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• W2509631742 abstract "Information on soils such as nutrient availability is essential for sustainable mountain ecosystem management. Heterogeneous soil nutrients might determine growth, distribution, and diversity of plants. Therefore, spatial patterns of soil nutrients should be investigated in mountainous areas. Digital soil mapping (soil landscape modelling) was used for important chemical soil parameters in the Soyang lake watershed, South Korea. Specific purposes are: (1) to develop maps of soil nutrients for ecological land potential assessment, (2) to investigate spatial patterns of various phosphorus (P) fractions, and (3) to predict nitrogen (N) to P ratios in the topsoil layer. Firstly, vegetation indices had the highest predictive power for soil nutrients. Using selected instead of all predictors via recursive feature elimination (RFE) improved prediction results considerably. Random forest (RF) showed the best performance compared to support vector regression (SVR) and generalized additive models (GAM). Cluster analysis identified four land potential classes: fertile, medium and unfertile with an additional class dominated by high phosphorus and low carbon and nitrogen contents due to human impact. This study provides an effective approach to map ecological land potentials for sustainable mountain ecosystem management.Secondly, surface curvature and elevation were important predictors for all P fractions. The concentrations of all P fractions changed with surface curvature and elevation. Higher values of most P fractions were found at the lower slope due to soil erosion. Especially, organic P was enriched at the lower slope, while the relative portion of residual P fractions was largest at the upper slope. Finally, surface curvature was selected as an important predictor for P contents in organic and mineral A horizons. LiDAR derived vegetation predictors and normalized difference vegetation index (NDVI) strongly contributed to model N in the organic layer. N to P ratios in the organic and mineral A horizons showed higher values at convex upper slopes and increased with surface curvature. This implies that spatial patterns of P and N in a mountainous catchment with steep slopes under monsoon conditions are mainly controlled by topography.In this thesis, various methods (e.g. predictor selection and importance, uncertainty assessment, and LiDAR analysis) were applied to digital soil mapping. Important environmental predictors and processes related to spatial patterns of soil nutrients were investigated. Based on our results, it is possible to better understand soil nutrient dynamics in landscapes and identify sensitive areas under environmental changes (e.g. areas with high nitrogen deposition).%%%%Informationen uber Boden, insbesondere deren Nahrstoffverfugbarkeit, sin notwendig fur ein nachhaltiges Management von Gebirgslandschaften. Die raumliche Verteilung der Bodennahrstoffe hat hierbei oft einen grosen Einfluss auf Wachstum, Verteilung und Diversitat der Pflanzen. Der Erfassung der Raummuster von…" @default.
• W2509631742 created "2016-09-16" @default.
• W2509631742 creator A5028686687 @default.
• W2509631742 date "2016-01-01" @default.
• W2509631742 modified "2023-09-28" @default.
• W2509631742 title "Digital Soil Mapping for Functional Analysis of Site Characteristics in Complex Terrain" @default.
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