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sigugr

Workflow for Geographic Data

Streamlines geographic data transformation, storage and publication, simplifying data preparation and enhancing interoperability across formats and platforms.

README

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# sigugr: Workflow for Geographic Data <a href="https://josesamos.github.io/sigugr/"><img src="man/figures/logo.png" align="right" height="139" alt="sigugr website" /></a>

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The workflow for geographic data typically involves:

- Data acquisition: Many datasets are sourced from web downloads.  
- Data transformation: This includes tasks such as raster composition,
  resolution adjustments, clipping, reprojection, and style
  management.  
- Data storage: Storing the processed data in databases, such as
  PostGIS.  
- Data publication: Making the data accessible via platforms like
  GeoServer.

The goal of the `sigugr` package is to provide a comprehensive set of
functions that simplify the processes of transforming, storing, and
publishing geographic data.

## Installation

You can install the released version of `sigugr` from
[CRAN](https://CRAN.R-project.org) with:

``` r
install.packages("sigugr")
```

And the development version from [GitHub](https://github.com/) with:

``` r
# install.packages("pak")
pak::pak("josesamos/sigugr")
```

## Example

The satellite bands for a specific area were downloaded from
[*GloVis*](https://glovis.usgs.gov/app?fullscreen=0) (*USGS Global
Visualization Viewer*). They were integrated and initially transformed
using the [`satres`](https://CRAN.R-project.org/package=satres) package.
To reduce their file size and enable inclusion here, their resolution
was adjusted using the `aggregate_rasters()` function provided by this
package.

Figure 1 below shows the original satellite bands that we started with.

``` r
library(sigugr)

tif <- system.file("extdata", "sat.tif", package = "sigugr")
sat <- terra::rast(tif)
terra::plot(sat)
```

<div class="figure" style="text-align: center">

<img src="man/figures/README-web-usgs01-1.png" alt="Figure 1: Original satellite bands." width="80%" />
<p class="caption">
Figure 1: Original satellite bands.
</p>

</div>

We are interested only in the area defined by a polygon representing a
municipality in the region. Using the `clip_raster()` function, we
extract the area of interest. We can either preserve the original CRS of
the bands or reproject them to the CRS of the clipping polygon, which is
controlled by the `keep_crs` parameter.

The obtained result is shown in Figure 2.

``` r
gpkg <- system.file("extdata", "sigugr.gpkg", package = "sigugr")
polygon <- sf::st_read(gpkg, layer = "lanjaron", quiet = TRUE)

sat2 <- clip_raster(sat, polygon, keep_crs = FALSE)

terra::plot(sat2)
```

<div class="figure" style="text-align: center">

<img src="man/figures/README-clip-1.png" alt="Figure 2: Satellite bands cut by a polygon." width="80%" />
<p class="caption">
Figure 2: Satellite bands cut by a polygon.
</p>

</div>

We save the result in a working file, which will be used for database
storage and publication.

``` r
sat_file <- tempfile(fileext = ".tif")
terra::writeRaster(sat2, sat_file, filetype = "GTiff", overwrite = TRUE)
```

We store the result in a PostGIS database using the `store_raster()`
function. The database must have the `postgis` and `postgis_raster`
extensions enabled.

``` r
conn <- DBI::dbConnect(
  RPostgres::Postgres(),
  dbname = "sigugr",
  host = "localhost",
  user = "postgres",
  password = "postgres"
)

tables <- store_bands(sat_file, conn)

DBI::dbDisconnect(conn)
```

The following Figure 3 shows the access from QGIS to one of the tables
included in the database.

<div class="figure" style="text-align: center">

<img src="man/figures/qgis-postgis.png" alt="Figure 3: Accessing PostGIS from QGIS." width="100%" />
<p class="caption">
Figure 3: Accessing PostGIS from QGIS.
</p>

</div>

To publish the raster bands in GeoServer, we must use the version stored
in the file, as GeoServer does not support PostGIS as a source for
raster data. We publish them using the `publish_bands()` function.

``` r
gso <- geoserver(
  url = "http://localhost:8080/geoserver",
  user = "admin",
  password = "geoserver",
  workspace = "sigugr"
)

gso |>
  publish_bands(sat_file)
```

The result can also be viewed from QGIS by accessing the GeoServer
instance via WMS, as shown in Figure 4.

<div class="figure" style="text-align: center">

<img src="man/figures/qgis-geoserver.png" alt="Figure 4: Accessing GeoServer from QGIS." width="100%" />
<p class="caption">
Figure 4: Accessing GeoServer from QGIS.
</p>

</div>

Except for the functions used to connect to PostGIS and GeoServer, as
well as those for accessing layers in files, the following function
calls have been used to clip and reproject the satellite bands, store
them in PostGIS, and publish them in GeoServer:

``` r
# Clip and reproject
sat2 <- clip_raster(sat, polygon, keep_crs = FALSE)

# Store in PostGIS
tables <- store_bands(sat_file, conn)

# Publish in GeoServer
gso |>
  publish_bands(sat_file)
```

Using data obtained from the web, we can easily transform, store, and
publish it using the functions implemented in the package, as
demonstrated in this example.

Versions across snapshots

VersionRepositoryFileSize
1.0.0 rolling linux/jammy R-4.5 sigugr_1.0.0.tar.gz 3.2 MiB
1.0.0 rolling linux/noble R-4.5 sigugr_1.0.0.tar.gz 3.2 MiB
1.0.0 rolling source/ R- sigugr_1.0.0.tar.gz 3.2 MiB
1.0.0 latest linux/jammy R-4.5 sigugr_1.0.0.tar.gz 3.2 MiB
1.0.0 latest linux/noble R-4.5 sigugr_1.0.0.tar.gz 3.2 MiB
1.0.0 latest source/ R- sigugr_1.0.0.tar.gz 3.2 MiB
1.0.0 2026-04-26 source/ R- sigugr_1.0.0.tar.gz 3.2 MiB
1.0.0 2026-04-23 source/ R- sigugr_1.0.0.tar.gz 3.2 MiB
1.0.0 2026-04-09 windows/windows R-4.5 sigugr_1.0.0.zip 2.9 MiB
1.0.0 2025-04-20 source/ R- sigugr_1.0.0.tar.gz 3.2 MiB

Dependencies (latest)

Imports

Suggests