In envima/GEDItools:

load libraries and read data

library(caret)
library(CAST)
library(dplyr)

model_sf <- readRDS(file = "C:/Users/Alice/Uni/Projekte/GEDI/data/modeling/model_sf.rds")

split training and testing dataset

set.seed(1)
train_sf <- sample_frac(model_sf, size = 0.7)
st_geometry(train_sf) <- NULL
test_sf <- model_sf[!model_sf$ID %in% train_sf$ID,]
st_geometry(test_sf) <- NULL

model

pred <- train_sf[,c(which(colnames(train_sf) == "S1_S1") : which(colnames(train_sf) =="S2_NDVI"))]
resp <- train_sf$pai
mod <- train(pred, resp, method = "ranger", 
                 num.trees = 150, importance = "impurity")
saveRDS(mod, file = "C:/Users/Alice/Uni/Projekte/GEDI/data/modeling/mod.rds")

envima/GEDItools documentation built on July 25, 2020, 5:13 p.m.