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https://github.com/skgrange/gissr
Tools To Make Working With R and Spatial Data Easier
https://github.com/skgrange/gissr
Last synced: 3 months ago
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Tools To Make Working With R and Spatial Data Easier
- Host: GitHub
- URL: https://github.com/skgrange/gissr
- Owner: skgrange
- License: gpl-3.0
- Created: 2015-08-08T14:14:10.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2024-06-17T05:59:40.000Z (5 months ago)
- Last Synced: 2024-06-17T06:55:20.216Z (5 months ago)
- Language: R
- Homepage:
- Size: 2.08 MB
- Stars: 11
- Watchers: 5
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# **gissr** 
[](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 Because **gissr** is mostly built upon the older packages (that have now been archived), **gissr** was retired on June 17, 2024.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)