plot a surface map for ocean data

Description

This function uses ggplot to make a surface map to visualize ocean science data. It is not suitable for terrestrial data because the land map is plotted above the data points. Land map data is contained in the package mapdata. Ocean bathymetry is optionally plotted and data is retrieved from NOAA with a call to marmap::getNOAA.bathy(); alternatively, bathymetry data can be supplied as an existing object of class bathy.

Arguments

bathymetry = FALSE – can be logical (i.e. should a bathymetry be plotted) or the name of an object of class bathy

keep = FALSE – keep downloaded bathymetry in the current wd? only relevant with bathymetry=TRUE

lon.min, lon.max, lat.min, lat.max – map limits, if not supplied the range of lats and lons will be slightly extended

lats, lons – latitude and longitude of data

values – optional, data values

value.name – optional, name for the data legend

Example

normal plot

p1 <- plot_map(
    bathymetry = TRUE,
    keep = FALSE,
    lon.min = 112,
    lon.max = 118,
    lat.min = 16,
    lat.max = 24,
    lats = seq(22, 17, length.out = 10),
    lons = seq(114, 116, length.out = 10),
    values = rnorm(10),
    value.name = "example [unit]"
)

## Registered S3 methods overwritten by 'adehabitatMA':
##   method                       from
##   print.SpatialPixelsDataFrame sp  
##   print.SpatialPixels          sp

## Querying NOAA database ...

## This may take seconds to minutes, depending on grid size

## Building bathy matrix ...

p1

because the result is a ggplot, it can be extended with additional layers, and the theme can be changed

p1 +
    annotate("text", x = 115, y = 22, label = "some\ntext", size = 4, fontface = "bold") +
    geom_point(aes(x = c(116, 116.5, 117), y = c(22, 22, 22)), col = "red", size = 4) +
    theme_dark()

plot with bathy object supplied

plot_map(
    bathymetry = marmap::getNOAA.bathy(lon1 = 114, lon2 = 116, lat1 = 18, lat2 = 20, resolution = 1),
    keep = FALSE,
    lon.min = 112,
    lon.max = 118,
    lat.min = 16,
    lat.max = 24,
    lats = seq(22, 17, length.out = 10),
    lons = seq(114, 116, length.out = 10),
    values = rnorm(10),
    value.name = "example [unit]")

## Querying NOAA database ...

## This may take seconds to minutes, depending on grid size

## Building bathy matrix ...

bounding box not fully supplied

plot_map(
    lon.min = -59, 
    lat.max = -33,
    lats = seq(-35.5, -37.5, length.out = 10),
    lons = seq(-56.5, -52, length.out = 10),
    values = rnorm(10),
    value.name = "example [unit]"
)

plot with categorical values

plot_map(
    lon.min = -59, 
    lat.max = -33,
    lats = seq(-35.5, -37.5, length.out = 10),
    lons = seq(-56.5, -52, length.out = 10),
    values = c(rep("cat1", 3), rep("cat2", 7)),
    value.name = "category")

the function can also be used to make an empty

p1 <- plot_map(lon.min = -5, lon.max = 15, lat.min = 50, lat.max = 60)
p1

… which can then be filled with data

p1 + geom_point(aes(seq(2, 9, length.out = 10), seq(52, 58, length.out = 10), col = rnorm(10)))