Name: maptools
Owner: rOpenSci
Description: CRAN Task View for mapping tools
Created: 2014-11-10 19:51:56.0
Updated: 2017-01-18 14:34:25.0
Pushed: 2016-04-04 17:58:35.0
Homepage:
Size: 98
Language: Makefile
GitHub Committers
| User | Most Recent Commit | # Commits |
|---|
Other Committers
| User | Email | Most Recent Commit | # Commits |
|---|
README
CRAN Task View: Mapping tools and services
Maintainer: Contact:
Jeff Hollister, Scott Chamberlain, hollister.jeff at epa.gov
Karthik Ram, Hadley Wickham, Ben
Marwick, Cory Nissen
This task view contains information about mapping and visualizing
spatial data in R. The base version of R does not ship with many tools
for mapping spatial data. Thankfully, there are an increasingly large
number of tools for doing so, both with just R or javascript libraries.
A list of available packages and functions is presented below, grouped
by the type of activity. If you have any comments or suggestions for
additions or improvements for this taskview, go to Github and submit an issue, or make some changes and
submit a pull request. If
you can't contribute on Github, send Jeff an email. If you have an issue with one of
the packages discussed below, please contact the maintainer of that
package. This task view is focused on mapping spatial data and less so
on the foundations of working with spatial data in R. That material is
covered in detail in the Spatial Task View. There is some overlap between the two
task views, but an effort has been made to reduce redundancy so that
these task views compliment one another.
Mapping tools in R
Visualization
- cartodb: CartoDB R
client. Not on CRAN, and hasn't been active for a while. Source on Github
- cartographer:
Interactive maps in R using
d3-carto-map. Source on Github
- ggmap:
Visualization of spatial data and models on top of Google Maps,
OpenStreetMaps, Stamen Maps, or CloudMade Maps using ggplot2.
Source on Github
- leaflet:
Client for the JavaScript library Leaflet.js. Uses
htmlwidgets
to provide structure for output. Integrated with R Console, RStudio,
and R Markdown v 2. Can include interactive maps with markdown
documents as well as with
shiny
apps. Source on Github
- leafletR:
Another client for the JavaScript library Leaflet.js. Basic mapping
functionality to combine vector data and online map tiles from
different sources. Source on Github
- mapview:
This package provides wrappers to the
leaflet
package that simplifies the creation of maps. Stated purpose of the
package is to facilitate interactive viewing of spatial data in R.
Source on Github.
- micromap:
This group of functions simplifies the creation of linked micromap
plots, and uses ggplot2 plotting framework. Source on Github.
- OpenStreetMap:
An R client for fetching raster images via the Open Street Maps API.
- plotGoogleMaps:
This package provides a interactive plot device for handling the
geographic data for web browsers. It is designed for the automatic
creation of web maps as a combination of users' data and Google Maps
layers.
- quickmpar:
Quick visualization of
sp and
raster
objects. Provides basic interactivity including zooming and panning
as well as identifying features. Source on Github
- rasterVis:
Package for enhanced visualization of raster data. Source on Github
- Rgooglemaps:
Query Google static maps, and use the map as a background image to
overlay plots within R. Source on Github
- rMaps: A general purpose
wrapper around main Javascript mapping libraries, including
Leaflet,
Datamaps, and
Crosslet. Source on Github
- sp: Core
spatial package in R with basic spatial data manipulation methods.
Most spatial analysis packages reuse the classes and methods
provided by
sp.
Plotting capability in
sp
is provided through plot methods. More advanced plotting based on
lattice.
Source on GitHub
- tmap:
Package provides an approach to build thematic maps (e.g.
chloropleth or bubble maps). Utilizes a grammar of graphics syntax.
Source on GitHub
Projecting Data
Coordinates for spatial data can come in many different flavors with
different units, datum, projections, and more. Many of the tools will
visualize your data regardless of the native coordinate reference
system; however, most (all?) of the javascript libraries assume some
flavor of latitude-longitude, thus if your data are projected they need
to be transformed back to geographic coordinates prior to mapping. For
most mapping and visualization efforts unprojected data (often displayed
in Web Mercator/EPSG::3857) is fine; however, if accurate area, length,
or distance measurements are required through interacting with the map,
then projections need to be considered. A discussion of projections and
coordinate systems is beyond the scope of this task view. To learn more
a good starting place is NCEAS' Overview of Coordinate Reference Systems in R.
This more general discussion of projection from the
USGS
is also good.
Once you know that you need to transform you data there are several
options:
- sp: The
function
spTransform (and methods in
rgdal) is
the workhorse function for spatial transformations of vector data
and it uses PROJ.4 arguments to
specify the transformations. Accepted inputs are provided by the
spTransform methods in
rgdal.
Source for sp on GitHub. Source for rgdal on R-Forge.
- mapproj:
This package provides a function to convert two vectors representing
longitude (x) and latitude (y) to projected coordinates.
- PBSmapping:
The function
convUL will transform coordinates between Universal
Transverse Mercator (UTM) and longitude-latitude. A data frame with
a projection attribute is required input. Source on Google Code
Geocoding
Geocoding is the process of converting address or place name information
into geographic coordinates. Most of these have somewhat restricted
Terms of Service(TOS). Be sure to read those carefully prior to use.
Links for the TOS are provided.
Map Data
There are *many* possible sources and formats of data to use as base
layers, so this list will most certainly be incomplete. Details for
reading and writing most types of spatial data are already included in
the Analysis of Spatial Data Task View, thus this list
will focus on additional sources or features not discussed in that task
view.
- geojsonio:
Provides utility for working with geojson data in R. Includes
functions to convert sp objects, lists, and character to geojson
format.
- geonames:
functions for working with geonames, a
geographical database that covers all countries and contains over
eight million place names
- maps:
Collection of coarse scaled for the US, some European countries, and
a world map. Stored as `map` objects and various other geographic
datasets. Location information in decimal degrees. Needs conversion
to work with visualization from
sp,
ggmap,
etc. Code for projections and additional maps in packages
mapproj
mapdata.
- openadds: An R client for
Openaddresses. The Openaddresses data
comes in a variety of formats and this package provides common
interface to simplify working with it in R. Source on Github
- osmar:
Package for interacting with the Open Street Map API in R. Functions
for converting an open street map object into
sp or
igraph
objects. Source on R-Forge.
- prism: Accesses climate data
from PRSIM. Also provides some
basic plotting and mapping functions.
- rworldmap:
Set of functions to create country based world maps. Allows for
joining of user specified data and can display chloropleth, gridded,
bubble plot, bar charts, or pie charts. Data stored as `sp`
objects. Source on Google Code.
- tigris: Access US Census TIGER
shapefiles directly in R. This package is currently in active
development.
- USAboundaries:
provides spatial objects with the boundaries of states or counties
in the United States of America from 1629 to 2000. It provides data
from the Atlas of Historical County Boundaries.
- UScensus2010:
Functions to facilitate accessing data from the 2010 US Census using
a suite of packages. Includes spatial data for census geographies
(e.g. tracts, blocks, block groups, etc.). This packages is the
third in a series of related package suites:
UScensus1990blkgrp
and
UScensus2000.
CRAN packages:
Related links:
