Filling the gaps in soil data: A multi-model framework for addressing data gaps using pedotransfer functions and machine-learning with uncertainty estimates to estimate bulk density-Reference-Cited by-同舟云学术

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Filling the gaps in soil data: A multi-model framework for addressing data gaps using pedotransfer functions and machine-learning with uncertainty estimates to estimate bulk density

Published:2024-10 Issue: Volume:245 Page:108310
ISSN:0341-8162
Container-title:CATENA
language:en
Short-container-title:CATENA

Author:

Arbor Adrienne^ORCID,Schmidt Margaret,Zhang Jin^ORCID,Bulmer Chuck,Filatow Deepa,Kasraei Babak,Smukler Sean^ORCID,Heung Brandon^ORCID

Publisher

Elsevier BV

Reference116 articles.

1. Evaluation of pedotransfer functions for predicting soil bulk density for U.S. soils;Abdelbaki;Ain Shams Eng. J.,2018

2. The effect of organic matter on the bulk and true densities of some uncultivated podzolic soils;Adams;J. Soil Sci.,1973

3. Enhancing pedotransfer functions with environmental data for estimating bulk density and effective cation exchange capacity in a data-sparse situation;Akpa;Soil Use Manag.,2016

4. Assessment of various pedotransfer functions for the prediction of the dry bulk density of cultivated soils in a semiarid environment;Alaboz;Commun. Soil Sci. Plant Anal.,2021

5. Bulk densities of California soils in relation to other soil properties;Alexander;Soil Sci. Soc. Am. J.,1980

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