Digital Soil Maps underlying the publication "high-resolution digital soil mapping of amorphous iron- and aluminium-(hydr)oxides to guide sustainable phosphorus and carbon management"
This dataset contains digital soil maps (.tiff) of predicted soil contents of oxalate-extractable iron and aluminium at a 25 m spatial resolution across six depth layers (0-5 cm, 5-10 cm, 10-25 cm, 25-60 cm, 60-100 cm and 100-200 cm) for agricultural fields in the Netherlands. For each of these depth layers, there is a map of mean predictions, the 5th, 50th (median) and 95th quantile predictions, as well as the 90% prediction interval (PI90 = 95th - 5th quantile) and prediction interval ratio (PIR = PI90 / median). PI90 and PIR represent absolute and relative uncertainty predictions, respectively. The maps were created using Quantile Regression Forest models, which were calibrated using geo-referenced wet-chemical measurements (n = 12,110) and near-infrared (NIR) estimates (n = 102,393) of oxalate-extractable iron and aluminium and over 150 spatial covariates (spatially explicit environmental variables of soil forming factors). See publication for details, including the assessment of map quality using design-based statistical inference.
| Main Authors: | , , , , , , |
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| Format: | Dataset biblioteca |
| Published: |
Wageningen University & Research
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| Subjects: | agriculture, aluminium, digital soil mapping, iron, netherlands, oxalate, phosphorus sorption capacity, soil functions, soil health, |
| Online Access: | https://research.wur.nl/en/datasets/digital-soil-maps-underlying-the-publication-high-resolution-digi |
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