tools.ctv

<CRANTaskView>

<name>MappingTools</name>
<topic>Mapping tools and services</topic>
<maintainer email="hollister.jeff@epa.gov">Jeff Hollister, Scott Chamberlain,
    Karthik Ram, Hadley Wickham, Ben Marwick, Cory Nissen</maintainer>
<version>2015-07-04</version>

<info> 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 <a href="https://github.com/ropensci/maptools/issues">
submit an issue</a>, or <a href="https://github.com/ropensci/maptools/CONTRIBUTING.md">
make some changes</a> and <a href="https://github.com/ropensci/maptools/pulls">
submit a pull request</a>. If you can't contribute on Github,
<a href="mailto:hollister.jeff@epa.gov">send Jeff an email</a>. 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 <view>Spatial Task View</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.

<h2>
Mapping tools in R
</h2>

<p><strong>Visualization</strong></p>
<ul>
<li>
  <a href="https://github.com/Vizzuality/cartodb-r">cartodb</a>: CartoDB R client.
  Not on CRAN, and hasn't been active for a while.
    <a href="https://github.com/Vizzuality/cartodb-r">Source on Github</a>
</li>
<li>
  <a href="https://github.com/ropensci/cartographer">cartographer</a>: Interactive
  maps in R using <a href="https://github.com/emeeks/d3-carto-map">d3-carto-map</a>.
  <a href="https://github.com/ropensci/cartographer">Source on Github</a>
</li>
<li>
  <pkg>ggmap</pkg>: Visualization of spatial data and models on top of Google Maps,
  OpenStreetMaps, Stamen Maps, or CloudMade Maps using ggplot2.
  <a href="https://github.com/dkahle/ggmap">Source on Github</a>
</li>
<li>
  <pkg>leaflet</pkg>: Client for the JavaScript library Leaflet.js.  Uses <pkg>htmlwidgets</pkg> 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 <pkg>shiny</pkg> apps.  <a href="https://github.com/rstudio/leaflet">Source on Github</a>
</li>
<li>
  <pkg>leafletR</pkg>: Another client for the JavaScript library Leaflet.js. Basic mapping
    functionality to combine vector data and online map tiles from different
    sources. <a href="https://github.com/chgrl/leafletR">Source on Github</a>
</li>
<li>
  <pkg>mapview</pkg>: This package provides wrappers to the <pkg>leaflet</pkg> package that simplifies the creation of maps.  Stated purpose of the package is to facilitate interactive viewing of spatial data in R.
  <a href="https://github.com/environmentalinformatics-marburg/mapview">Source on
  Github.</a>
</li>
<li>
  <pkg>micromap</pkg>: This group of functions simplifies the creation of linked
  micromap plots, and uses ggplot2 plotting framework.
  <a href="https://github.com/USEPA/R-micromap-package-development">Source on
  Github.</a>
</li>
<li>
  <pkg>OpenStreetMap</pkg>: An R client for fetching raster images via the Open Street Maps API.
</li>
<li>
  <pkg>plotGoogleMaps</pkg>: 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.
</li>
<li>
  <pkg>quickmpar</pkg>: Quick visualization of <pkg>sp</pkg> and <pkg>raster</pkg> objects.  Provides basic interactivity including zooming and panning as well as identifying features.
  <a href="https://github.com/jhollist/quickmapr">Source on Github</a>
</li>
<li>
  <pkg>rasterVis</pkg>: Package for enhanced visualization of raster data.
  <a href="https://github.com/oscarperpinan/rastervis/">Source on Github</a>
</li>
<li>
  <pkg>Rgooglemaps</pkg>: Query Google static maps, and use the map as a background
  image to overlay plots within R.
  <a href="https://github.com/markusloecher/RgoogleMaps">Source on Github</a>
</li>
<li>
  <a href="https://github.com/ramnathv/rMaps">rMaps</a>: A general purpose wrapper
  around main Javascript mapping libraries, including
  <a href="http://leafletjs.com/">Leaflet</a>,
  <a href="http://datamaps.github.io/">Datamaps</a>, and
  <a href="http://sztanko.github.io/crosslet/">Crosslet</a>.
  <a href="https://github.com/ramnathv/rMaps">Source on Github</a>
</li>
<li>
  <pkg>sp</pkg>: Core spatial package in R with basic spatial data manipulation methods. Most spatial analysis packages reuse the classes and methods provided by [sp](http://cran.r-project.org/web/packages/sp/index.html). Plotting capability in [sp](http://cran.r-project.org/web/packages/sp/index.html) is provided through plot methods. More advanced plotting based on <pkg>lattice</pkg>.
  <a href="https://github.com/edzer/sp/">Source on GitHub</a>
</li>
<li>
  <pkg>tmap</pkg>: Package provides an approach to build thematic maps (e.g. chloropleth or bubble maps).  Utilizes a grammar of graphics syntax.
  <a href="https://github.com/mtennekes/tmap">Source on GitHub</a>
</li>
</ul>

<p><strong>Projecting Data</strong></p>
<p>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](https://www.nceas.ucsb.edu/~frazier/RSpatialGuides/OverviewCoordinateReferenceSystems.pdf).  This more general discussion of projection from the [USGS](http://egsc.usgs.gov/isb//pubs/MapProjections/projections.html) is also good.</p>

<p>Once you know that you need to transform you data there are several options:</p>
<ul>
<li>
  <pkg>sp</pkg>: The function <code>spTransform</code> (and methods in
  <pkg>rgdal</pkg>) is the workhorse function for spatial transformations of
  vector data and it uses [PROJ.4](http://trac.osgeo.org/proj/) arguments to
  specify the transformations.  Accepted inputs are provided by the spTransform
  methods in <pkg>rgdal</pkg>.   <a href="https://github.com/edzer/sp/"> Source for <code>sp</code> on GitHub</a>. <a href="https://r-forge.r-project.org/projects/rgdal/"> Source for <code>rgdal</code> on R-Forge</a>.
</li>
  <pkg>raster</pkg>: Use <code>rasterProject()</code> to project rasters.
  Projecting rasters is a bit different than vector as the transformation results
  in a rotated grid which require some interpolation to map the original cell
  values to the new cell values. Dealing with this requires a separate function
  and <code>rasterProject()</code> has options for dealing with the interpolation.
<li>
  <pkg>mapproj</pkg>: This package provides a function to convert two vectors
  representing longitude (x) and  latitude (y) to projected coordinates.
</li>
<li>
  <pkg>PBSmapping</pkg>: The function <code>convUL</code> will transform
  coordinates between Universal Transverse Mercator (UTM) and longitude-latitude.
  A data frame with a <code>projection</code> attribute is required input.
  <a href="http://code.google.com/p/pbs-software/">Source on Google Code</a>
</li>
</ul>

<p><strong>Geocoding</strong></p>
<p>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.</p>
<ul>
<li>
  <pkg>geocodeHERE</pkg>: Client for Nokia's
  <a href="https://developer.here.com/geocoder">HERE geocoding API</a>.
  <a href="https://github.com/corynissen/geocodeHERE/">Source on GitHub</a>
</li>
<li>
  <pkg>ggmap</pkg>: The function <code>geocode</code> in <pkg>ggmap</pkg> uses
  the <a href="https://developers.google.com/maps/documentation/geocoding/?csw=1">Google Geocoding API</a>.
  <a href="https://github.com/dkahle/ggmap">Source on Github</a>
</li>
<li>
  <a href="https://github.com/trestletech/rydn">rydn</a>: Client for the Yahoo!
  Developers Network <a href="https://developer.yahoo.com/boss/">BOSS PlaceFinder API</a>.
  <a href="https://github.com/trestletech/rydn">Source on Github</a>
</li>
</ul>

<p><strong>Map Data</strong></p>
<p>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 <view>Analysis of Spatial Data Task View</view>, thus this list will focus on additional sources or features not discussed in that task view.  </p>
<ul>

<li>
   <pkg>geojsonio</pkg>: Provides utility for working with geojson data in R.  Includes functions to convert sp objects, lists, and character to geojson format.
</li>
<li>
  <pkg>geonames</pkg>: functions for working with
  <a href="http://www.geonames.org/">geonames</a>, a geographical database that
  covers all countries and contains over eight million place names
</li>
<li>
  <pkg>maps</pkg>: 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 <pkg>sp</pkg>, <pkg>ggmap</pkg>, etc.  Code for
  projections and additional maps in packages <pkg>mapproj</pkg> <pkg>mapdata</pkg>.
</li>
<li>
    <a href="https://github.com/sckott/openadds">openadds</a>: An R client for <a href="http://openaddresses.io">Openaddresses</a>.  The Openaddresses data comes in a variety of formats and this package provides common interface to simplify working with it in R.
    <a href="https://github.com/sckott/openadds">Source on Github</a>
</li>
<li>
  <pkg>osmar</pkg>: Package for interacting with the Open Street Map API in R.
  Functions for converting an open street map object into <pkg>sp</pkg> or
  <pkg>igraph</pkg> objects.
  <a href="https://r-forge.r-project.org/projects/osmar/">Source on R-Forge.</a>
</li>
<li>
  <a href="https://github.com/ropensci/prism">prism</a>: Accesses climate data from [PRSIM](http://www.prism.oregonstate.edu/). Also provides some basic plotting and mapping functions.
</li>
<li>
  <pkg>rworldmap</pkg>: 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.
  <a href="https://code.google.com/p/rworld/downloads/list">Source on Google Code.</a>
</li>
<li>
  <a href="https://github.com/walkerke/tigris">tigris</a>: Access US Census TIGER shapefiles directly in R.  This package is currently in active development.
</li>
<li>
  <pkg>USAboundaries</pkg>: 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.
</li>
<li>
  <pkg>UScensus2010</pkg>: 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: <pkg>UScensus1990blkgrp</pkg> and <pkg>UScensus2000</pkg>.    
</li>

</ul>

</info>

<packagelist>
  <pkg priority="core">sp</pkg>
{{#pkgs}}
  <pkg>{{package}}</pkg>
{{/pkgs}}
</packagelist>

<links>
  <a href="http://cran.r-project.org/web/views/Spatial.html">Analysis of Spatial Data Task View</a>
</links>

</CRANTaskView>