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Geomorphographic terrain classification for predictingforest soil properties in Northwestern Switzerland

机译:地貌地形分类法预测瑞士西北部的森林土壤特性

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Digital terrain classification is of elementary importance for model-based predic-tion of the spatial distribution of soil properties and local water balance. This study describes a terrain analysis method that combines modeled and defined geomorphographic terrain attributes with detailed field knowledge and local mapping experience. 450 forest soil profiles were used to statistically analyze the correlation to soil properties. The result is a two-stage hierarchical terrain classification approach that provides a differentiated and satisfactory reproduction of characteristic terrain attributes in the primary landscape units. As field sur-veys show, modeled steep slopes, ridges, slope edges, convex and concave slope formations correlate well to local landform elements. Up to now, the results for mid slope modeling have been unsatisfactory. Furthermore, non-relevant or incorrectly delimitated landform elements were also modeled, making manual correction indispensible. In order for terrain modeling to be feasible it is necessary to entail detailed terrain knowledge of the region to be modeled. In this study, statistical analyses of the correlation between soil properties and modeled landform elements were conducted. The results show that steep slopes, convex and concave slope for-mations, steep stream channels and rock faces correlate well to soil properties. A few single relations were found for plateaus and ridges and trough-shaped valleys. Slope edges and mid slopes show almost no characteristic soil properties. Modeled landform elements are the most essential predictor for the development of prediction models for forest soil properties. The complex morphographic terrain classification approach, described in this study, is a feasible spatial and hierarchical basis for decision-based prediction models.
机译:数字地形分类对于基于模型的土壤属性空间分布和局部水平衡的预测至关重要。这项研究描述了一种地形分析方法,该方法将建模和定义的地貌地形属性与详细的现场知识和本地制图经验相结合。使用450种森林土壤剖面对与土壤特性的相关性进行统计分析。结果是两阶段的分层地形分类方法,该方法在主要景观单元中提供了特征性地形属性的差异化和令人满意的再现。正如现场调查所显示的那样,建模的陡坡,山脊,边坡边缘,凸面和凹面的坡度与当地地形要素的相关性很好。到目前为止,中坡建模的结果还不令人满意。此外,还对不相关或边界不正确划定的地形要素进行了建模,使得人工校正必不可少。为了使地形建模可行,有必要对要建模的区域进行详细的地形知识。在这项研究中,对土壤性质和模拟的地形要素之间的相关性进行了统计分析。结果表明,陡坡,凹凸面形态,陡峭的河道和岩面与土壤特性密切相关。在高原,山脊和槽形山谷中发现了一些单一的关系。边坡和中坡几乎没有特征性的土壤性质。建模的地形要素是开发森林土壤特性预测模型的最重要的预测因子。在这项研究中描述的复杂形态地形分类方法,是基于决策的预测模型的可行的空间和层次基础。

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