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https://github.com/skgrange/gissr

Tools To Make Working With R and Spatial Data Easier
https://github.com/skgrange/gissr

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Tools To Make Working With R and Spatial Data Easier

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# **gissr** 



[![Lifecycle: retired](https://img.shields.io/badge/lifecycle-retired-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#retired)



**gissr** is a collection of R functions which make working with spatial data easier.



## Retired note



As most spatial data and R users will be aware, the **rgdal**, **rgeos**, and **maptools** packages were retired in October 2023. This is because the developer of the packages retired and a new generation of spatial tools has emerged in the form of the **sf**, **terra**, and **stars** packages. Because **gissr** is mostly built upon the older packages (that have now been archived), **gissr** was retired on June 17, 2024. The development of **gissr**'s successor based on the **sf** and  **terra** packages called [**sspatialr**](https://github.com/skgrange/sspatialr) is ongoing. For new projects, it is recommended that **sspatialr** is used rather than **gissr**.



## Installation



The development version: 



```

# Install dependency

remotes::install_github("skgrange/threadr")



# Install gissr

remotes::install_github("skgrange/gissr")

```



## Background



R's spatial data analysis abilities are very well developed. Therefore, R can be an effective geographical information system (GIS). A key advantage of R in GIS applications is that the user can dip in and out of R's general string, numerical, and visualisation tools and apply them to spatial data.



However, the challenges I have with using R as a GIS are:



  - Keeping track of the multiple packages which are used,

  

  - the lack of consistency among these packages, and

  

  - the lack of tidy outputs which other areas of the R ecosystem have been so good at developing. 

  

To overcome these points, I have written wrappers for many geographical functions which generally begin `sp_` to do particular tasks and bundle all the dependencies together as a package. Some of these functions will likely be useful for others. 



## Utility functions



  - Easily read shapefiles, GPX, GeoJSON, KML, GML, TAB, and File Geodatabases with `sp_read`, a wrapper for `rgdal::readOGR`.

    - Also check spatial files and system things with `sp_list_drivers`, `sp_list_layers`, and `sp_layer_info`. 

    

  - Transform projection systems with `sp_transform`.

    - `sp_transform` can also force projections when a spatial object has none.

    - `transform_coordinates` does a similar thing, but for data frames.

    

  - Transform data frames (tables) to spatial points, lines, or polygons with `sp_from_data_frame`. 

  

  - Transform data frames with a well-known text (WKT) variable (or just a vector) to a spatial object with `sp_from_wkt`.

  

  - Bind/combine different spatial objects with `sp_bind`. 

  

  - Unite spatial objects with `sp_unite` and do the opposite with `sp_disaggregate`. 

  

  - Calculate lengths or areas of spatial objects with `sp_area` and `sp_length`.

  

  - Clip or crop a spatial object to a rectangular envelope with `sp_clip`. 

  

    - To filter objects by other polygons, use `[` subsetting (or `sp_filter`). 

    

    - Rectangular or elliptical polygons can be created with `sp_create_envelope` and `sp_ellipse` for this purpose too. 

    

  - Do simple transformations to spatial objects with `sp_move`, `sp_flip`, `sp_reflect`, and `sp_rotate`. 

  

  - Simplify spatial objects with `sp_simplify`.

  

  - "Dissolve" polygons to make a single feature with `sp_dissolve_polygons`.

  

  - "Punch" holes in polygons with `sp_punch`. 

  

  - Add positive or negative buffers with `sp_buffer`.

  

  - Create enclosing polygons with `sp_convex_hull`.

  

  - Find centroids of geometries with `sp_centroid`. 

  

  - "Promote" or "demote" Spatial\* to Spatial\*DataFrame, *i.e.* add or drop data slots for geometries with `sp_promote` and `sp_demote`. 

  

  - Return and reset geometry IDs with `sp_feature_ids` and `sp_reset_feature_ids`.

  

  - Point-in-polygon tests with `sp_left_join`.

  

  - Calculate distances among spatial objects with `sp_distance`.

    - `distance_by_haversine` does the same thing, but with a different method, and for data frames.

    

  - Fix issues with spatial objects with `sp_fix`. This function is a blatant wrap of [`cleangeo::clgeo_Clean`](https://github.com/eblondel/cleangeo). This function is a good piece of work so make sure you have a look at the **cleangeo** package.

  

  - Parse vectors of degrees, minutes, and seconds into decimal degrees with `dms_to_decimal`. 

  

  - Sort/arrange points in a clockwise order with `sort_points`. 

  

  - Create Tessellation polygons with `sp_tessellation_polygons`. 

  

  - Export spatial objects to spatial data files with `write_gpx`, `write_geojson`, and `write_shapefile`. 

  

  - Transform spatial objects to data frames with `sp_fortify`. 

  

### Raster functions



  - Create a raster layer from spatial data with `ra_from_sp`. 

  

  - Filter/crop/mask a raster layer with a spatial polygon with `ra_mask`. 

  

  - Interpolate a raster layer/surface with `ra_interpolate`. 

  

  - Increase a raster's resolution with `ra_disaggregate`. 

  

  - Smooth a raster's values with `ra_focal`.

  

  - Extract values from raster objects using spatial data types with `ra_drill` and then produce a "tidy data" version with `tidy_ra_drill`.

  

  - Transform raster objects to data frames with `ra_fortify`.

  

  - Bind or merge a number of raster layers together with `ra_bind` 

  

### OpenStreetMap data importers



  - A collection of `get_osm_*` functions to import data from OpenStreetMap. 



## Things I want to do



  - Develop a function which can read *n* features in a spatial data file. This will be helpful when large data files are encountered and system memory is too small to load the entire file at once. 

  

  - Get the interface between R and SpatiaLite sorted -- this can probably be left to [**sf**](https://github.com/r-spatial/sf) now.

  

  - Concave hull function *i.e.* find minimum area polygon. 

  

  - Add support for WKB (well-known binary). 



## See also



  - [**sf**](https://github.com/r-spatial/sf)

  - [**terra**](https://github.com/rspatial/terra)

  - [**sspatialr**](https://github.com/skgrange/sspatialr)