sampling: Example Data: input table of values and rasters to downscale

In jasonleebrown/machisplin: Interpolation of noisy multi-variate data using machine learning ensembling

Example Data: input table of values and rasters to downscale

Description

Example Data: input table of values and rasters to downscale

Usage

data(sampling)

Format

An data frame with 813 rows and 4 variables (oordinates named exactly as 'long' and 'lat') and two layers to downscale:

long

longitude

#long,lat,bio_1,bio_12

lat

latittude

var1

bio_1

var2

bio_12

Examples

library(machisplin)
library(raster)

##load spatial data with (coordinates named exactly as 'long' and 'lat') and any number of layers to downscale
data(sampling)

## load environmental variables for all sites of the study area 2 (env2). Column names should be x,y,X1,X2,...,Xn)

ALT = raster(system.file("extdata", "alt.tif", package="machisplin"))

SLOPE = raster(system.file("extdata", "slope.tif", package="machisplin"))

TWI = raster(system.file("extdata", "TWI.tif", package="machisplin"))

##function input: raster stack of covariates
raster_stack<-stack(ALT,SLOPE,TWI)

jasonleebrown/machisplin documentation built on Jan. 2, 2023, 3:08 a.m.