This study investigates the complexity of spatial soil modelling, particularly focusing on the challenge of variable vertical support in traditional soil data collection. Traditional soil sampling, described in terms of horizons, often fails to accurately pinpoint the specific depths for specific soil properties. This gap is significant, as depth-specific data is crucial for a thorough understanding of soil formation processes and for assessing potential environmental impacts. In digital soil mapping (DSM), the prevalent reliance on standardised depth intervals and mass-preserving spline functions for data resampling results in a modelling approach that tends to disregard depth-related details, thereby introducing potential uncertainties.

中文翻译：

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多个空间支撑上三维土壤测绘的高斯过程回归


本研究研究了空间土壤建模的复杂性，特别关注传统土壤数据收集中可变垂直支撑的挑战。传统的土壤采样以地平线来描述，通常无法准确地确定特定土壤特性的特定深度。这一差距是巨大的，因为特定深度的数据对于彻底了解土壤形成过程和评估潜在的环境影响至关重要。在数字土壤测绘（DSM）中，数据重采样普遍依赖标准化深度间隔和质量保持样条函数，导致建模方法往往忽视与深度相关的细节，从而引入潜在的不确定性。