R/convertNaturalEarthAdm1.R
In MazamaScience/MazamaSpatialUtils: Spatial Data Download and Utility Functions
Defines functions
convertNaturalEarthAdm1
Documented in
convertNaturalEarthAdm1
#' @importFrom rlang .data
#' @export
#'
#' @title Convert Level 1 (state) borders shapefile
#'
#' @description Returns a simple features data frame for 1st level administrative divisions
#'
#' The full resolution file will be named "NaturalEarthAdm1.rda". In addition,
#' "_05", _02" and "_01" versions of the file will be created that that are
#' simplified to 5\%, 2\% and 1\%. Simplified versions will greatly improve the
#' speed of both searching and plotting.
#'
#' @details A state border shapefile is downloaded and converted to a
#' simple features data frame with additional columns of data. The resulting file
#' will be created in the spatial data directory which is set with
#' \code{setSpatialDataDir()}. The resulting file
#' will be created in this same spatial data directory.
#'
#' Within the \pkg{MazamaSpatialUtils} package the phrase 'state' refers to
#' administrative divisions beneath the level of the country or nation. This
#' makes sense in the United 'States'. In other countries this level is known as
#' 'province', 'territory' or some other term.
#'
#'
#' @references https://www.naturalearthdata.com
convertNaturalEarthAdm1 <- function() {
# ----- Setup ----------------------------------------------------------------
# Use package internal data directory
dataDir <- getSpatialDataDir()
# Specify the name of the dataset and file being created
datasetName <- 'NaturalEarthAdm1'
# ----- Get the data ---------------------------------------------------------
# Build appropriate request URL
url <- 'http://www.naturalearthdata.com/http//www.naturalearthdata.com/download/10m/cultural/ne_10m_admin_1_states_provinces.zip'
filePath <- file.path(dataDir, basename(url))
utils::download.file(url, filePath)
# NOTE: This zip file has no directory so extra subdirectory needs to be created
utils::unzip(filePath, exdir = file.path(dataDir, 'adm'))
# ----- Convert to SFDF ------------------------------------------------------
# Convert shapefile into simple features data frame
# NOTE: The 'adm' directory has been created
dsnPath <- file.path(dataDir, 'adm')
shpName <- 'ne_10m_admin_1_states_provinces'
SFDF <- convertLayer(
dsn = dsnPath,
layer = shpName
)
# ----- Select useful columns and rename -------------------------------------
# > dplyr::glimpse(SFDF, width = 75)
# Rows: 4,596
# Columns: 122
# $ featurecla <chr> "Admin-1 states provinces", "Admin-1 states provinces"…
# $ scalerank <int> 3, 6, 2, 6, 3, 4, 4, 3, 4, 3, 4, 3, 3, 10, 9, 2, 2, 2,…
# $ adm1_code <chr> "ARG-1309", "URY-8", "IDN-1185", "MYS-1186", "CHL-2694…
# $ diss_me <int> 1309, 8, 1185, 1186, 2694, 1936, 1937, 2693, 1939, 269…
# $ iso_3166_2 <chr> "AR-E", "UY-PA", "ID-KI", "MY-12", "CL-AP", "BO-L", "B…
# $ wikipedia <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ iso_a2 <chr> "AR", "UY", "ID", "MY", "CL", "BO", "BO", "CL", "BO", …
# $ adm0_sr <int> 1, 1, 5, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, …
# $ name <chr> "Entre Ríos", "Paysandú", "Kalimantan Timur", "Sabah",…
# $ name_alt <chr> "Entre-Rios", NA, "Kaltim", "North Borneo", NA, NA, NA…
# $ name_local <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ type <chr> "Provincia", "Departamento", "Propinsi", "State", "Reg…
# $ type_en <chr> "Province", "Department", "Province", "State", "Region…
# $ code_local <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ code_hasc <chr> "AR.ER", "UY.PA", "ID.KI", "MY.SA", "CL.AP", "BO.LP", …
# $ note <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ hasc_maybe <chr> NA, NA, NA, NA, NA, NA, NA, NA, "BO.OR|BOL-POT", NA, "…
# $ region <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ region_cod <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ provnum_ne <int> 10, 19, 15, 1, 0, 8, 7, 0, 1, 20006, 8, 22, 5, 0, 0, N…
# $ gadm_level <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, …
# $ check_me <int> 20, 0, 20, 20, 20, 0, 0, 20, 10, 20, 10, 20, 20, 20, 2…
# $ datarank <int> 3, 8, 1, 6, 3, 8, 6, 3, 6, 3, 5, 3, 3, 10, 8, 1, 1, 1,…
# $ abbrev <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ postal <chr> "ER", "PA", "KI", "SA", NA, "LP", "OR", "TA", "PO", "A…
# $ area_sqkm <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, 0, 0,…
# $ sameascity <int> -99, -99, -99, -99, 7, 6, 6, -99, -99, 6, 7, 6, -99, -…
# $ labelrank <int> 3, 6, 2, 6, 7, 6, 6, 3, 4, 6, 7, 6, 3, 20, 9, 2, 2, 2,…
# $ name_len <int> 10, 8, 16, 5, 18, 6, 5, 8, 6, 11, 5, 5, 5, 8, 7, 6, 8,…
# $ mapcolor9 <int> 3, 2, 6, 3, 5, 2, 2, 5, 2, 5, 4, 3, 3, 6, 3, 2, 4, 4, …
# $ mapcolor13 <int> 13, 10, 11, 6, 9, 3, 3, 9, 3, 9, 11, 13, 13, 3, 7, 2, …
# $ fips <chr> "AR08", "UY11", "ID14", "MY16", NA, "BL04", "BL05", "C…
# $ fips_alt <chr> NA, NA, NA, NA, NA, NA, NA, NA, "BL05", NA, "PE18", NA…
# $ woe_id <int> 2344682, 2347650, 2345723, 2346310, 56043702, 2344804,…
# $ woe_label <chr> "Entre Rios, AR, Argentina", "Paysandú, UY, Uruguay",…
# $ woe_name <chr> "Entre Ríos", "Paysandú", "Kalimantan Timur", "Sabah",…
# $ latitude <dbl> -32.02750, -32.09330, 1.28915, 5.31115, -18.32070, -14…
# $ longitude <dbl> -59.28240, -57.22400, 116.35400, 117.09500, -69.68040,…
# $ sov_a3 <chr> "ARG", "URY", "IDN", "MYS", "CHL", "BOL", "BOL", "CHL"…
# $ adm0_a3 <chr> "ARG", "URY", "IDN", "MYS", "CHL", "BOL", "BOL", "CHL"…
# $ adm0_label <int> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 2, 2, 2, 2, …
# $ admin <chr> "Argentina", "Uruguay", "Indonesia", "Malaysia", "Chil…
# $ geonunit <chr> "Argentina", "Uruguay", "Indonesia", "Malaysia", "Chil…
# $ gu_a3 <chr> "ARG", "URY", "IDN", "MYS", "CHL", "BOL", "BOL", "CHL"…
# $ gn_id <int> 3434137, 3441242, 1641897, 1733039, 6693562, 3911924, …
# $ gn_name <chr> "Provincia de Entre Rios", "Departamento de Paysandu",…
# $ gns_id <int> -988655, -908097, -2680740, -2405166, 10749159, -69341…
# $ gns_name <chr> "Entre Rios", "Paysandu, Departamento de", "Kalimantan…
# $ gn_level <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, NA, 1, 1,…
# $ gn_region <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ gn_a1_code <chr> "AR.08", "UY.11", "ID.14", "MY.16", "CL.16", "BO.04", …
# $ region_sub <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ sub_code <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ gns_level <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, NA, 1, 1,…
# $ gns_lang <chr> "khm", "fra", "ind", "fil", "ara", "kor", "kor", "fra"…
# $ gns_adm1 <chr> "AR08", "UY11", "ID14", "MY16", "CI16", "BL04", "BL05"…
# $ gns_region <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ min_label <dbl> 6.0, 8.0, 5.0, 7.0, 6.0, 6.6, 6.6, 6.0, 6.6, 6.0, 6.6,…
# $ max_label <dbl> 11.0, 11.0, 10.1, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, …
# $ min_zoom <dbl> 6.0, 8.0, 4.6, 7.0, 6.0, 6.6, 6.6, 6.0, 6.6, 6.0, 6.6,…
# $ wikidataid <chr> "Q44762", "Q16576", "Q3899", "Q179029", "Q2109", "Q272…
# $ name_ar <chr> "إنتري ريوس", "إدارة بايساندو", "كالمنتان الشرقية", "ص…
# $ name_bn <chr> "এন্ত্রে রিও প্রদেশ", "পেসান্ডো বিভাগ", "পূর্ব কালিমান্তান", …
# $ name_de <chr> "Entre Ríos", "Paysandú", "Ostkalimantan", "Sabah", "A…
# $ name_en <chr> "Entre Ríos", "Paysandú", "East Kalimantan", "Sabah", …
# $ name_es <chr> "Entre Ríos", "Paysandú", "Kalimantan Oriental", "Saba…
# $ name_fr <chr> "Entre Ríos", "Paysandú", "Kalimantan oriental", "Saba…
# $ name_el <chr> "Έντρε Ρίος", "Παϊσαντού", "Ανατολικό Καλιμαντάν", "Σα…
# $ name_hi <chr> "एन्ट्रे रियोस", "पयसंदु विभाग", "पूर्व कालिमंतान", "साबाह राज्…
# $ name_hu <chr> "Entre Ríos", "Paysandú", "Kelet-Kalimantan", "Sabah",…
# $ name_id <chr> "Entre Ríos", "Departemen Paysandú", "Kalimantan Timur…
# $ name_it <chr> "Entre Ríos", "dipartimento di Paysandú", "Kalimantan …
# $ name_ja <chr> "エントレ・リオス州", "パイサンドゥ県", "東カリマンタ…
# $ name_ko <chr> "엔트레리오스", "파이산두", "동칼리만탄", "사바", "아…
# $ name_nl <chr> "Entre Ríos", "Paysandú", "Oost-Kalimantan", "Sabah", …
# $ name_pl <chr> "Entre Ríos", "Paysandú", "Borneo Wschodnie", "Sabah",…
# $ name_pt <chr> "Entre Ríos", "Paysandú", "Kalimantan Oriental", "Sabá…
# $ name_ru <chr> "Энтре-Риос", "Пайсанду", "Восточный Калимантан", "Саб…
# $ name_sv <chr> "Entre Ríos", "Paysandú", "Kalimantan Timur", "Sabah",…
# $ name_tr <chr> "Entre Ríos eyaleti", "Paysandu Departmanı", "Doğu Kal…
# $ name_vi <chr> "Entre Ríos", "Paysandú", "Đông Kalimantan", "Sabah", …
# $ name_zh <chr> "恩特雷里奥斯省", "派桑杜省", "东加里曼丹省", "沙巴", …
# $ ne_id <dbl> 1159309789, 1159307733, 1159310009, 1159310033, 115931…
# $ name_he <chr> "אנטרה ריוס", "פאיסאנדו", "מזרח קלימנטאן", "סבה", "ארי…
# $ name_uk <chr> "Ентре-Ріос", "Пайсанду", "Східний Калімантан", "Сабах…
# $ name_ur <chr> "صوبہ انترے ریوس", "پایساندو محکمہ", "مشرقی کالیمانتان…
# $ name_fa <chr> "ایالت انتره ریوز", "بخش پایساندو", "کالیمانتان شرقی",…
# $ name_zht <chr> "恩特雷里奥斯省", "派桑杜省", "東加里曼丹省", "沙巴", …
# $ FCLASS_ISO <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_US <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_FR <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_RU <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_ES <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_CN <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_TW <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_IN <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_NP <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_PK <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_DE <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_GB <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_BR <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_IL <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_PS <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_SA <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_EG <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_MA <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_PT <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_AR <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_JP <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_KO <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_VN <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_TR <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_ID <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_PL <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_GR <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_IT <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_NL <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_SE <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_BD <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_UA <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_TLC <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ geometry <MULTIPOLYGON [°]> MULTIPOLYGON (((-58.20011 -..., MULTIPOLY…
# Data Dictionary:
# featurecla --> (drop)
# scalerank ---> (drop)
# adm1_code ---> adm1_code: Unique identifier
# diss_me -----> (drop)
# iso_3166_2 --> (drop)
# wikipedia ---> (drop)
# iso_a2 ------> countryCode: 2-character country code
# adm0_sr -----> (drop)
# name --------> stateName: Native language name
# name_alt ----> (drop)
# name_local --> (drop)
# type --------> (drop)
# type_en -----> (drop)
# code_local --> (drop)
# code_hasc ---> code_hasc: HASC code
# note --------> (drop)
# hasc_maybe --> (drop)
# region ------> (drop)
# region_cod --> (drop)
# provnum_ne --> (drop)
# gadm_level --> (drop)
# check_me ----> (drop)
# datarank ----> (drop)
# abbrev ------> (drop)
# postal ------> postal: country FIPS code
# area_sqkm ---> area_sqkm: area in square kilometers
# sameascity --> (drop)
# labelrank ---> (drop)
# name_len ----> (drop)
# mapcolor9 ---> (drop)
# mapcolor13 --> (drop)
# fips --------> stateFIPS: FIPS code
# fips_alt ----> (drop)
# woe_id ------> (drop)
# woe_label ---> (drop)
# woe_name ----> (drop)
# latitude ----> latitude: latitude coordinate
# longitude ---> longitude: longitude coordinate
# sov_a3 ------> (drop)
# adm0_a3 -----> (drop)
# adm0_label --> (drop)
# admin -------> (drop)
# geounit -----> (drop)
# gu_a3 -------> (drop)
# gn_id -------> (drop)
# gn_name -----> (drop)
# gns_id ------> (drop)
# gns_name ----> (drop)
# gn_level ----> (drop)
# gn_region ---> (drop)
# gn_a1_code --> (drop)
# region_sub --> (drop)
# sub_code ----> (drop)
# gns_level ---> (drop)
# gns_lang ----> gns_lang: ISO 639-3 language identifier
# gns_adm1 ----> gns_adm1: adm1 identifier
# gns_reigon --> (drop)
# min_label ---> (drop)
# max_label ---> (drop)
# min_zoom ----> (drop)
# wikidataid --> (drop)
# name_* ------> (drop)
# ne_id -------> (drop)
# FCLASS* ----->
# NOTE: Subset to filter out exceptional areas (islands and disputed
# NOTE: territories) marked with '~'
goodAreas <- stringr::str_subset(SFDF$code_hasc, "~", negate = TRUE)
SFDF <-
SFDF %>%
dplyr::filter(.data$code_hasc %in% goodAreas)
# Add the core identifiers to the simple features data frame
SFDF$stateCode <-
SFDF$code_hasc %>%
stringr::str_trim() %>%
stringr::str_sub(4,-1)
SFDF$countryName <- MazamaSpatialUtils::codeToCountry(SFDF$iso_a2)
SFDF$stateName <- SFDF$name
SFDF$stateFIPS <- SFDF$fips
# Create the new dataframe in a specific column order
SFDF <-
SFDF %>%
dplyr::select(
countryCode = .data$iso_a2,
countryName = .data$countryName,
stateCode = .data$stateCode,
stateName = .data$name,
stateFIPS = .data$stateFIPS,
latitude = .data$latitude,
longitude = .data$longitude,
area_sqkm = .data$area_sqkm,
postal = .data$postal,
adm1_code = .data$adm1_code,
code_hasc = .data$code_hasc,
gns_lang = .data$gns_lang,
gns_adm1 = .data$gns_adm1
)
# ----- Simplify and save ----------------------------------------------------
uniqueIdentifier <- "adm1_code"
simplifyAndSave(
SFDF = SFDF,
datasetName = datasetName,
uniqueIdentifier = uniqueIdentifier,
dataDir = dataDir
)
# ----- Clean up and return --------------------------------------------------
# Clean up
unlink(filePath, force = TRUE)
unlink(dsnPath, recursive = TRUE, force = TRUE)
return(invisible(datasetName))
}
# ===== TEST ===================================================================
if ( FALSE ) {
library(sf)
# Look or horizontal lines from polygons that cross the dateline.
# NOTE: These are sometimes created by sf::st_make_valid()
loadSpatialData(datasetName)
SFDF <- get(paste0(datasetName, ""))
SFDF_05 <- get(paste0(datasetName, "_05"))
SFDF_02 <- get(paste0(datasetName, "_02"))
SFDF_01 <- get(paste0(datasetName, "_01"))
plot(SFDF_01$geometry)
dev.off(dev.list()["RStudioGD"])
plot(SFDF_02$geometry)
dev.off(dev.list()["RStudioGD"])
plot(SFDF_05$geometry)
dev.off(dev.list()["RStudioGD"])
#plot(SFDF$geometry)
# Try out getSpatialData()
lons <- c(-120:-110, 0:10)
lats <- c(30:40, 30:40)
df <- getSpatialData(lons, lats, SFDF_01)
df <- getSpatialData(lons, lats, SFDF_02)
df <- getSpatialData(lons, lats, SFDF_05)
df <- getSpatialData(lons, lats, SFDF)
# Special Case of Russian failing to plot properly
SFDF %>% dplyr::filter(countryCode == "RU") %>% sf::st_geometry() %>% plot()
}
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Defines functions convertNaturalEarthAdm1
Documented in convertNaturalEarthAdm1
#' @importFrom rlang .data
#' @export
#'
#' @title Convert Level 1 (state) borders shapefile
#'
#' @description Returns a simple features data frame for 1st level administrative divisions
#'
#' The full resolution file will be named "NaturalEarthAdm1.rda". In addition,
#' "_05", _02" and "_01" versions of the file will be created that that are
#' simplified to 5\%, 2\% and 1\%. Simplified versions will greatly improve the
#' speed of both searching and plotting.
#'
#' @details A state border shapefile is downloaded and converted to a
#' simple features data frame with additional columns of data. The resulting file
#' will be created in the spatial data directory which is set with
#' \code{setSpatialDataDir()}. The resulting file
#' will be created in this same spatial data directory.
#'
#' Within the \pkg{MazamaSpatialUtils} package the phrase 'state' refers to
#' administrative divisions beneath the level of the country or nation. This
#' makes sense in the United 'States'. In other countries this level is known as
#' 'province', 'territory' or some other term.
#'
#'
#' @references https://www.naturalearthdata.com
convertNaturalEarthAdm1 <- function() {
# ----- Setup ----------------------------------------------------------------
# Use package internal data directory
dataDir <- getSpatialDataDir()
# Specify the name of the dataset and file being created
datasetName <- 'NaturalEarthAdm1'
# ----- Get the data ---------------------------------------------------------
# Build appropriate request URL
url <- 'http://www.naturalearthdata.com/http//www.naturalearthdata.com/download/10m/cultural/ne_10m_admin_1_states_provinces.zip'
filePath <- file.path(dataDir, basename(url))
utils::download.file(url, filePath)
# NOTE: This zip file has no directory so extra subdirectory needs to be created
utils::unzip(filePath, exdir = file.path(dataDir, 'adm'))
# ----- Convert to SFDF ------------------------------------------------------
# Convert shapefile into simple features data frame
# NOTE: The 'adm' directory has been created
dsnPath <- file.path(dataDir, 'adm')
shpName <- 'ne_10m_admin_1_states_provinces'
SFDF <- convertLayer(
dsn = dsnPath,
layer = shpName
)
# ----- Select useful columns and rename -------------------------------------
# > dplyr::glimpse(SFDF, width = 75)
# Rows: 4,596
# Columns: 122
# $ featurecla <chr> "Admin-1 states provinces", "Admin-1 states provinces"…
# $ scalerank <int> 3, 6, 2, 6, 3, 4, 4, 3, 4, 3, 4, 3, 3, 10, 9, 2, 2, 2,…
# $ adm1_code <chr> "ARG-1309", "URY-8", "IDN-1185", "MYS-1186", "CHL-2694…
# $ diss_me <int> 1309, 8, 1185, 1186, 2694, 1936, 1937, 2693, 1939, 269…
# $ iso_3166_2 <chr> "AR-E", "UY-PA", "ID-KI", "MY-12", "CL-AP", "BO-L", "B…
# $ wikipedia <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ iso_a2 <chr> "AR", "UY", "ID", "MY", "CL", "BO", "BO", "CL", "BO", …
# $ adm0_sr <int> 1, 1, 5, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, …
# $ name <chr> "Entre Ríos", "Paysandú", "Kalimantan Timur", "Sabah",…
# $ name_alt <chr> "Entre-Rios", NA, "Kaltim", "North Borneo", NA, NA, NA…
# $ name_local <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ type <chr> "Provincia", "Departamento", "Propinsi", "State", "Reg…
# $ type_en <chr> "Province", "Department", "Province", "State", "Region…
# $ code_local <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ code_hasc <chr> "AR.ER", "UY.PA", "ID.KI", "MY.SA", "CL.AP", "BO.LP", …
# $ note <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ hasc_maybe <chr> NA, NA, NA, NA, NA, NA, NA, NA, "BO.OR|BOL-POT", NA, "…
# $ region <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ region_cod <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ provnum_ne <int> 10, 19, 15, 1, 0, 8, 7, 0, 1, 20006, 8, 22, 5, 0, 0, N…
# $ gadm_level <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, …
# $ check_me <int> 20, 0, 20, 20, 20, 0, 0, 20, 10, 20, 10, 20, 20, 20, 2…
# $ datarank <int> 3, 8, 1, 6, 3, 8, 6, 3, 6, 3, 5, 3, 3, 10, 8, 1, 1, 1,…
# $ abbrev <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ postal <chr> "ER", "PA", "KI", "SA", NA, "LP", "OR", "TA", "PO", "A…
# $ area_sqkm <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, 0, 0,…
# $ sameascity <int> -99, -99, -99, -99, 7, 6, 6, -99, -99, 6, 7, 6, -99, -…
# $ labelrank <int> 3, 6, 2, 6, 7, 6, 6, 3, 4, 6, 7, 6, 3, 20, 9, 2, 2, 2,…
# $ name_len <int> 10, 8, 16, 5, 18, 6, 5, 8, 6, 11, 5, 5, 5, 8, 7, 6, 8,…
# $ mapcolor9 <int> 3, 2, 6, 3, 5, 2, 2, 5, 2, 5, 4, 3, 3, 6, 3, 2, 4, 4, …
# $ mapcolor13 <int> 13, 10, 11, 6, 9, 3, 3, 9, 3, 9, 11, 13, 13, 3, 7, 2, …
# $ fips <chr> "AR08", "UY11", "ID14", "MY16", NA, "BL04", "BL05", "C…
# $ fips_alt <chr> NA, NA, NA, NA, NA, NA, NA, NA, "BL05", NA, "PE18", NA…
# $ woe_id <int> 2344682, 2347650, 2345723, 2346310, 56043702, 2344804,…
# $ woe_label <chr> "Entre Rios, AR, Argentina", "Paysandú, UY, Uruguay",…
# $ woe_name <chr> "Entre Ríos", "Paysandú", "Kalimantan Timur", "Sabah",…
# $ latitude <dbl> -32.02750, -32.09330, 1.28915, 5.31115, -18.32070, -14…
# $ longitude <dbl> -59.28240, -57.22400, 116.35400, 117.09500, -69.68040,…
# $ sov_a3 <chr> "ARG", "URY", "IDN", "MYS", "CHL", "BOL", "BOL", "CHL"…
# $ adm0_a3 <chr> "ARG", "URY", "IDN", "MYS", "CHL", "BOL", "BOL", "CHL"…
# $ adm0_label <int> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 2, 2, 2, 2, …
# $ admin <chr> "Argentina", "Uruguay", "Indonesia", "Malaysia", "Chil…
# $ geonunit <chr> "Argentina", "Uruguay", "Indonesia", "Malaysia", "Chil…
# $ gu_a3 <chr> "ARG", "URY", "IDN", "MYS", "CHL", "BOL", "BOL", "CHL"…
# $ gn_id <int> 3434137, 3441242, 1641897, 1733039, 6693562, 3911924, …
# $ gn_name <chr> "Provincia de Entre Rios", "Departamento de Paysandu",…
# $ gns_id <int> -988655, -908097, -2680740, -2405166, 10749159, -69341…
# $ gns_name <chr> "Entre Rios", "Paysandu, Departamento de", "Kalimantan…
# $ gn_level <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, NA, 1, 1,…
# $ gn_region <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ gn_a1_code <chr> "AR.08", "UY.11", "ID.14", "MY.16", "CL.16", "BO.04", …
# $ region_sub <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ sub_code <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ gns_level <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, NA, 1, 1,…
# $ gns_lang <chr> "khm", "fra", "ind", "fil", "ara", "kor", "kor", "fra"…
# $ gns_adm1 <chr> "AR08", "UY11", "ID14", "MY16", "CI16", "BL04", "BL05"…
# $ gns_region <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ min_label <dbl> 6.0, 8.0, 5.0, 7.0, 6.0, 6.6, 6.6, 6.0, 6.6, 6.0, 6.6,…
# $ max_label <dbl> 11.0, 11.0, 10.1, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, …
# $ min_zoom <dbl> 6.0, 8.0, 4.6, 7.0, 6.0, 6.6, 6.6, 6.0, 6.6, 6.0, 6.6,…
# $ wikidataid <chr> "Q44762", "Q16576", "Q3899", "Q179029", "Q2109", "Q272…
# $ name_ar <chr> "إنتري ريوس", "إدارة بايساندو", "كالمنتان الشرقية", "ص…
# $ name_bn <chr> "এন্ত্রে রিও প্রদেশ", "পেসান্ডো বিভাগ", "পূর্ব কালিমান্তান", …
# $ name_de <chr> "Entre Ríos", "Paysandú", "Ostkalimantan", "Sabah", "A…
# $ name_en <chr> "Entre Ríos", "Paysandú", "East Kalimantan", "Sabah", …
# $ name_es <chr> "Entre Ríos", "Paysandú", "Kalimantan Oriental", "Saba…
# $ name_fr <chr> "Entre Ríos", "Paysandú", "Kalimantan oriental", "Saba…
# $ name_el <chr> "Έντρε Ρίος", "Παϊσαντού", "Ανατολικό Καλιμαντάν", "Σα…
# $ name_hi <chr> "एन्ट्रे रियोस", "पयसंदु विभाग", "पूर्व कालिमंतान", "साबाह राज्…
# $ name_hu <chr> "Entre Ríos", "Paysandú", "Kelet-Kalimantan", "Sabah",…
# $ name_id <chr> "Entre Ríos", "Departemen Paysandú", "Kalimantan Timur…
# $ name_it <chr> "Entre Ríos", "dipartimento di Paysandú", "Kalimantan …
# $ name_ja <chr> "エントレ・リオス州", "パイサンドゥ県", "東カリマンタ…
# $ name_ko <chr> "엔트레리오스", "파이산두", "동칼리만탄", "사바", "아…
# $ name_nl <chr> "Entre Ríos", "Paysandú", "Oost-Kalimantan", "Sabah", …
# $ name_pl <chr> "Entre Ríos", "Paysandú", "Borneo Wschodnie", "Sabah",…
# $ name_pt <chr> "Entre Ríos", "Paysandú", "Kalimantan Oriental", "Sabá…
# $ name_ru <chr> "Энтре-Риос", "Пайсанду", "Восточный Калимантан", "Саб…
# $ name_sv <chr> "Entre Ríos", "Paysandú", "Kalimantan Timur", "Sabah",…
# $ name_tr <chr> "Entre Ríos eyaleti", "Paysandu Departmanı", "Doğu Kal…
# $ name_vi <chr> "Entre Ríos", "Paysandú", "Đông Kalimantan", "Sabah", …
# $ name_zh <chr> "恩特雷里奥斯省", "派桑杜省", "东加里曼丹省", "沙巴", …
# $ ne_id <dbl> 1159309789, 1159307733, 1159310009, 1159310033, 115931…
# $ name_he <chr> "אנטרה ריוס", "פאיסאנדו", "מזרח קלימנטאן", "סבה", "ארי…
# $ name_uk <chr> "Ентре-Ріос", "Пайсанду", "Східний Калімантан", "Сабах…
# $ name_ur <chr> "صوبہ انترے ریوس", "پایساندو محکمہ", "مشرقی کالیمانتان…
# $ name_fa <chr> "ایالت انتره ریوز", "بخش پایساندو", "کالیمانتان شرقی",…
# $ name_zht <chr> "恩特雷里奥斯省", "派桑杜省", "東加里曼丹省", "沙巴", …
# $ FCLASS_ISO <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_US <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_FR <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_RU <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_ES <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_CN <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_TW <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_IN <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_NP <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_PK <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_DE <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_GB <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_BR <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_IL <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_PS <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_SA <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_EG <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_MA <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_PT <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_AR <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_JP <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_KO <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_VN <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_TR <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_ID <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_PL <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_GR <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_IT <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_NL <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_SE <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_BD <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_UA <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ FCLASS_TLC <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ geometry <MULTIPOLYGON [°]> MULTIPOLYGON (((-58.20011 -..., MULTIPOLY…
# Data Dictionary:
# featurecla --> (drop)
# scalerank ---> (drop)
# adm1_code ---> adm1_code: Unique identifier
# diss_me -----> (drop)
# iso_3166_2 --> (drop)
# wikipedia ---> (drop)
# iso_a2 ------> countryCode: 2-character country code
# adm0_sr -----> (drop)
# name --------> stateName: Native language name
# name_alt ----> (drop)
# name_local --> (drop)
# type --------> (drop)
# type_en -----> (drop)
# code_local --> (drop)
# code_hasc ---> code_hasc: HASC code
# note --------> (drop)
# hasc_maybe --> (drop)
# region ------> (drop)
# region_cod --> (drop)
# provnum_ne --> (drop)
# gadm_level --> (drop)
# check_me ----> (drop)
# datarank ----> (drop)
# abbrev ------> (drop)
# postal ------> postal: country FIPS code
# area_sqkm ---> area_sqkm: area in square kilometers
# sameascity --> (drop)
# labelrank ---> (drop)
# name_len ----> (drop)
# mapcolor9 ---> (drop)
# mapcolor13 --> (drop)
# fips --------> stateFIPS: FIPS code
# fips_alt ----> (drop)
# woe_id ------> (drop)
# woe_label ---> (drop)
# woe_name ----> (drop)
# latitude ----> latitude: latitude coordinate
# longitude ---> longitude: longitude coordinate
# sov_a3 ------> (drop)
# adm0_a3 -----> (drop)
# adm0_label --> (drop)
# admin -------> (drop)
# geounit -----> (drop)
# gu_a3 -------> (drop)
# gn_id -------> (drop)
# gn_name -----> (drop)
# gns_id ------> (drop)
# gns_name ----> (drop)
# gn_level ----> (drop)
# gn_region ---> (drop)
# gn_a1_code --> (drop)
# region_sub --> (drop)
# sub_code ----> (drop)
# gns_level ---> (drop)
# gns_lang ----> gns_lang: ISO 639-3 language identifier
# gns_adm1 ----> gns_adm1: adm1 identifier
# gns_reigon --> (drop)
# min_label ---> (drop)
# max_label ---> (drop)
# min_zoom ----> (drop)
# wikidataid --> (drop)
# name_* ------> (drop)
# ne_id -------> (drop)
# FCLASS* ----->
# NOTE: Subset to filter out exceptional areas (islands and disputed
# NOTE: territories) marked with '~'
goodAreas <- stringr::str_subset(SFDF$code_hasc, "~", negate = TRUE)
SFDF <-
SFDF %>%
dplyr::filter(.data$code_hasc %in% goodAreas)
# Add the core identifiers to the simple features data frame
SFDF$stateCode <-
SFDF$code_hasc %>%
stringr::str_trim() %>%
stringr::str_sub(4,-1)
SFDF$countryName <- MazamaSpatialUtils::codeToCountry(SFDF$iso_a2)
SFDF$stateName <- SFDF$name
SFDF$stateFIPS <- SFDF$fips
# Create the new dataframe in a specific column order
SFDF <-
SFDF %>%
dplyr::select(
countryCode = .data$iso_a2,
countryName = .data$countryName,
stateCode = .data$stateCode,
stateName = .data$name,
stateFIPS = .data$stateFIPS,
latitude = .data$latitude,
longitude = .data$longitude,
area_sqkm = .data$area_sqkm,
postal = .data$postal,
adm1_code = .data$adm1_code,
code_hasc = .data$code_hasc,
gns_lang = .data$gns_lang,
gns_adm1 = .data$gns_adm1
)
# ----- Simplify and save ----------------------------------------------------
uniqueIdentifier <- "adm1_code"
simplifyAndSave(
SFDF = SFDF,
datasetName = datasetName,
uniqueIdentifier = uniqueIdentifier,
dataDir = dataDir
)
# ----- Clean up and return --------------------------------------------------
# Clean up
unlink(filePath, force = TRUE)
unlink(dsnPath, recursive = TRUE, force = TRUE)
return(invisible(datasetName))
}
# ===== TEST ===================================================================
if ( FALSE ) {
library(sf)
# Look or horizontal lines from polygons that cross the dateline.
# NOTE: These are sometimes created by sf::st_make_valid()
loadSpatialData(datasetName)
SFDF <- get(paste0(datasetName, ""))
SFDF_05 <- get(paste0(datasetName, "_05"))
SFDF_02 <- get(paste0(datasetName, "_02"))
SFDF_01 <- get(paste0(datasetName, "_01"))
plot(SFDF_01$geometry)
dev.off(dev.list()["RStudioGD"])
plot(SFDF_02$geometry)
dev.off(dev.list()["RStudioGD"])
plot(SFDF_05$geometry)
dev.off(dev.list()["RStudioGD"])
#plot(SFDF$geometry)
# Try out getSpatialData()
lons <- c(-120:-110, 0:10)
lats <- c(30:40, 30:40)
df <- getSpatialData(lons, lats, SFDF_01)
df <- getSpatialData(lons, lats, SFDF_02)
df <- getSpatialData(lons, lats, SFDF_05)
df <- getSpatialData(lons, lats, SFDF)
# Special Case of Russian failing to plot properly
SFDF %>% dplyr::filter(countryCode == "RU") %>% sf::st_geometry() %>% plot()
}
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