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geoidep

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

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 

library(geoidep)
#> 
#> ── Welcome to geoidep ──────────────────────────────────────────────────────────
#> ℹ geoidep is a wrapper that allows you to download cartographic data for Peru from R.
#> Currently, `geoidep` supports the following providers:
#> ✔ Geobosque
#> ✔ INEI
#> ✔ Midagri
#> ✔ Sernanp
#> ℹ For more information, please use the `get_data_sources()` function.

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 vegetation_cov… TRUE                 Ministr… 2018  http…
#> 5 Midagri  Agriculture agriculture_se… TRUE                 Ministr… 2024  http…
#> 6 Midagri  Agriculture oil_palm_areas  TRUE                 Ministr… 2016… http…

In summary the suppliers and the number of available layers

get_providers() 
#> # A tibble: 4 × 2
#>   provider  layer_count
#>   <fct>           <int>
#> 1 Geobosque           5
#> 2 INEI                3
#> 3 Midagri             4
#> 4 Sernanp            61

Example 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 -...

Example 03: Working with Gebosque data

This is another example of how to obtain historical forest loss data according to a given administrative boundary.

loreto <- dep |> filter(NOMBDEP == "LORETO")
historico <- get_forest_loss_data(
  layer = "stock_bosque_perdida_departamento",
  ubigeo = loreto[["CCDD"]],
  show_progress = FALSE)
historico |> 
  ggplot(aes(x = anio,y = perdida )) + 
  geom_point(size = 2) + 
  geom_line(linewidth =1) + 
  theme_minimal() + 
  labs(
    title = "Pérdida de bosque del departamento de Loreto \ndurante los años 2001 - 2023",
    caption = "Fuente: Geobosque")