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climodr

Create good quality climate models in an easy to use workflow. Newbie or Expert in climate modelling? This package suits all skill levels.

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Documentation

Getting Started

This website is intended to provide additional information for the climodr package, although the provided introductions, explanations and examples might be u...

Recommendations

To run climodr, you need a PC with a running version of R. Using an Interface like R-Studio is also strongly recomended.

Frequently Asked Questions

No Frequently Asked Questions yet.

Overview

The Environment in climodr serves as a method to setup the same workspace for every usecase of climodr. The idea of this is to make climodr easy to share and...

envi.create

With the envi.create() function, one points out a path where the package should store all its data. There is also the memfrac argument. This argument allows...

clim.sample

Load example data Description Climodr comes with a full set of example data. But since this package runs primarily with data, that is not linked to the glob...

Overview

The Pre-Processing phase cleans up your data, creates additional information like spectral indices and makes the data ready for spatial modelling.

prep.csv

Preparing CSV-Data Description Crops input data to the extent size and removes NA-Values Usage prep.csv(method = "proc", save_output = TRUE, ...) Argumen...

proc.csv

Processing CSV-Data Description Calculate averaged sensor values aggregated to a given time interval. Usage proc.csv(method = "monthly", rbind = TRUE, save...

spat.csv

Spatial aggregation for CSV-Data Description Extract station coordinates from meta-data and reproject the coordinates to the project coordinate reference sy...

crop.all

Cropping tiff data Description Crops input data to the extent size and reprojects them into project Coordinate reference system. Usage crop.all( method =...

calc.indices

Calculate spectral indices Description Calculates a set of spectral indices to have more predictor variables available when further modeling. Usage calc.in...

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 e...

Overview

This chapter contains the core function of climodr, its model function. You also find a function for finding autocorrelations in your data pre modelling and ...

autocorr

Test for Autocorrelation Description Tests the final.csv created with ‘fin.csv’ on autocorrelation to produce reliable models. Usage autocorr( method = "...

calc.model

Modelling Description Creates Models for each climate value Usage calc.model( method = "monthly", timespan, climresp, classifier = c("rf", "pls", "...

climpred

Predict sensor data area wide Description Use the models created using ‘calc.model’ to predict the modeled data onto a full spatial raster scene. Usage cli...

Overview

The final chapter of climodr will show you how to create ready to use climate maps using the climodr package.

climplot

Create Maps using the ‘terra’ package graphic parameters Description Plot results of climodr into maps. Right now maps are created using the terra package. ...