Physically-based digital geomorphological mapping: Case study of glacial and karst topography

IF 3.1 2区 地球科学 Q2 GEOGRAPHY, PHYSICAL Geomorphology Pub Date : 2024-11-28 DOI:10.1016/j.geomorph.2024.109539
Anton B. Popov , Jozef Minár , Lucian Drǎguţ
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Abstract

Digital geomorphological mapping is considered here as a semi-automated procedure of division the land surface into genetically meaningful objects. The basis is automatic segmentation into elementary forms, the smallest and indivisible elements of the land surface, should be geometrically clearly identifiable, with maximal internal homogeneity and clear discontinuities at their boundaries. These elements can then be combined into more complex genetically homogeneous composite forms. Given the crucial role of gravitational energy in landform formation, it should also be considered in elementary land surface segmentation . This research builds on the theoretical foundation of physical geomorphometry, which explores the relationship between gravitational energy and geomorphometric variables. Specifically, we apply the recently published algorithm for physically-based elementary land surface segmentation by Minár et al. (2024), which utilizes dynamic least squares (DLS) generalization within a GEOBIA framework. The algorithm was initially tested in structurally fluvial hilly terrain using nine physically interpretable gravity-specific point-based variables (elevation, slope aspect and gradient, three basic curvatures, and three changes in curvature). In this study, we extend the application of this algorithm to two different areas of the Western Carpathians: the glacial topography of its highest part and a karst plateau. By using a slightly simplified and specifically modified version of the physically-based algorithm, we achieved plausible and genetically interpretable results in both case studies, which confirms the value of physical geomorphometry in geomorphological mapping. Additionally, a novel concept of physical-geomorphometric signature was applied in both case studies as a support for the physical-geomorphometric analysis. The physical-geomorphometric signature is very helpful in the quantitative comparison between various genetic groups of landforms.
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基于物理的数字地貌制图:冰川和喀斯特地形的案例研究
数字地貌测绘在这里被认为是一种将地表划分为具有遗传意义的对象的半自动化过程。其基础是自动分割成基本形式,即地表最小和不可分割的元素,在几何上应该是清晰可识别的,内部均匀性最大,边界处有明显的不连续。然后,这些元素可以组合成更复杂的基因同质组合形式。鉴于重力能在地形形成中的重要作用,在基本的地表分割中也应考虑重力能。本研究建立在物理地貌学的理论基础上,探讨了重力能与地貌变量之间的关系。具体来说,我们将最近发表的算法应用于Minár等人(2024)基于物理的基本陆地表面分割,该算法在GEOBIA框架内利用动态最小二乘(DLS)概化。该算法最初在河流丘陵地形上进行了测试,使用了9个物理可解释的重力特定点变量(高程、坡向和坡度、3个基本曲率和3个曲率变化)。在这项研究中,我们将该算法的应用扩展到喀尔巴阡山脉西部的两个不同地区:其最高部分的冰川地形和喀斯特高原。通过使用稍微简化和专门修改的基于物理的算法,我们在两个案例研究中都获得了合理和遗传可解释的结果,这证实了物理地貌学在地貌制图中的价值。此外,在这两个案例研究中应用了一个新的物理地貌特征概念,作为物理地貌分析的支持。物理地貌特征对不同地貌成因群之间的定量比较非常有帮助。
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来源期刊
Geomorphology
Geomorphology 地学-地球科学综合
CiteScore
8.00
自引率
10.30%
发文量
309
审稿时长
3.4 months
期刊介绍: Our journal''s scope includes geomorphic themes of: tectonics and regional structure; glacial processes and landforms; fluvial sequences, Quaternary environmental change and dating; fluvial processes and landforms; mass movement, slopes and periglacial processes; hillslopes and soil erosion; weathering, karst and soils; aeolian processes and landforms, coastal dunes and arid environments; coastal and marine processes, estuaries and lakes; modelling, theoretical and quantitative geomorphology; DEM, GIS and remote sensing methods and applications; hazards, applied and planetary geomorphology; and volcanics.
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