar clutter is simulated using the terrain models, and these are then compared to radar observations to exclude clutter and identify possible subsurface return echoes. Finally, the dielectric constant is estimated with measurements in both radargrams and surface imagery. Results. The resolution and quality of the terrain models greatly influence the clutter simulations. Higher resolution can produce finer cluttergrams, which assists in identifying possible subsurface features. One possible subsurface layering sequence is identified in one radargram. Conclusions. A combination of radar observations, terrain models, and surface images reveals the dielectric constant of the surface deposit in Oxia Planum to be 4.9–8.8, indicating that the surface-covering material is made up of clay-bearing units in this region

A High-Resolution Digital Terrain Model Mosaic of the Mars 2020 Perseverance Rover Landing Site at Jezero Crater

We demonstrate the capabilities of a published MADNet monocular height estimation network in producing a refined digital terrain model (DTM) mosaic at 50 cm/pixel resolution for the Mars 2020 Perseverance rover landing site in Jezero crater on Mars. Our approach utilizes the publicly available Mars 2020 Terrain Relative Navigation (TRN) High-Resolution Imaging Science Experiment (HiRISE) Digital Terrain Model (DTM) mosaic, which was originally created by the United States Geological Survey (USGS) Astrogeology Science Centre. Our resultant HiRISE MADNet DTM mosaic is strictly matched with the original HiRISE TRN DTM and orthoimage mosaics. These mosaics are themselves co-aligned with the USGS TRN Context Camera (CTX) based DTM and orthoimage mosaics, as well as the ESA/DLR/FUB (European Space Agency/German Aerospace Center/Free University Berlin) High Resolution Stereo Camera (HRSC) level 5 DTM and orthoimage mosaics. In this paper, we provide a brief description of the technical details, and present both visual and quantitative assessments of the refined MADNet HiRISE Jezero DTM mosaic product. This DTM product is now publicly available at http://dx.doi.org/10.17169/refubium-38359

Calibrating mars orbiter laser altimeter pulse widths at mars science laboratory candidate landing sites

Accurate estimates of surface roughness allow quantitative comparisons between planetary terrains. These comparisons enable us to improve our understanding of commonly occurring surface processes, and develop a more complete analysis of candidate landing and roving sites. A (secondary) science goal of the Mars Orbiter Laser Altimeter was to map surface roughness within the laser footprint using the backscatter pulse-widths of individual pulses, at finer scales than can be derived from the elevation profiles. On arrival at the surface, these pulses are thought to have diverged to between 70 and 170 m, corresponding to surface roughness estimates at 35 and 70 m baselines respectively; however, the true baseline and relationship remains unknown. This work compares the Mars Orbiter Laser Altimeter pulse-widths to surface roughness estimates at various baselines from high-resolution digital terrain models at the final four candidate landing sites of Mars Science Laboratory. The objective was to determine the true baseline at which surface roughness can be estimated, and the relationship between surface roughness and the pulse-widths, to improve the reliability of current global surface roughness estimates from pulse-width maps. The results seem to indicate that pulse-widths from individual shots are an unreliable indicator of surface roughness, and instead, the pulse-widths should be downsampled to indicate regional roughness, with the Slope-Corrected pulse-width dataset performing best. Where Rough Patches are spatially large compared to the footprint of the pulse, pulse-widths can be used as an indicator of surface roughness at baselines of 150 to 300 m; where these patches are spatially small, as observed at Mawrth Vallis, pulse-widths show no correlation to surface roughness. This suggests that a more complex relationship exists, with varying correlations observed, which appear dependent on the distribution of roughness across the sites

Ultra-High-Resolution 1 m/pixel CaSSIS DTM Using Super-Resolution Restoration and Shape-from-Shading: Demonstration over Oxia Planum on Mars

We introduce a novel ultra-high-resolution Digital Terrain Model (DTM) processing system using a combination of photogrammetric 3D reconstruction, image co-registration, image super-resolution restoration, shape-from-shading DTM refinement, and 3D co-alignment methods. Technical details of the method are described, and results are demonstrated using a 4 m/pixel Trace Gas Orbiter Colour and Stereo Surface Imaging System (CaSSIS) panchromatic image and an overlapping 6 m/pixel Mars Reconnaissance Orbiter Context Camera (CTX) stereo pair to produce a 1 m/pixel CaSSIS Super-Resolution Restoration (SRR) DTM for different areas over Oxia Planum on Mars—the future ESA ExoMars 2022 Rosalind Franklin rover’s landing site. Quantitative assessments are made using profile measurements and the counting of resolvable craters, in comparison with the publicly available 1 m/pixel High-Resolution Imaging Experiment (HiRISE) DTM. These assessments demonstrate that the final resultant 1 m/pixel CaSSIS DTM from the proposed processing system has achieved comparable and sometimes more detailed 3D reconstruction compared to the overlapping HiRISE DT

A new global fAPAR and LAI dataset derived from optimal albedo estimates: comparison with MODIS products

We present the first comparison between new fAPAR and LAI products derived from the GlobAlbedo dataset and the widely-used MODIS fAPAR and LAI and products. The GlobAlbedo derived products are produced using a 1D two-stream radiative transfer (RT) scheme designed explicitly for global parameter retrieval from albedo, with consistency between RT model assumptions and observations, as well as with typical large-scale land surface model RT schemes. The approach does not require biome-specific structural assumptions (e.g. cover, clumping, understory), unlike more detailed 3D RT model approaches. GlobAlbedo-derived values of fAPAR and LAI are compared with MODIS values over 2002-2011 at multiple flux tower sites within selected biomes, over 1200 × 1200 km regions and globally. GlobAlbedo-derived fAPAR and LAI values are temporally more stable than the MODIS values due to (1) the smoothness of the underlying albedo, derived via optimal estimation (assimilation) using an a priori estimate of albedo derived from an albedo ‘climatology’ (composited multi-year albedo observations) and (2) space-time invariant prior information in the inversion of the two-stream RT scheme. Parameters agree closely in timing but with GlobAlbedo values consistently lower than MODIS, particularly for LAI. Larger differences occur in winter (when values are lower) and in the Southern hemisphere. Globally, we find that: GlobAlbedo-derived fAPAR is ~0.9- 1.01 × MODIS fAPAR with an offset of ~0.03; GlobAlbedo-derived LAI is ~0.6 × MODIS LAI with an offset of ~0.2. Differences arise due to the RT model assumptions underlying the products, meaning care is required in interpreting either set of values, particularly when comparing to finescale ground-based estimates. We present global calibrations between GlobAlbedo-derived and MODIS products.JRC.H.5-Land Resources Managemen