QuickPointMapping

Report
Quick maps in R
Melanie Frazier, NCEAS
Presentation materials here:
http://nceas.ucsb.edu/~frazier/RSpatialGuides/ggmap/
Have Lat/Long data?
And, you want to see where they are
Data from the EPA’s WestuRe project:
http://www.epa.gov/wed/pages/models/WestuRe/WestuRe.htm
2
Many options: But we’ll stick with 2
library(plotKML)
library(ggmap)
ggmap
Part 1
Part 2
Download the
map raster
Overlay data
onto raster
Refer to Quickstart guide:
4
ggmap: Part 1 (getting the map)
A. Specify coordinates
- geocode
myLocation <- “University of Washington”
- Lat/Long
myLocation <- c(lon=-95.36, lat=29.76)
- Bounding box
(lowerleftlon, lowerleftlat,
upperrightlon, upperrightlat)
myLocation <- c(-130, 30, -105, 50)
[NOTE: glitchy for google maps]
5
ggmap: Part 1 (getting the map)
B. Define map source, maptype, and color
maptype = watercolor toner terrain
source
stamen
terrain
satellite
roadmap
hybrid
google
color
osm
(and, cloudmade)
can do any of
the maps in
“bw”
6
ggmap: Part 1 (getting the map)
B. Define map source, maptype, and color
Scale matters in regard to map source/type
7
ggmap: Part 1 (getting the map)
B. get_map function provides a general
approach for quickly getting maps
myMap <- get_map(location = myLocation,
source = “stamen”,
maptype = “watercolor”,
color = “bw”)
Additional options such as “zoom” and “crop”
?ggmap
ggmap: Part 1 (getting the map)
Sometimes get_map doesn’t provide the
control needed to get the map you want.
In this case, use the specific functions
designed for the different map sources:
get_googlemap
get_openstreetmap
get_stamenmap
get_cloudmademap
ggmap: Part 2 (overlaying your data)
A. Plot the raster
ggmap(myMap)
B. Get your lat/long point data:
myData <read.csv(“http://nceas.ucsb.edu/~frazier/RSpatialG
uides/ggmap/EstuaryData.csv”)
C. Add points (ggplot2 syntax)
ggmap(myMap)+
geom_point(aes(x=estLongitude, y=estLatitude),
data=myData, alpha=0.5,
color=“darkred”, size=3)
ggmaps: Part 2
ggmaps: Part 2
ggmap: Additional options
plotKML
plotKML
Tutorial:
http://gsif.isric.org/doku.php?id=wiki:tutorial_plotkml
Load libraries:
library(plotKML)
library(sp)
Convert to spatial dataframe object:
coordinates(myData) <- ~estLongitude+estLatitude
Provide the projection (just copy this):
proj4string(myData) <- CRS("+proj=longlat +datum=WGS84")
Make the plot:
plotKML(myData, colour="lnEstArea", balloon=TRUE)
Questions
Presentation materials here:
http://nceas.ucsb.edu/~frazier/RSpatialGuides/ggmap/

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