Importing Google Maps to Plot Data- Kait Farrell

Skills Sharing: Importing Google Maps directly into R to visualize data

Why use this skill?

• Visually show differences between sampling locations based on some other parameter of interest
• Directly import maps from Google Maps or OpenStreet Map- ArcGIS not required (does require internet connection)
• Minimal coding needed to execute

R Package involed

• ggmap
• ggplot2

Challenges

• Adjusting map parameters to show focal area most effectively

Zoom ranges from 3 (continent) to 21 (building), default value 10 (city)

• Obtaining code to fine-tune plot outputs (similar to ggplot)

Details shown in code below include:

• Superimposing points from data file (ex. 'data') based on sampling lat/long where color and size both vary by discharge ('Q')
• Defining color scales and limits
• Defining size scale for plotted points

Example code

# Load relevant packages
library(ggplot2)
library(ggmap)

# Import dataset to superimpose over map
data <- read.csv("C:\\Users\\FarrellKJ\\Documents\\R\\mean_depth.csv", header = TRUE)

# Pull map from Google (e.g., location = c('Sunappe, NH') or specified lat/long (as below)
map <- get_map(location = c(lon = -83.44, lat = 35.05), zoom = 14, maptype = c('hybrid'))

# Plot map- 2013 Q
ggmap(map)
+ geom_point(aes(x = lat, y = long, colour=Q, size=Q), data = data)
+ scale_colour_continuous(name='Discharge (L/s)',limits=c(0,1000), low = "yellow", high = "red", space = "Lab", guide = "colorbar")
+ scale_size(guide='none', range= c(2,12), limits=c(0,1000), breaks=c(5, 50, 100, 400, 800))

Example plot based on code above, showing changes in discharge along a stream network