# Get started

CatastRo provide access to different API services of the Spanish Cadastre. With CatastRo it is possible to download official information of addresses, properties, parcels and buildings.

## OVCCoordenadas Service

The OVCCoordenadas service allows to retrieve the coordinates of a known cadastral reference (geocoding). It is also possible to retrieve the cadastral references around a specific pair of coordinates (reverse geocoding). CatastRo returns the results on a `tibble` format. This functionality is described in detail in the corresponding vignette (see `vignette("ovcservice", package = "CatastRo")`).

## INSPIRE Services

> The INSPIRE Directive aims to create a European Union spatial data infrastructure for the purposes of EU environmental policies and policies or activities which may have an impact on the environment. This European Spatial Data Infrastructure will enable the sharing of environmental spatial information among public sector organisations, facilitate public access to spatial information across Europe and assist in policy-making across boundaries.

> From https://knowledge-base.inspire.ec.europa.eu/overview_en

The implementation of the INSPIRE directive on the Spanish Cadastre (see Catastro INSPIRE) allows to retrieve spatial objects from the database of the cadastre:

- Vector objects: Parcels, addresses, buildings, cadastral zones and more. These objects are provided by CatastRo as `sf` objects as provided by the sf package.
- Imagery: Image layers representing the same information than the vector objects. These objects are provided by CatastRo as `SpatRaster` objects as provided by the terra package.

Note that the coverage of this service is 95% of the Spanish territory, excluding Basque Country and Navarre1 that have their own independent cadastral offices.

There are three types of functions, each one querying a different service:

1. ATOM service: The ATOM service allows to batch-download vector objects of different cadastral elements for a specific municipality.

2. WFS service: The WFS service allows to download vector objects of specific cadastral elements. Note that there are some restrictions on the extension and number of elements to query. For batch-downloading the ATOM service is preferred.

3. WMS service: This service allows to download georeferenced images of different cadastral elements.

## Examples

### Working with layers

On this example we would demonstrate some of the main capabilities of the package by recreating a cadastral map of the surroundings of the Santiago Bernabéu Stadium. We would make use of the WMS and WFS services to get different layers in order to show some of the capabilities of the package:

    # Extract building by bounding box
    # Check https://boundingbox.klokantech.com/

    library(CatastRo)

    stadium <- catr_wfs_get_buildings_bbox(
      c(-3.6891446916, 40.4523311971, -3.687462138, 40.4538643165),
      srs = 4326
    )

    # Now extract cadastral parcels. We can use spatial objects on the query

    stadium_parcel <- catr_wfs_get_parcels_bbox(stadium)

    # Project for tiles

    stadium_parcel_pr <- sf::st_transform(stadium_parcel, 25830)

    # Extract imagery: Labels of the parcel

    labs <- catr_wms_get_layer(stadium_parcel_pr,
      what = "parcel",
      styles = "BoundariesOnly",
      srs = 25830
    )

    # Plot
    library(ggplot2)
    library(tidyterra) # For terra tiles

    ggplot() +
      geom_spatraster_rgb(data = labs) +
      geom_sf(data = stadium_parcel_pr, fill = NA, col = "red", linewidth = 2) +
      geom_sf(data = stadium, fill = "red", alpha = .5) +
      coord_sf(crs = 25830)

Example: Santiago Bernabeu

### Thematic maps

We can create also thematic maps using the information available on the spatial objects. We would produce a visualization of the urban growth of Granada using CatastRo, replicating the map produced by Dominic Royé on his post Visualize urban growth, using the ATOM services.

In first place, we extract the coordinates of the city center of Granada using mapSpain:

    library(dplyr)
    library(sf)
    library(mapSpain)

    # Use mapSpain for getting the coords

    city <- esp_get_capimun(munic = "^Granada$")

Next step consists on extracting the buildings using the ATOM service. We would use also the function `catr_get_code_from_coords()` to identify the code of Granada in the Cadastre, and we would download the buildings with `catr_atom_get_buildings()`.

    city_catr_code <- catr_get_code_from_coords(city)

    city_catr_code
    #> # A tibble: 1 × 12
    #>   munic catr_to catr_munic catrcode cpro  cmun  inecode nm    cd    cmc   cp    cm
    #>   <chr> <chr>   <chr>      <chr>    <chr> <chr> <chr>   <chr> <chr> <chr> <chr> <chr>
    #> 1 GRAN… 18      900        18900    18    087   18087   GRAN… 18    900   18    87

    city_bu <- catr_atom_get_buildings(city_catr_code$catrcode)

Next step for creating the visualization is to limit the analysis to a circle of radius 1.5 km around the city center:

    buff <- city %>%
      # Adjust CRS to 25830: (Buildings)
      st_transform(st_crs(city_bu)) %>%
      # Buffer
      st_buffer(1500)

    # Cut buildings

    dataviz <- st_intersection(city_bu, buff)

    ggplot(dataviz) +
      geom_sf()

Minimal cadastral map of Granada

Let’s extract now the construction year, available in the column `beginning`:

    # Extract 4 initial positions
    year <- substr(dataviz$beginning, 1, 4)

    # Replace all that doesn't look as a number with 0000
    year[!(year %in% 0:2500)] <- "0000"

    # To numeric
    year <- as.integer(year)

    # New column
    dataviz <- dataviz %>%
      mutate(year = year)

Last step is to create groups based on the year and create the data visualization. We use here the function `cut()` to create classes for every decade starting in year 1900:

    dataviz <- dataviz %>%
      mutate(year_cat = cut(year,
        breaks = c(0, seq(1900, 2030, by = 10)),
        dig.lab = 4
      ))

    ggplot(dataviz) +
      geom_sf(aes(fill = year_cat), color = NA, na.rm = TRUE) +
      scale_fill_manual(
        values = hcl.colors(15, "Spectral"),
        na.translate = FALSE
      ) +
      theme_void() +
      labs(title = "GRANADA", fill = "") +
      theme(
        panel.background = element_rect(fill = "black"),
        plot.background = element_rect(fill = "black"),
        legend.justification = .5,
        legend.text = element_text(
          colour = "white",
          size = 12
        ),
        plot.title = element_text(
          colour = "white", hjust = .5,
          margin = margin(t = 30),
          size = 30
        ),
        plot.caption = element_text(
          colour = "white",
          margin = margin(b = 20), hjust = .5
        ),
        plot.margin = margin(r = 40, l = 40)
      )

Granada: Urban growth

## References

- Royé D (2019). “Visualize urban growth.” https://dominicroye.github.io/en/2019/visualize-urban-growth/.

1. The package CatastRoNav provides access to the Cadastre of Navarre, with similar functionalities than CatastRo.↩︎