SELECT NAME_0, NAME_1, HASC_1, ISO FROM gadm36 WHERE ISO LIKE 'US%'; Here is how to work with the data after a successful download. Workflow A: Extract a single country from global Geopackage (fastest) If you downloaded the global Geopackage, you don’t need to re-download per country:
library(sf) library(dplyr) gadm <- st_read("gadm36_levels.gpkg", layer="ADM_ADM_1") pop_data <- read.csv("population_estimates.csv") # has GID_1 column merged <- left_join(gadm, pop_data, by="GID_1") GADM 3.6 boundaries are high-resolution (often >1 MB per province). Use simplification before serving tiles: download gadm data version 36 work
Example – add population data in R:
GADM (Database of Global Administrative Areas) is the gold standard for boundary data. Version 3.6, released in late 2020 (with minor updates into 2021), remains one of the most widely used versions due to its stability, licensing clarity, and compatibility with legacy systems. However, novice users often struggle with file formats, projection mismatches, and API changes. SELECT NAME_0, NAME_1, HASC_1, ISO FROM gadm36 WHERE
If you have landed on this page, you are likely looking for a reliable, step-by-step protocol to and actually get it to work in your Geographic Information System (GIS), statistical software (like R or Python), or web mapping platform. Version 3
Target Keyword: download gadm data version 36 work
# Manual download method download.file("https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_USA_1_sp.rds", "gadm36_USA_1_sp.rds") usa_adm1 <- readRDS("gadm36_USA_1_sp.rds") Solution: Cross-reference with GADM 3.6’s lookup table. Download the gadm36_levels.gpkg and query the gadm36 table using SQL: