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_process_lau_centres.Rmd
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_process_lau_centres.Rmd
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---
title: "Processing population-weighted centres of local administrative units (LAU) in Europe"
description: |
If you need the coordinates of a city, where do you put the centre?
author:
- name: Giorgio Comai
url: https://giorgiocomai.eu
affiliation: OBCT/EDJNet
affiliation_url: https://www.europeandatajournalism.eu/
date: "`r Sys.Date()`"
params:
pop_grid_year: NA
lau_year: NA
power_centre: NA
adjusted: NA
nuts_year: NA
output: github_document
---
## Data processing
```{r setup, include=FALSE}
# options(warn = -1)
process_pop_centre <- TRUE
knitr::opts_chunk$set(echo = TRUE)
library("tidyverse", quietly = TRUE)
library("sf", quietly = TRUE)
library("latlon2map")
library("RSQLite") # for caching
options(timeout = 60000)
cache_folder <- fs::path(fs::path_home_r(), "R", "ll_data")
fs::dir_create(cache_folder)
ll_set_folder(path = cache_folder)
## set db
db <- DBI::dbConnect(
drv = RSQLite::SQLite(),
fs::path(cache_folder, "pop_weighted_centre.sqlite")
)
pop_grid_year <- params$pop_grid_year
lau_year <- params$lau_year
power_centre <- params$power_centre
adjusted = params$adjusted
nuts_year = params$nuts_year
#nuts_year = 2021
adjusted_text <- ifelse(adjusted,
"adjusted_intersection",
"full_intersection")
source("functions.R")
base_folder_by_geo_eu <- fs::path("lau_nuts_concordance_by_geo")
lau_nuts_full_combo_file <- fs::path(base_folder_by_geo_eu,
stringr::str_c(c("lau",
lau_year,
"nuts",
nuts_year,
"concordance_by_geo.csv"),
collapse = "_"))
lau_nuts_combo_df <- readr::read_csv(lau_nuts_full_combo_file,
show_col_types = FALSE)
countries <- unique(lau_nuts_combo_df$country)
current_csv_folder <- fs::path("lau_centres",
paste("lau",
lau_year,
"nuts",
nuts_year,
"pop",
pop_grid_year,
"p",
power_centre,
adjusted_text,
sep = "_"))
fs::dir_create(current_csv_folder)
```
```{r process}
purrr::walk(
.x = countries,
.f = function(current_country) {
current_country_csv <- fs::path(current_csv_folder,
paste0(paste(current_country,
"lau",
lau_year,
"nuts",
nuts_year,
"pop",
pop_grid_year,
"p",
power_centre,
adjusted_text,
sep = "_"),
".csv"))
current_country_lau_sf <- ll_get_lau_eu(silent = TRUE,
year = lau_year) %>%
dplyr::filter(CNTR_CODE == current_country)
if (fs::file_exists(current_country_csv)==FALSE) {
message(paste0("Now processing ",
current_country,
" (",
which(countries %in% current_country),
" of ",
length(countries),
")"))
pop_grid_current_country <- ll_get_population_grid(year = pop_grid_year,
match_country = current_country,
silent = TRUE)
nuts2_current_country <- lau_nuts_combo_df %>%
dplyr::filter(country == current_country) %>%
dplyr::distinct(nuts_2) %>%
dplyr::pull(nuts_2)
current_country_area_file_csv <- fs::path(
"lau_nuts_area",
paste("lau", lau_year, "nuts", nuts_year, "area", sep = "_"),
paste0(current_country, "_lau_nuts_area.csv"))
if (fs::file_exists(current_country_area_file_csv)==FALSE) {
return(NULL)
}
current_country_area_df <- readr::read_csv(current_country_area_file_csv,
show_col_types = FALSE)
current_lau_nuts2_combo_df <- current_country_area_df %>%
dplyr::mutate(nuts_2 = stringr::str_remove(string = nuts_3, pattern = ".{1}$")) %>%
group_by(gisco_id, nuts_2) %>%
dplyr::summarise(area = sum(area), .groups = "drop_last") %>%
group_by(gisco_id) %>%
dplyr::mutate(area_share = area/sum(area)) %>%
dplyr::ungroup() %>%
dplyr::filter(area>0) %>%
dplyr::arrange(gisco_id, nuts_2) %>%
dplyr::group_by(gisco_id) %>%
dplyr::summarise(nuts_combo = paste(nuts_2, collapse = "_")) %>%
dplyr::arrange(nuts_combo)
current_country_nuts_combo <- current_lau_nuts2_combo_df %>%
dplyr::distinct(nuts_combo) %>%
dplyr::pull(nuts_combo)
pb <- progress::progress_bar$new(total = length(current_country_nuts_combo))
pop_centre_by_country_df <- purrr::map_dfr(
.x = current_country_nuts_combo,
.f = function(current_nuts_combo) {
#message(current_nuts_combo)
pb$tick()
current_nuts2 <- stringr::str_split(current_nuts_combo,
pattern = "_",
simplify = TRUE) %>%
as.character()
current_nuts2_sf <- purrr::map_dfr(current_nuts2, function(x) {
ll_get_nuts_eu(nuts_id = x,
resolution = 1,
level = 2,
year = nuts_year,
silent = TRUE)
})
input_grid_sf <- ll_get_population_grid(year = pop_grid_year,
match_sf = current_nuts2_sf,
match_name = current_nuts_combo,
population_grid_sf = pop_grid_current_country,
silent = TRUE)
lau_to_process <- current_lau_nuts2_combo_df %>%
dplyr::filter(nuts_combo == current_nuts_combo) %>%
dplyr::pull(gisco_id)
pop_centre_by_nuts_combo_df <- purrr::map_dfr(
.x =lau_to_process,
.f = function(current_gisco_id) {
# message(current_gisco_id)
current_lau_sf <- ll_get_lau_eu(gisco_id = current_gisco_id,
year = lau_year,
lau_sf = current_country_lau_sf,
silent = TRUE)
valid_lau_l <- sf::st_is_valid(current_lau_sf)
# this check is necessary for the rare invalid lau,
# e.g. NO_4631 in LAU 2020
if (valid_lau_l) {
current_pop_grid_sf <- ll_get_population_grid(
year = pop_grid_year,
match_sf = current_lau_sf,
match_name = stringr::str_c(current_gisco_id,"-",
"lau_", lau_year, "-",
"pop_grid_", pop_grid_year,"-",
"intersects"),
population_grid_sf = input_grid_sf,
join = sf::st_intersects,
silent = TRUE
)
} else {
current_pop_grid_sf <- sf::st_filter(
x = input_grid_sf %>% sf::st_transform(3857),
y = current_lau_sf %>% sf::st_transform(3857),
.predicate = sf::st_intersects
) %>%
sf::st_transform(4326)
}
# for older grid datasets
if (is.element("CNTR_CODE", colnames(current_pop_grid_sf))) {
current_pop_grid_sf <- current_pop_grid_sf %>%
rename(CNTR_ID = CNTR_CODE)
}
# for older grid datasets
if (is.element("TOT_P_2018", colnames(current_pop_grid_sf))) {
current_pop_grid_sf <- current_pop_grid_sf %>%
rename(TOT_P = TOT_P_2018)
}
if (nrow(current_pop_grid_sf)>0&sum(current_pop_grid_sf$TOT_P)>0) {
if (valid_lau_l) {
pop_centre_df <- ll_find_pop_centre(sf_location = current_lau_sf,
sf_population_grid = current_pop_grid_sf,
power = power_centre,
adjusted = adjusted) %>%
sf::st_coordinates() %>%
tibble::as_tibble() %>%
dplyr::transmute(
gisco_id = current_gisco_id,
longitude = as.numeric(X),
latitude = as.numeric(Y)
) %>%
dplyr::left_join(lau_nuts_combo_df, by = "gisco_id") %>%
dplyr::mutate(pop_weighted = TRUE)
} else {
pop_centre_df <- ll_find_pop_centre(sf_location = current_lau_sf %>% sf::st_transform(3857),
sf_population_grid = current_pop_grid_sf %>% sf::st_transform(3857),
power = power_centre,
adjusted = adjusted) %>%
sf::st_coordinates() %>%
tibble::as_tibble() %>%
dplyr::transmute(
gisco_id = current_gisco_id,
longitude = as.numeric(X),
latitude = as.numeric(Y)
) %>%
dplyr::left_join(lau_nuts_combo_df, by = "gisco_id") %>%
dplyr::mutate(pop_weighted = TRUE)
}
pop_centre_df
} else {
pop_centre_df <- sf::st_centroid(current_lau_sf) %>%
sf::st_coordinates() %>%
tibble::as_tibble() %>%
dplyr::transmute(
gisco_id = current_gisco_id,
longitude = as.numeric(X),
latitude = as.numeric(Y)
) %>%
dplyr::left_join(lau_nuts_combo_df, by = "gisco_id") %>%
dplyr::mutate(pop_weighted = FALSE)
pop_centre_df
}
})
pop_centre_by_nuts_combo_df
})
concordance_combo_df <- readr::read_csv(fs::path("lau_nuts_concordance_combo",
stringr::str_c(c("lau",
lau_year,
"nuts",
nuts_year,
"concordance_combo"),
collapse = "_"),
stringr::str_c(c(current_country,
"lau",
lau_year,
"nuts",
nuts_year,
"concordance_combo.csv"),
collapse = "_")),
show_col_types = FALSE)
concordance_combo_df %>%
dplyr::left_join(y = pop_centre_by_country_df %>%
dplyr::arrange(gisco_id) %>%
dplyr::select(gisco_id, longitude, latitude, pop_weighted),
by = "gisco_id") %>%
dplyr::select(gisco_id, longitude, latitude, dplyr::everything()) %>%
readr::write_csv(file = current_country_csv)
}
})
```
```{r}
eu_csv_file <- fs::path("lau_centres",
paste0(paste("lau",
lau_year,
"nuts",
nuts_year,
"pop",
pop_grid_year,
"p",
power_centre,
adjusted_text,
sep = "_"),
".csv"))
if (fs::file_exists(eu_csv_file)==FALSE) {
purrr::map_dfr(.x = fs::dir_ls(path = current_csv_folder),
.f = readr::read_csv, col_types = cols(
gisco_id = col_character(),
longitude = col_double(),
latitude = col_double(),
country = col_character(),
nuts_2 = col_character(),
nuts_3 = col_character(),
lau_id = col_character(),
lau_name = col_character(),
population = col_double(),
area_km2 = col_double(),
year = col_double(),
fid = col_character(),
concordance = col_character(),
pop_weighted = col_logical()
)) %>%
dplyr::arrange(gisco_id) %>%
readr::write_csv(file = eu_csv_file)
}
```