predGeo {geomod}

Function to develop spatial map of Geotechnical soil properties

Description

This functions is used to estimate spatial maps of Geotechnical soil properties using machine learning technique

Usage

predGeo(indata,fgrid, k, z, model="rf")

Arguments

indata

one column input spatial dataframe containing the target soil variable or its transformation

fgrid

Input grid or raster stack containing predictors set for the target soil variable

k

Set limit for number of simulations for the spatial modelling algorithm

z

Confidence interval level in percent (for example 95)

model

The model for predicting target soil variable using the predictors (for example linear)

Details

One-variable input dataframe is prefered or at least the first column should have the target Geotechnical variable to predict. It should not contain NAs. The number of realizations k need not be too high because the software multiplies it exponentially and may slow down the computing process if set to a high value. For example k=5 will results into more than 40 realizations created

Value

a raster map of prediction for the target Geotechnical property

Note

The input dataframe and predictors need to have similar coordinate reference system (CRS). In addition, the input dataframe should not have missing entrie (NAs)

Author(s)

Festus K. Ngeno and Christian Omuto

See Also

regmodelSuit

Examples

library(caret)
library(sp)
library(rasterVis)
library(raster)
library(randomForest)
data(predLayer)
data(sampleData)
soils=subset(sampleData,!is.na(sampleData$LL))
dattu=sampleData[,c("LL")]

  Tesrd=predGeo(dattu,predLayer,k=3,90,"lm")