Automatically calculating the apparent depths of pits using the Pit Topography from Shadows (PITS) tool

Daniel Le Corre, D. Mary, N. Mason, J. Bernard-Salas, Nick Cox
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Abstract

Pits, or pit craters, are near-circular depressions found in planetary surfaces, which are generally formed through gravitational collapse. Pits will be primary targets for future space exploration and habitability for their presence on most rocky Solar System surfaces and their potential to be entrances to sub-surface cavities. This is particularly true on Mars, where caves have been simulated to harbour stable reserves of ice water across much of the surface. Caves can also provide natural shelter from the high radiation dosages experienced at the surface. Since pits are rarely found to have corresponding high-resolution elevation data, tools are required for approximating their depths in order to find those which are the ideal candidates for follow-up remote investigation and future exploration. The Pit Topography from Shadows (PITS) tool has been developed to automatically calculate the apparent depth of a pit (h) by measuring the width of its shadow as it appears in satellite imagery. The tool requires just one cropped single- or multi-band image of a pit to calculate a profile of h along the length of the shadow, thus allowing for depth calculation where altimetry or stereo image data is not available. We also present a method for correcting shadow width measurements made in non-nadir observations for all possible values of emission and solar/satellite azimuth angles. Shadows are extracted using image segmentation in the form of k-means clustering and silhouette analysis. Across 19 shadow-labelled Mars Reconnaissance Orbiter red-band HiRISE images of Atypical Pit Craters (APCs) from the Mars Global Cave Candidate Catalog (MGC3), PITS detected 99.6 per cent of all shadow pixels (with 94.8 per cent of all detections being true shadow pixels). Following this testing, PITS has been applied to 123 red-band HiRISE images containing 88 APCs, which revealed an improvement in the variation of the calculated h due to emission angle correction, and also found 10 APCs that could be good candidates for cave entrances on Mars due to their h profiles.
使用坑地形从阴影(坑)工具自动计算坑的表观深度
坑或坑坑是在行星表面发现的近圆形洼地,通常是由引力坍缩形成的。凹坑将成为未来太空探索的主要目标,因为它们存在于太阳系大多数岩石表面,并有可能成为地下洞穴的入口。在火星上尤其如此,在那里,洞穴被模拟成在大部分地表上都有稳定的冰水储备。洞穴还可以提供天然的避难所,以躲避地表的高辐射剂量。由于很少发现坑具有相应的高分辨率高程数据,因此需要工具来近似其深度,以便找到后续远程调查和未来勘探的理想候选者。凹坑的阴影地形(PITS)工具已经开发出来,通过测量凹坑在卫星图像中出现的阴影宽度,自动计算凹坑的表观深度(h)。该工具只需要一个裁剪的单波段或多波段凹坑图像来计算沿阴影长度的h轮廓,从而允许深度计算,而高度测量或立体图像数据不可用。我们还提出了一种校正非最低点观测中所有可能的发射和太阳/卫星方位角值的阴影宽度测量的方法。采用k-均值聚类和轮廓分析的图像分割方法提取阴影。在火星全球洞穴候选目录(MGC3)的19个阴影标记的火星侦察轨道器红带HiRISE非典型坑坑(apc)图像中,PITS检测到99.6%的阴影像素(其中94.8%是真正的阴影像素)。在此测试之后,将PITS应用于包含88个apc的123张红色波段HiRISE图像,发现由于发射角校正,计算h的变化有所改善,并且还发现10个apc由于其h剖面可能是火星洞穴入口的良好候选者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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