run_sicktree_model_multitile: Run a saved MaxEnt model in predictive mode on a tile of...

In pieterbeck/CanHeMonR: Tools for canopy health monitoring through image analysis

Description

Run a saved MaxEnt model in predictive mode on a tile of image data

Run a saved MaxEnt model in predictive mode on a tile of image data

Usage

run_sicktree_model_multitile(predictors_dir, txt_dir, fname_predictors_txt,
  MaxEntmodel_dir, fname_MaxEntmodel_r, output_dir)

run_sicktree_model_multitile(predictors_dir, txt_dir, fname_predictors_txt,
  MaxEntmodel_dir, fname_MaxEntmodel_r, output_dir)

Arguments

predictors_dir	Direcotry where predictor layers are held
txt_dir	Path where a txt file listing predictor layers is held
fname_predictors_txt	Textfile specifying the predictors (ie covariates) for the model as image filenames in the correct order
MaxEntmodel_dir	Directory where the MaxEnt model file is held
fname_MaxEntmodel_r	Filename of the MaxEnt model saved in rds format (see ?readRDS)
output_dir	Output directory for the tif
fname_predictors_txt	Textfile specifying the predictors (ie covariates) for the model as image filenames in the correct order
fname_MaxEntmodel_r	Filename of the MaxEnt model saved in rds format (see ?readRDS)
output_dir	Directory to write the output to

Value

Saves class-specific distribution models as raster images, using image layers as inputs

Saves class-specific distribution models as raster images, using image layers as inputs

Note

Run in 32-bit R installation.

Examples

## Not run: 
model_dir <- "//ies.jrc.it/h03/CANHEMON/H03_CANHEMON/Imagery/Portugal/DMC/ortophotos_22122016/classification_temp/"

run_sicktree_model_multitile(fname_predictors_txt = file.path(model_dir,'predictors_pt606000_4401000.txt'),
                            fname_MaxEntmodel_r = file.path(model_dir, 'Pb.rdsdata'),
                            fname_output_tif =  file.path(model_dir,'MaxEnt_Pb_pt606000_4401000.tif'))
run the tile for which you had a good model trained on that tile only.
the difference was that that earlier model sampled from circles around the points.
model_dir <- "//ies.jrc.it/h03/CANHEMON/H03_CANHEMON/Imagery/Portugal/DMC/ortophotos_22122016/classification_temp/"
run_sicktree_model_multitile(fname_predictors_txt = file.path(model_dir,'predictors_pt617000_4404000.txt'),
                            fname_MaxEntmodel_r = file.path(model_dir, 'samp10_Pb.rdsdata'),
                            fname_output_tif =  file.path(model_dir,'MaxEnt_Pb_pt617000_4404000_100.tif'))

run_sicktree_model_multitile(
 predictors_dir = "//ies.jrc.it/h03/CANHEMON/H03_CANHEMON/Imagery/Portugal/DMC/ortophotos_22122016/RGBN_LUT",
 txt_dir = "//ies.jrc.it/h03/CANHEMON/H03_CANHEMON/Imagery/Portugal/DMC/ortophotos_22122016/classification_temp/",
 fname_predictors_txt = "predictors_pt617000_4404000.txt",
 MaxEntmodel_dir = "//ies.jrc.it/h03/CANHEMON/H03_CANHEMON/Imagery/Portugal/DMC/ortophotos_22122016/classification_temp",
 fname_MaxEntmodel_r = "samp10_Pb.rdsdata",
 output_dir = "//ies.jrc.it/h03/CANHEMON/H03_CANHEMON/Imagery/Portugal/DMC/ortophotos_22122016/classification_temp",
)

## End(Not run)
## Not run: 
run_sicktree_model_multitile(
 txt_dir = "//ies.jrc.it/h03/CANHEMON/H03_CANHEMON/Imagery/Portugal/DMC/ortophotos_22122016/classification_temp/",
 fname_predictors_txt = "predictors_pt617000_4404000.txt",
 predictors_dir = "//ies.jrc.it/h03/CANHEMON/H03_CANHEMON/Imagery/Portugal/DMC/ortophotos_22122016/RGBN_LUT",
 MaxEntmodel_dir = "//ies.jrc.it/h03/CANHEMON/H03_CANHEMON/Imagery/Portugal/DMC/ortophotos_22122016/classification_temp",
 fname_MaxEntmodel_r = "samp10_Pb.rdsdata",
 output_dir = "//ies.jrc.it/h03/CANHEMON/H03_CANHEMON/Imagery/Portugal/DMC/ortophotos_22122016/classification_temp",
)

## End(Not run)

pieterbeck/CanHeMonR documentation built on May 25, 2019, 7:11 a.m.