Abstract Flow pattern reconstructions for past glaciations are based on the analysis of the spatial distribution of subglacial landforms, and streamlined subglacial landforms (oriented parallel or sub-parallel to the ice flow) are regarded as the main indicators of the previous ice flow. Manual mapping of these landforms is a time consuming and subjective process, making semi-automated mapping (SAM) methods attractive. We present a novel SAM method that extracts mean directional trends from a digital elevation model (DEM) by performing greyscale thinning on its derived slope raster, and produce directional statistics from the lines extracted from the resulting skeleton. The method has been tested on artificial (synthetically generated) surfaces to demonstrate its potential for detecting directions of idealized landforms. The tests carried out on the artificial surfaces reveal that a landform feature has to be at least six (raster) cells wide for its direction to be properly detected by the method. The application of the method on real-world terrain data shows that the method is capable of reconstructing glacial flow patterns, and that it is robust to reasonable variations in the method parameters. We believe that the method should also have great potential for detecting directional trends in the general field of geomorphology. The user friendliness of the method and the simple interpretation of the results should make this a useful tool for geomorphological studies.

中文翻译：

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使用灰度细化和方向趋势分析从数字高程模型中提取和可视化冰川冰流方向

摘要 过去冰期流型重建是基于对冰下地貌空间分布的分析，以流线型冰下地貌（平行或次平行于冰流方向）作为以往冰流的主要指标。这些地貌的手动制图是一个耗时且主观的过程，这使得半自动制图 (SAM) 方法具有吸引力。我们提出了一种新的 SAM 方法，该方法通过在其派生的坡度栅格上执行灰度细化从数字高程模型 (DEM) 中提取平均方向趋势，并从从结果骨架中提取的线生成方向统计信息。该方法已在人工（合成生成）表面上进行了测试，以证明其检测理想化地貌方向的潜力。在人造表面上进行的测试表明，地形特征必须至少有六个（栅格）单元宽，才能通过该方法正确检测其方向。该方法在真实世界地形数据上的应用表明，该方法能够重建冰川流动模式，并且对方法参数的合理变化具有鲁棒性。我们认为，该方法在检测地貌学一般领域的方向趋势方面也应该具有很大的潜力。该方法的用户友好性和对结果的简单解释应使其成为地貌研究的有用工具。该方法在真实世界地形数据上的应用表明，该方法能够重建冰川流动模式，并且对方法参数的合理变化具有鲁棒性。我们认为，该方法在检测地貌学一般领域的方向趋势方面也应该具有很大的潜力。该方法的用户友好性和对结果的简单解释应使其成为地貌研究的有用工具。该方法在真实世界地形数据上的应用表明，该方法能够重建冰川流动模式，并且对方法参数的合理变化具有鲁棒性。我们认为，该方法在检测地貌学一般领域的方向趋势方面也应该具有很大的潜力。该方法的用户友好性和对结果的简单解释应使其成为地貌研究的有用工具。