Mean Normalized Usage (MNU)

GENERAL INFORMATION

DATA TITLE: Mean Normalized Usage (MNU) of Environmental Covariates for Cubist Soil Property Prediction Models

PROJECT TITLE: Digital soil mapping via machine learning of agronomic properties for the full soil profile at within-field resolution

DATA ABSTRACT: This dataset and code repository contain the results and scripts used to evaluate the relative importance of environmental covariates across 126 machine learning models predicting a suite of soil agronomic properties for the full soil profile (18 soil properties × 7 depth intervals). Covariate importance is normalized to account for usage frequency of covariate predictors as model rules and linear model coefficients across depth class, covariate type, and analysis scale.

AUTHORS

Meyer P. Bohn Iowa State University Department of Agronomy mpbohn@iastate.edu

Bradley A. Miller Iowa State University Department of Agronomy millerba@iastate.edu

ASSOCIATED PUBLICATIONS

Bohn, M.P., B.A. Miller. 2025. Digital soil mapping via machine learning of agronomic properties for the full soil profile at within-field resolution. Agronomy Journal. (In Press)

COLLECTION INFORMATION

Time period(s): 2019 Location(s): Sustainable Advanced Bioeconomy Research Farm, Ames, IA, USA

CODEBOOK

Number Of Variables/Columns: 14 baseline + 6 generated = 20 total Number Of Cases/Rows: 10,108 Missing Data Codes: NA

Columns in the Base Data

Columns in the Base Data

Column

Description

model_conditions

Percent usage as model rule in decision tree

model_usage

Percent usage in multiple linear regression as coefficient

covariate

Covariate name including analysis scale or year

Deriv

Remote-sensed derivative type (Terrain or Imagery)

type1

Specific derivative classification

type2

Generalized derivative classification

stat

Statistical aggregation method

year

Year of remote-sensed data source

prop

Soil property model and depth interval

soil

Soil property name

depth_int

Depth interval (cm)

depth

Cleaned depth interval name (cm)

top_depth

Top depth of depth interval (cm)

bot_depth

Bottom depth of depth interval (cm)

Columns Produced by mean_normalized_usage()

Columns Produced by mean_normalized_usage()

Column

Description

analysis.scale

Analysis scale of covariate (m)

rel_scale

Relative verbal scale classification of analysis scale

depth_class

Verbal scale classification of depth interval

total_usage

Sum of model_conditions and model_usage

total_covs

Total number of covariates in the soil x depth model

total_usage_scaled

Min-max normalized value of total_usage

total_covs_scaled

Min-max normalized value of total_covs

normalized_usage

Product of total_usage_scaled and total_covs_scaled

mean_normalized_usage

Group mean of normalized_usage

Soil Properties Modeled

Soil Properties Modeled

Property

Description

Units

Ca

Calcium cation

mg kg⁻¹

CCE

Calcium Carbonate Equivalent

%

CEC

Cation Exchange Capacity

cmolc kg⁻¹

cf

Coarse Fragments

%

clay

Clay Fraction

%

EC

Electrical Conductivity

dS m⁻¹

K

Potassium cation

mg kg⁻¹

Mg

Magnesium cation

mg kg⁻¹

Na

Sodium cation

mg kg⁻¹

Olsen P

Olsen Test Phosphorus

mg kg⁻¹

pH

pH (1:1 soil water suspension)

sand

Sand Fraction

%

silt

Silt Fraction

%

Cstock

Soil Organic Carbon Stock

g cm⁻²

TOC

Total Organic Carbon

%

Total N

Total Nitrogen

%

Bray P

Bray Test Phosphorus

mg kg⁻¹

buf_pH

Buffered pH

Covariate Metadata

Covariate Metadata

Covariate

Description

CA

Catchment area

crosc

Cross-sectional curvature

CS

Catchment slope

HDCN_strahl3_d

Horizontal distance to channel network (Strahler 3)

IR

Infrared band

MCA

Modified catchment area

NAIP

National Agriculture Imagery Program

nnes

Northness

plc

Plan curvature

prc

Profile curvature

rel

Relative elevation

slp

Slope gradient

SWI

SAGA wetness index

tpi

Topographic position index

wnes

Westness

CONTENTS