bavDC: Bavarian Data Cube
Installation
You can install bavDC from github with:
# Install remotes if not available
if(!"remotes" %in% installed.packages()[,"Package"]) install.packages("remotes")
# Install baVDC package from Github
remotes::install_github("RS-eco/bavDC", build_vignettes = T)
If package installation with install_github()
fails, try this as an
alternative:
tmp_zip <- tempfile(fileext = ".zip")
source_url <- "https://api.github.com/repos/RS-eco/bavDC/zipball/main"
utils::download.file(source_url, destfile=tmp_zip, method="wget")
file.exists(tmp_zip)
remotes::install_local(tmp_zip)
After installation, simply load the bavDC
package:
library(bavDC)
If you encounter a bug or if you have any problems, please file an issue on Github.
Shiny app
You can start the baVDC Shiny app, by:
library(shiny)
runApp()
Please note: The app currently only supports the alt_bavtk4tel
dataset.
Datasets
The individual datasets can then be loaded, by:
# Elevation & Terrain (SRTM)
data("alt_bav_tk4tel")
# Outline of Bavaria (GADM)
data("bavaria")
# BayWRF monthly climate data
load(system.file("extdata", "baywrf_pr_bav.rda", package = "bavDC"))
load(system.file("extdata", "baywrf_tas_bav.rda", package = "bavDC"))
load(system.file("extdata", "baywrf_tasmin_bav.rda", package = "bavDC"))
load(system.file("extdata", "baywrf_tasmax_bav.rda", package = "bavDC"))
# BioTime data for Germany
data("biotime_deu")
# BirdLife, IUCN and GARD range data
data("amphibians_bav")
data("bird_bav")
data("gard_reptiles_bav")
load(system.file("extdata", "mammals_bav.rda", package = "bavDC"))
data("odonata_bav")
data("reptiles_bav")
# Bird range data from the LFU
data("bird_bva_shape") # sf-object
data("bird_bva_shape_tk4tel") #gridded
# Bird and Odonata Atlas data
data("aves_tk4tel")
data("odonata_tk4tel")
# Carbon stock data
data("carbon_bav")
# CCI land cover data
data("cci_bav_tk4tel")
# Chelsa climate data
data("chelsa_bav_tk4tel")
# Euro-cordex climate simulations
data("cordex_bioclim_bav_tk4tel")
data("cordex_bioclim_bav")
load(system.file("extdata", "cordex_prAdjust_bav.rda", package = "bavDC"))
load(system.file("extdata", "cordex_tasminAdjust_bav.rda", package = "bavDC"))
load(system.file("extdata", "cordex_tasmaxAdjust_bav.rda", package = "bavDC"))
#The analysis of all monthly Euro-Cordex climate scenarios can be found here: https://raw.githubusercontent.com/RS-eco/bavDC/main/vignettes/bavaria-eurocordex.html
#And the corresponding .Rmd-file is available from here: https://raw.githubusercontent.com/RS-eco/bavDC/main/vignettes/bavaria-eurocordex.Rmd
# Corine land-cover and land cover change
data("corine_cha_bav_tk4tel") # Land-cover change
data("corine_cha_bav")
data("corine_cha_perc_bav")
data("corine_lc_bav_tk4tel") # Land cover
data("corine_lc_bav") # Corine Land cover data at 100 x 100 m resolution
data("corine_lc_perc_bav") # Corine land cover percentage data at 1 x 1 km resolution
# Gridded population data for Bavaria at 1km resolution
data("bav_pop_1km")
# Diva shapefiles for Germany
data("diva_cover_deu") # Land-cover data
data("diva_pop_deu") # Population data
data("diva_rails_deu") # Railway tracks
data("diva_roads_deu") # Roads
data("diva_water_areas_deu") # Lakes
data("diva_water_lines_deu") # Rivers
# DWD climate data
data("dwd_annual_ts_bav") # Annual time series data of whole of Bavaria
load(system.file("extdata", "dwd_yearmon_rsms_bav_tk4tel.rda", package = "bavDC")) # Gridded monthly climate data
load(system.file("extdata", "dwd_yearmon_tadnmm_bav_tk4tel.rda", package = "bavDC"))
load(system.file("extdata", "dwd_yearmon_tadxmm_bav_tk4tel.rda", package = "bavDC"))
load(system.file("extdata", "dwd_yearmon_tamm_bav_tk4tel.rda", package = "bavDC"))
# E-OBS observed climate data
data("e-obs_elev_ens_0.1deg_bav")
data("e-obs_rr_ens_mean_0.1deg_bav_yearmon")
data("e-obs_rr_ens_spread_0.1deg_bav_yearmon")
data("e-obs_tg_ens_mean_0.1deg_bav_yearmon")
data("e-obs_tg_ens_spread_0.1deg_bav_yearmon")
data("e-obs_tn_ens_mean_0.1deg_bav_yearmon")
data("e-obs_tn_ens_spread_0.1deg_bav_yearmon")
data("e-obs_tx_ens_mean_0.1deg_bav_yearmon")
data("e-obs_tx_ens_spread_0.1deg_bav_yearmon")
# EBCC data of Bavaria
data("ebcc_bav")
# EU-DEM elevation & hillshade data
data("eu_dem_bav_500m")
data("hillshade_bav_500m")
# EuroLST Land surface temperature
data("eurolst_bav_tk4tel")
# EWEMBI daily temperature and precipitation
data("ewembi_bav")
# EWEMBI daily temperature and precipitation data for the whole of Germany can be extracted from the processNC package (https://github.com/RS-eco/processNC)
# List daily temperature files for Germany from 1979 till 2016
ewembi_tas_ger <- list.files(paste0(system.file(package="processNC"), "/extdata"),
pattern="tas.*\\.nc", full.names=T)
# List daily precipitation files for Germany from 1979 till 2016
ewembi_pr_ger <- list.files(paste0(system.file(package="processNC"), "/extdata"),
pattern="tas.*\\.nc", full.names=T)
# Forest disturbance data
data("forest_disturbance_bav_300m")
# GIMMS3g NDVI data
data("gimms3g_v0_bav")
data("gimms3g_v1_bav")
# Globcover land cover
data("globcover_bav_tk4tel")
# Human footprint
data("hfp_1993_v3_bav")
data("hfp_2009_v3_bav")
# Important bird areas
data("iba_bav")
# ISIMIP2b climate and land-use
data("isimip_bio_bav_tk4tel")
data("isimip_lu_bav_tk4tel")
# KK09, KK10 data
data("kk09_bav")
data("kk10_bav")
# Lakes & Rivers
data("lakes_points_bav")
data("lakes_poly_bav")
data("rivers_bav")
# Landsystem data
data("landsystem_bav_tk4tel")
data("landsystem_bav")
data("landsystem_perc_bav_tk4tel")
data("landsystem_perc_bav")
# Merraclim climate
data("merraclim_2.5m_bav_tk4tel")
data("merraclim_5m_bav_tk4tel")
data("merraclim_10m_bav_tk4tel")
# MODIS land-cover
data("modis_lc_bav_tk4tel")
# MODIS Land surface temperature
data("modis_lst_bav_tk4tel")
# Naturraeume (from large to small)
data("ng_geo")
data("ng_gross")
data("ng_ssymank")
data("ng_meynen_schmit")
data("ng_unter_absp")
data("ng_abspziele")
# Protected areas
data("dist_pa_bav_tk4tel")
load(system.file("extdata", "pa_bav.rda", package = "bavDC"))
data("pa_bav_tk4tel")
# Plot coordinates
data("plot_coords_bav")
# Potential natural vegetation
data("pnv_bav")
# Predicts data
data("predicts_deu")
# Standardized taxonomy
data("taxonomyStd")
# Tandem-X Forest/Non-forest
data("tdm_fnf_bav")
# TK25 grid
data("tk4tel_db")
data("tk4tel_grid")
data("tk25_grid")
# Worldclim v1.4
data("wc1.4_10m_bav_tk4tel")
data("wc1.4_2.5m_bav_tk4tel")
data("wc1.4_30s_bav_tk4tel")
data("wc1.4_5m_bav_tk4tel")
# Worldclim v2.0
data("wc2.0_10m_bav_tk4tel")
data("wc2.0_2.5m_bav_tk4tel")
data("wc2.0_30s_bav_tk4tel")
data("wc2.0_5m_bav_tk4tel")
# WFDE5 re-analysis climate data (0.5°)
data("wfde5_rainf_bav")
data("wfde5_snowf_bav")
data("wfde5_tair_bav")
Note: The code of how the datasets were created can be found in the data-raw folder.
Note: Climate, land-use and species data for the whole of Europe can be found in the edc package.