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"

DOI:10.4121/96c54816-4e36-4285-89fd-a63e478f9acd.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/96c54816-4e36-4285-89fd-a63e478f9acd

Datacite citation style

van Doorn, Maarten; Anatol Helfenstein; Ros, Gerard H.; Heuvelink, Gerard B.M.; van Rotterdam-Los, Debby et. al. (2024): 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". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/96c54816-4e36-4285-89fd-a63e478f9acd.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

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.


History

  • 2024-02-29 first online, published, posted

Publisher

4TU.ResearchData

Format

tiff

Organizations

Nutriënten Management Instituut; Wageningen University & Research;
ISRIC - World Soil Information

DATA

Files (74)