Journal
ICARUS
Volume 391, Issue -, Pages -Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.icarus.2022.115341
Keywords
Mars surface; Image processing; Instrumentation
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Digital Elevation Models (DEMs) are widely used in planetary sciences, including for Mars. They provide necessary topography parameters for geomorphological studies. However, DEMs are not free from vertical errors, leading to uncertainties in calculating parameters such as local slopes. Slope maps computed from DEMs often display slope patterns unrelated to the original images, which may originate from DEM vertical errors. To investigate this, a numerical method is proposed to quantitatively analyze slope errors based on DEM error propagation using synthetic models. The method reveals that vertical errors in DEMs can generate slope patterns similar to those observed. Estimates of slope errors are also provided for four martian cameras, aiming to constrain local slope uncertainties in geomorphological studies.
Digital Elevation Models (DEM) are widely used in planetary sciences, including for the specific case of Mars. DEMs allow us to extract topography parameters necessary in geomorphological studies. However, DEMs are not free from vertical errors, which yields uncertainties in calculations of parameters such as local slopes. In addition, slope maps computed from DEMs often display slope patterns which are not spatially correlated with the original images. We suspect such slope patterns to originate from DEM vertical errors. To investigate this question, we propose a fully numerical method to provide a quantitative analysis of slope errors based on DEM error propagation using synthetic models. We find that the addition of vertical errors following a normal distribution (random noise) leads to the occurrence of slope patterns comparable to those in observed data. Results are similar for the two models of spatially correlated errors. We also provide estimations of slope errors for four martian cameras: HiRISE (High Resolution Imaging Science Experiment), CaSSIS (Colour and Stereo Surface Imaging System), HRSC (High Resolution Stereo Camera) and MOC (Martian Orbiter Camera). These estimations aim to be used as first order uncertainty constraints on local slopes for geomorphological studies.
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