In maxikellerbauer/stAirPol: Spatio-temporal Modelling of Air Pollution Data

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

require(RSQLite)
require(stAirPol)
require(data.table)

Here we specify the folder where all data should be saved Also, the time range is specified here

path = '~/data'
start_date = "2017-12-01"
end_date = "2017-12-31"


# (1) Download data: luftdaten.info ---------------------------------------

Download the raw csv files Downloaded files are stored in the subfolder ./luftdaten/ NOTE: That may take some time

dir.create(path)
dir.create(paste0(path, "/luftdaten/"))
LD_download(folder = paste0(path, "/luftdaten/"), start = start_date,
            end = end_date)

Transform the csv files to a useful format, and store them in a SQLite database

dir.create(paste0(path, "/db/"))
LD_sql2(start = start_date, end = end_date,
        source = paste0(path, "/luftdaten/"),
        dbname = paste0(path, "/db/"))
dir.create(paste0(path, "/db/data"))
split_db_in_months(paste0(path, "/db"))
download_sensor_age(path = path)

# (2) Download data: DWD --------------------------------------------------

Download wind and precipitation from the DWD All Information’s are stored in the subfolder ./dwd

dir.create(paste0(path, "/dwd/"))
download_dwd_data(obs = 'wind', path = paste0(path, "/dwd/"))
download_dwd_data(obs = 'precipitation', path = paste0(path, "/dwd/"))
setup_station_table(paste0(path, "/dwd/"))


# (3) Download data: Open Transport Map -----------------------------------
dir.create(paste0(path, "/otm/"))
download_OTM(path = paste0(path, "/otm/"))