The goal of geoidep📦 is to offers R users an easy and accessible way to obtain official cartographic data on various topics, such as society🏛️, transport🚗, environment🌱, agriculture🌾, climate⛅️,among others.This includes information provided by regional government entities and technical-scientific institutions, managed by the Spatial Data Infrastructure of Peru.
Installation R
You can install the development version of geoidep like so:
install.packages('pak')
pak::pkg_install('ambarja/geoidep')or also the official version available on CRAN:
install.packages('geoidep')Example 01: Introduction
In this example, we can identify the list of providers available in geoidep and the layers they present.
get_data_sources() |>
head()
#> # A tibble: 6 × 7
#> provider category layer layer_can_be_actived admin_en year link
#> <chr> <chr> <chr> <lgl> <chr> <chr> <chr>
#> 1 INEI General departamento TRUE Nationa… 2019 http…
#> 2 INEI General provincia TRUE Nationa… 2019 http…
#> 3 INEI General distritos TRUE Nationa… 2019 http…
#> 4 Midagri Agriculture agriculture_s… TRUE Ministr… 2024 http…
#> 5 Midagri Agriculture oil_palm_areas TRUE Ministr… 2016… http…
#> 6 Geobosque Forest stock_bosque_… FALSE Ministr… 2001… http…In summary the suppliers and the number of available layers
get_providers()
#> # A tibble: 8 × 2
#> provider layer_count
#> <fct> <int>
#> 1 Geobosque 5
#> 2 INAIGEM 3
#> 3 INEI 7
#> 4 Midagri 2
#> 5 MTC 27
#> 6 Senamhi 1
#> 7 Serfor 1
#> 8 Sernanp 61Example 02: Download official INEI administrative boundaries
This is a simple example of how to download Peru’s official administrative boundaries:
dep <- get_departaments(show_progress = FALSE)The first 10 rows of the original data are displayed here:
head(dep)
#> Simple feature collection with 6 features and 6 fields
#> Geometry type: MULTIPOLYGON
#> Dimension: XY
#> Bounding box: xmin: -79.45857 ymin: -17.28501 xmax: -70.80408 ymax: -2.986125
#> Geodetic CRS: WGS 84
#> id objectid ccdd nombdep shape_length shape_area
#> 1 1 1 01 AMAZONAS 13.059047 3.199147
#> 2 2 2 02 ANCASH 11.788249 2.954697
#> 3 3 3 03 APURIMAC 7.730154 1.765933
#> 4 4 4 04 AREQUIPA 17.459435 5.330125
#> 5 5 5 05 AYACUCHO 17.127166 3.643705
#> 6 6 6 06 CAJAMARCA 12.540288 2.688386
#> geom
#> 1 MULTIPOLYGON (((-77.81399 -...
#> 2 MULTIPOLYGON (((-77.64697 -...
#> 3 MULTIPOLYGON (((-73.74655 -...
#> 4 MULTIPOLYGON (((-71.98109 -...
#> 5 MULTIPOLYGON (((-74.34843 -...
#> 6 MULTIPOLYGON (((-78.70034 -...