ggplot_geopos: Reads and plots geolocation estimates derived from archival...

In RchivalTag: Analyzing and Interactive Visualization of Archival Tagging Data

Reads and plots geolocation estimates derived from archival tagging data

Description

Geolocations provided via CSV or data frames are plotted as line or scatter plots. If netCDF (.nc) or KMZ files from the Wildlife Computers portal are selected, a SpatialPolygonsDataFrame is created and surface probability maps are illustrated. The netCDF transformation follows the R-code in the Location Processing User Guide. KMZ files already include contour lines of the 50, 95, and 99% likelihood areas, which are extracted and transformed to a SpatialPolygonsDataFrame.

Usage

ggplot_geopos(x, ggobj, xlim, ylim, zlim, standard_year=FALSE, 
              full_year=standard_year, date_format, lang_format="en", tz="UTC", 
              Breaks, cb.title, cb.date_format, cbpos, cb.height = 10, cb.xlab = "",
              cb.reverse=FALSE, pal.reverse=cb.reverse, prob_lim=.75, color_by="date", 
              pal, alpha=70, type="p",
              main ,lwd=1, size=2, shape=19, verbose= FALSE, ...)

get_geopos(x, xlim, ylim, date_format, lang_format="en", tz="UTC", 
           proj4string, prob_lim=.5, verbose=TRUE)

Arguments

x	data.frame containing horizontal position records, or a path/filename of .csv, .kmz, .kml, or .nc-files.
ggobj	A ggplot object (optional base plot).
xlim, ylim	Numeric vectors defining the limits of the x- and y-axes.
zlim, Breaks, standard_year, full_year	Date range and breaks of the colorbar. If standard_year = TRUE, positions are standardized yearly and tick breaks are ignored. If full_year = TRUE, the color scale covers all months from January to December.
date_format, lang_format, tz	character strings indicating the date format, language format and the corresponding time zone, defined by the vectors Date and Time (by default: date_format="%d-%b-%Y %H:%M:%S", lang_format="en", tz='UTC') If formatting fails, please check as well the input language format, defined by lang_format (and use abbrviations such as "en" for English,"es" for Spanish, "fr" for French, etc.) as well.
proj4string	Coordinate reference system (CRS; projection).
cb.title	Title of the colorbar (default "Date").
cb.date_format	Date format of the colorbar ticks (default "%Y-%m-%d").
cbpos, cb.xlab, cb.height	Position, x-axis label, and height of the colorbar.
prob_lim	For kmz, kml, or netCDF (.nc) files, defines the probability surface limit in %. Default 50%. Valid KMZ/KML values: 50, 95, 99.
color_by	Column or vector used for coloring geolocations (default "date").
pal	Color map used for polygon (.nc) or scatter plots. See cmap for pre-installed color maps.
cb.reverse, pal.reverse	Inverse order of ticks and colormap of colorscale.
alpha	Transparency of polygons or dots in percent (default 70).
type	Plot type: "p" for points (default), "l" for lines, "b" for both.
size, shape	Point size and type (default 2 and 19 for solid dots).
lwd	Line width.
...	Additional arguments passed to ggplotmap.
main	Overall plot title.
verbose	Whether file names should be printed when loading geolocation files (default TRUE for get_geopos(), FALSE for ggplot_geopos()).

Author(s)

Robert K. Bauer

See Also

leaflet_geopos, ggplotly_geopos, ggplotmap, SpatialPolygonsDataFrame

Examples

# Example 1a: Line plot from CSV
# library(oceanmap)
# csv_file <- system.file("example_files/15P1019-104659-1-GPE3.csv", package="RchivalTag")
# pos <- get_geopos(csv_file)
# ggobj <- ggplot_geopos(pos)
# ggobj
# ggplotly_geopos(ggobj)

# Example 1b: Scatter plot on existing landmask
# ggobj <- oceanmap::ggplotmap("lion", grid.res=5)
# ggobj4 <- ggplot_geopos(csv_file, ggobj)
# ggplotly_geopos(ggobj4)

# Example 2: Probability surfaces from netCDF
# nc_file <- system.file("example_files/15P1019-104659-1-GPE3.nc", package="RchivalTag")
# ggobj6 <- ggplot_geopos(nc_file)
# ggplotly_geopos(ggobj6)

# Example 3: Probability surfaces from KMZ
# kmz_file <- system.file("example_files/15P1019-104659-1-GPE3.kmz", package="RchivalTag")
# ggobj7 <- ggplot_geopos(kmz_file)
# ggplotly_geopos(ggobj7)

RchivalTag documentation built on Nov. 6, 2025, 1:18 a.m.