climodr (version 1.0.0)

fin.csv: Final aggregation for CSV-Data

Description

Extract the raster values of all raster layers from a scene at the station coordinates at each time stamp. The extracted data will be attached to the station data so there is a .csv-file with coordinates, sensor data (response values) and extracted raster data (predictor values). The data is ready to be used for modelling.

Usage

fin.csv(
  envrmt = .GlobalEnv$envrmt,
  method = "monthly",
  crs = NULL,
  save_output = TRUE,
  ...
)

Value

List

Arguments

envrmt

variable name of your envrmt list created using climodr's `envi.create` function. Default = envrmt.

method

character. Either "daily", monthly" or "annual". Also depends on the available data.

crs

character. If null, coordinate reference system from project files will be taken. Otherwise data will be reprojected into this crs.

save_output

logical. If cleaned data should be saved permanently in the Environment put save_output = TRUE. Otherwise the output will be saved in the temporary directory. Default: FALSE.

...

arguments passed down from other functions.

See Also

`prep.csv`, `proc.csv`, `spat.csv`, `calc.indices`

Examples

#create climodr environment and allow terra-functions to use 70% of RAM
envrmt <- envi.create(proj_path = tempdir(),
                      memfrac = 0.7)

# Load the climodr example data into the current climodr environment
clim.sample(envrmt = envrmt)

#prepare csv-files
prep.csv(envrmt = envrmt,
         method = "proc",
         save_output = TRUE)

#process csv-files
csv_data <- proc.csv(envrmt = envrmt,
                     method = "monthly",
                     rbind = TRUE,
                     save_output = TRUE)

# Crop all raster bands
crop.all(envrmt = envrmt,
         method = "MB_Timeseries",
         overwrite = TRUE)

# Calculate Indices from cropped raster bands
calc.indices(envrmt = envrmt,
             vi = "all",
             bands = c("blue", "green", "red",
                       "nir", "nirb",
                       "re1", "re2", "re3",
                       "swir1", "swir2"),
             overwrite = TRUE)

#extract station coordinates
csv_spat <- spat.csv(envrmt = envrmt,
                     method = "monthly",
                     des_file = "plot_description.csv",
                     save_output = TRUE)


#extract predictor values from raster files
csv_fin <- fin.csv(envrmt = envrmt,
                   method = "monthly",
                   save_output = TRUE)
head(csv_fin)