landmap (version 0.0.13)

cookfarm: The Cook Agronomy Farm data set

Description

The R.J. Cook Agronomy Farm (cookfarm) is a Long-Term Agroecosystem Research Site operated by Washington State University, located near Pullman, Washington, USA. Contains spatio-temporal (3D+T) measurements of three soil properties and a number of spatial and temporal regression covariates.

Usage

data(cookfarm)

Format

The cookfarm data set contains four data frames. The readings data frame contains measurements of volumetric water content (cubic-m/cubic-m), temperature (degree C) and bulk electrical conductivity (dS/m), measured at 42 locations using 5TE sensors at five standard depths (0.3, 0.6, 0.9, 1.2, 1.5 m) for the period "2011-01-01" to "2012-12-31":

SOURCEID

factor; unique station ID

Date

date; observation day

Port*VW

numeric; volumetric water content measurements at five depths

Port*C

numeric; soil temperature measurements at five depths

Port*EC

numeric; bulk electrical conductivity measurements at five depths

The profiles data frame contains soil profile descriptions from 142 sites:

SOURCEID

factor; unique station ID

Easting

numeric; x coordinate in the local projection system

Northing

numeric; y coordinate in the local projection system

TAXNUSDA

factor; Keys to Soil Taxonomy taxon name e.g. "Caldwell"

HZDUSD

factor; horizon designation

UHDICM

numeric; upper horizon depth from the surface in cm

LHDICM

numeric; lower horizon depth from the surface in cm

BLD

bulk density in tonnes per cubic-meter

PHIHOX

numeric; pH index measured in water solution

The grids data frame contains values of regression covariates at 10 m resolution:

DEM

numeric; Digital Elevation Model

TWI

numeric; SAGA GIS Topographic Wetness Index

MUSYM

factor; soil mapping units e.g. "Thatuna silt loam"

NDRE.M

numeric; mean value of the Normalized Difference Red Edge Index (time series of 11 RapidEye images)

NDRE.sd

numeric; standard deviation of the Normalized Difference Red Edge Index (time series of 11 RapidEye images)

Cook_fall_ECa

numeric; apparent electrical conductivity image from fall

Cook_spr_ECa

numeric; apparent electrical conductivity image from spring

X2011

factor; cropping system in 2011

X2012

factor; cropping system in 2012

The weather data frame contains daily temperatures and rainfall from the nearest meteorological station:

Date

date; observation day

Precip_wrcc

numeric; observed precipitation in mm

MaxT_wrcc

numeric; observed maximum daily temperature in degree C

MinT_wrccc

numeric; observed minimum daily temperature in degree C

References

• Gasch, C.K., Hengl, T., Graeler, B., Meyer, H., Magney, T., Brown, D.J., 2015. Spatio-temporal interpolation of soil water, temperature, and electrical conductivity in 3D+T: the Cook Agronomy Farm data set. Spatial Statistics, 14, pp. 70--90. 10.1016/j.spasta.2015.04.001

• Gasch, C. K., Brown, D. J., Campbell, C. S., Cobos, D. R., Brooks, E. S., Chahal, M., & Poggio, M. 2017. A Field-Scale Sensor Network Data Set for Monitoring and Modeling the Spatial and Temporal Variation of Soil Water Content in a Dryland Agricultural Field. Water Resources Research, 53(12), 10878-10887. 10.1002/2017wr021307

Examples

# NOT RUN {
library(rgdal)
data(cookfarm)

## gridded data:
grid10m <- cookfarm$grids
gridded(grid10m) <- ~x+y
proj4string(grid10m) <- CRS(cookfarm$proj4string)
#spplot(grid10m["DEM"], col.regions=SAGA_pal[[1]])

## soil profiles:
profs <- cookfarm$profiles
levels(cookfarm$profiles$HZDUSD)
## Bt horizon:
sel.Bt <- grep("Bt", profs$HZDUSD, ignore.case=FALSE, fixed=FALSE)
profs$Bt <- 0
profs$Bt[sel.Bt] <- 1
# }