From f458a84beb97bcbb6b2c42fb6bb3a33342beb460 Mon Sep 17 00:00:00 2001 From: "Jentsch, Helge Marc Ole" <helge.marc.ole.jentsch@uni-hamburg.de> Date: Wed, 24 Mar 2021 15:26:52 +0000 Subject: [PATCH] Update README.md --- README.md | 87 ++++++++++++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 86 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 27278aa..5105ae1 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ ## Welcome to the help-page of ClimDatDownloadR -To get started please proceed [here](./articles/ClimDatDownloadR.html). +To get started please proceed [here](./README.md#a-warm-welcome). _This R-package was developed as a student project for the masters programm Geography at the Universität Hamburg, Germany._ @@ -21,3 +21,88 @@ I would appreciate your feedback and possible bug reports. If you find anything, please send an email to [helge.marc.ole.jentsch@uni-hamburg.de](<mailto:helge.marc.ole.jentsch@uni-hamburg.de>) Thank you very much for using ClimDatDownloadR! + +## A warm welcome +Hello and welcome to the ClimDatDownloadR R-package. + +With this package **cli**mate **dat**asets provided by [Chelsa](http://chelsa-climate.org/) and [WorldClim](https://www.worldclim.org/) can be automatically **download**ed, clipped, and converted with **R**. + +To start, you'll have to install the package and it's dependencies first, if not already done. Then you can activate the package with the `library`-function. + +```{r setup} +# install.packages(c("gdalUtils", "httr", "ncdf4", "qpdf", "raster", "RCurl", "RefManageR", "rgdal", "stringr", "sf", "sp", "svMisc", "utils"), dependencies = TRUE) +# install.packages("https://gitlab.rrz.uni-hamburg.de/helgejentsch/climdatdownloadr/-/archive/master/climdatdownloadr-master.tar.gz", repos = NULL, type = "source") +library(ClimDatDownloadR) +``` +Very well, now that you have the package installed and attached, let's start with the data sets of the climatologies of Chelsa and WorldClim. + +## Download Climatologies +In the help pages of [Chelsa.Clim.download()](../man/Chelsa.Clim.download.Rd) and [WorldClim.HistClim.download()](../man/WorldClim.HistClim.download.Rd) you can find further information about the handling of these functions. In fact running the functions all by itself bulk-downloads all the climatology data sets from the servers to your current working directory. + +Let's start with a example of the Chelsa climatologies: +``` +Chelsa.Clim.download( + # first you'll have to choose your working directory + # don't worry about having a directory for every parameter you want to download + # ClimDatDownloadR sorts this out for you + save.location = "./", + # now you'll have to choose parameters. + # since there is the possibility to download more than one data set + # the parameters must be a string-vector input. + # Single parameters, however, can be just put in as a string. + # the valid parameter inputs can be found in the help (linked s.o.) + parameter = c("temp", "bio"), + # Now, since you chose "temp" and "bio" as input parameters, + # you can specify the months and bioclim-variables to download. + # If you want all of them, just leave the default values. + # It is crutial, however, that the inputs are integer number values. + month.var = c(1), # Here January was chosen to be downloaded for demonstration purposes + bio.var = c(1), # Here the first bioclim-variable was chosen to be downloaded for demonstration purposes + # For Chelsa a newer Version of their climatologies was published in 2019. + # They still got their old version still hosted on their website. + # So you can download it as well, if you want to reproduce some research you base your studies on. + version.var = "1.2", # Here the newer version is chosen + # Now you can choose whether you want the data set clipped + clipping = TRUE, # Here TRUE was chosen to show a basic introduction to the function + # Since "clipping" is enganged now you can specify the extent you want to have for your analysis + # This is possible via the parameters "clip.shapefile", "clip.extent", and "buffer" + clip.extent = c(-9,20,35,80), # Here the extent for Europe was used ... + buffer = 5, # ... with a 5 arc-degree buffer. + # Now, since some might prefer older file formats there is a possibility to convert + # clipped files and raw data into ESRI-ASCII format + convert.files.to.asc = FALSE, + # now you can stack the data ... + stacking.data = FALSE, + # ... and choose if you want to combine the raw data in a .zip-file ... + combine.raw.zip = FALSE, + # and whether raw data should be deleted. + delete.raw.data = FALSE, + # Finally you are presented with the option to save a bibliography file at the save location. + save.bib.file = TRUE +) +``` +___ +With this showing the basic principle of these functions, here is a example of a WorldClim climatology download: +``` +WorldClim.HistClim.download( + # As you can see, the structure of this function is very similar to the Chelsa-function + save.location = "./", + parameter = c("temp", "bio"), + month.var = c(1), + bio.var = c(1), + # Here the resolution of the downloaded data set must be added + # If no input is given all resolutions will be downloaded + resolution = "10m", # here 10 arc-minutes are chosen + # WorldClim also recently had an update to version 2.1 + version.var = "2.1", # Here the newer version is chosen + clipping = TRUE, + clip.extent = c(-9,20,35,80), + buffer = 5, + convert.files.to.asc = FALSE, + stacking.data = FALSE, + # here you can choose if you want to keep the downloaded zip-file + keep.raw.zip = FALSE, + delete.raw.data = FALSE, + save.bib.file = TRUE +) +``` -- GitLab