isis: ISRIC Soil Information System
In landmap: Automated Spatial Prediction using Ensemble Machine Learning

Description Usage Format Author(s) Examples

ISRIC's collection of global soil monoliths that represent the main soil reference groups of the World Reference Base for Soil Resources (WRB). Includes some 950 monoliths (785 with coordinates) from over 70 countries with detailed soil profile and environmental data.

1	data(isis)

The isis data set contains two data frames — sites and horizons. Sites table contains the following columns:

SOURCEID: factor; unique ISIS code
LONWGS84: numeric; longitude in decimal degrees on the WGS84 datum
LATWGS84: numeric; latitude in decimal degrees on the WGS84 datum
TIMESTRR: Date; the date on which this particular soil was described or sampled
TAXGWRB: factor; soil group based on the WRB classification system
TAXNUSDA: factor; Keys to Soil Taxonomy taxon name e.g. "Natraqualf"
BDRICM: numeric; depth to bedrock (R horizon) if observed
SOURCEDB: factor; source data base

Horizons table contains the following columns:

SOURCEID: factor; unique ISIS code
UHDICM: numeric; upper horizon depth from the surface in cm
LHDICM: numeric; lower horizon depth from the surface in cm
CRFVOL: numeric; volume percentage of coarse fragments (> 2 mm)
PHIHOX: numeric; pH index measured in water solution
PHIKCL: numeric; pH index measured in KCl solution
ORCDRC: numeric; soil organic carbon content in permilles
SNDPPT: numeric; weight percentage of the sand particles (0.05–2 mm)
SLTPPT: numeric; weight percentage of the silt particles (0.0002–0.05 mm)
CLYPPT: numeric; weight percentage of the clay particles (<0.0002 mm)
CEC: numeric; Cation Exchange Capacity in cmol+/kg
BLD: bulk density in tonnes per cubic-meter

ISRIC — World Soil Information

library(rgdal)
library(sp)

data(isis)
sites <- isis$sites
coordinates(sites) <- ~ LONWGS84 + LATWGS84
proj4string(sites) <- "+proj=longlat +datum=WGS84"
## Not run: 
## obtain country borders:
library(maps)
country.m = map('world', plot=FALSE, fill=TRUE)
IDs <- sapply(strsplit(country.m$names, ":"), function(x) x[1])
require(maptools)
country <- as(map2SpatialPolygons(country.m, IDs=IDs), "SpatialLines")
proj4string(country) = "+proj=longlat +datum=WGS84"
## overlay and plot points and maps:
plot(country, col="darkgrey")
points(sites, pch=21, bg="red", cex=.6, col="black")

## End(Not run)