| Title: | Argos Locations Filter |
|---|---|
| Description: | Filters animal satellite tracking data obtained from the Argos system(<https://www.argos-system.org/>), following the algorithm described in Freitas et al (2008) <doi:10.1111/j.1748-7692.2007.00180.x>. It is especially indicated for telemetry studies of marine animals, where Argos locations are predominantly of low-quality. |
| Authors: | Carla Freitas [aut, cre] |
| Maintainer: | Carla Freitas <[email protected]> |
| License: | GPL (>= 2) |
| Version: | 0.70 |
| Built: | 2024-12-17 06:37:43 UTC |
| Source: | CRAN |
Function bearing calculates the bearing, in degrees, between two geographical locations.
Function bearingTrack calculates the bearing between a sequence of locations.
bearing(lat1, lat2, lon1, lon2) bearingTrack(lat, lon)bearing(lat1, lat2, lon1, lon2) bearingTrack(lat, lon)
lat1 |
latitude of the first location, in decimal degrees |
lat2 |
latitude of the second location, in decimal degrees |
lon1 |
longitude of the first location, in decimal degrees |
lon2 |
longitude of the second location, in decimal degrees |
lat |
vector of latitudes, in decimal degrees |
lon |
vector of longitudes, in decimal degrees |
Bearings are calculated using spherical trigonometry. Formulas are given in Zwillinger (2003).
bearing returns the bearing, in degrees, between the first location and
the second location. 0 is North. bearingTrack returns a vector of bearings between the sequence
of locations.
Carla Freitas
Zwillinger D. (2003) Standard Mathematical Tables and Formulae, 31st edition. Chapman & Hall/CRC, Boca Raton, FL.
# Bearing between two geographical locations: lat1<-rnorm(1,80) lat2<-rnorm(1,80) lon1<-rnorm(1,20) lon2<-rnorm(1,20) bearing(lat1,lat2,lon1,lon2) # Bearing between a sequence of 10 geographical locations: lat<-rnorm(10,80) lon<-rnorm(10,20) bearingTrack(lat,lon)# Bearing between two geographical locations: lat1<-rnorm(1,80) lat2<-rnorm(1,80) lon1<-rnorm(1,20) lon2<-rnorm(1,20) bearing(lat1,lat2,lon1,lon2) # Bearing between a sequence of 10 geographical locations: lat<-rnorm(10,80) lon<-rnorm(10,20) bearingTrack(lat,lon)
Internal function for package argosfilter
This function is not to be called by the user.
No return value
Internal function for package argosfilter
This function is not to be called by the user.
No return value
Function distance calculates the distance, in km, between two geographical locations
following the great circle route.
Function distanceTrack calculates the distance, in km, between a sequence of locations.
distance(lat1, lat2, lon1, lon2) distanceTrack(lat,lon)distance(lat1, lat2, lon1, lon2) distanceTrack(lat,lon)
lat1 |
latitude of the first location, in decimal degrees |
lat2 |
latitude of the second location, in decimal degrees |
lon1 |
longitude of the first location, in decimal degrees |
lon2 |
longitude of the second location, in decimal degrees |
lat |
vector of latitudes, in decimal degrees |
lon |
vector of longitudes, in decimal degrees |
Distances are calculated using spherical trigonometry. See details on formulae in Zwillinger (2003).
distance returns the distance between the two locations.
distanceTrack returns a vector of distances between the sequence of locations.
In both cases, distances are given in km.
Carla Freitas
Zwillinger D. (2003) Standard Mathematical Tables and Formulae, 31st edition. Chapman & Hall/CRC, Boca Raton, FL.
# Distance between two geographical locations lat1<-rnorm(1,80) lon1<-rnorm(1,20) lat2<-rnorm(1,80) lon2<-rnorm(1,20) distance(lat1,lat2,lon1,lon2) # Distance between a sequence of 10 geographical locations: lat<-rnorm(10,80) lon<-rnorm(10,20) distanceTrack(lat,lon)# Distance between two geographical locations lat1<-rnorm(1,80) lon1<-rnorm(1,20) lat2<-rnorm(1,80) lon2<-rnorm(1,20) distance(lat1,lat2,lon1,lon2) # Distance between a sequence of 10 geographical locations: lat<-rnorm(10,80) lon<-rnorm(10,20) distanceTrack(lat,lon)
Internal function for package argosfilter
This function is not to be called by the user.
No return value
Internal function for package argosfilter
This function is not to be called by the user.
No return value
Converts degrees to radians
radian(degree)radian(degree)
degree |
vector of values in degrees |
Returns a vector of values in radians.
Carla Freitas
# Convert latitudes and longitudes from decimal degrees to radians lat<-rnorm(10,80) lon<-rnorm(10,20) lat_rad<-radian(lat) lon_rad<-radian(lon)# Convert latitudes and longitudes from decimal degrees to radians lat<-rnorm(10,80) lon<-rnorm(10,20) lat_rad<-radian(lat) lon_rad<-radian(lon)
This function filters location data obtained from Argos, using the Freitas et al. (2008) algorithm.
sdafilter(lat, lon, dtime, lc, vmax = 2, ang = c(15, 25), distlim = c(2500, 5000))sdafilter(lat, lon, dtime, lc, vmax = 2, ang = c(15, 25), distlim = c(2500, 5000))
lat |
a numeric vector of latitudes, in decimal degrees |
lon |
a numeric vector of longitudes, in decimal degrees |
dtime |
a vector of class POSIXct with date and time for each location |
lc |
a numeric or character vector of Argos location classes. Argos locations Z can be entered as "Z", "z" or -9 |
vmax |
speed threshold, in m/s. Default is 2 m/s |
ang |
angles of the spikes to be removed. Default is c(15,25). No spikes are removed if |
distlim |
lengths of the above spikes, in meters. Default is c(2500,5000) |
Locations are filtered using the algorithm described in Freitas et al. (2008).
The algorithm first removes all locations with location class Z (-9), which are
the points for which the location process failed. Then all locations requiring
unrealistic swimming speeds are removed, using the MacConnell et al. (1992) algorithm,
unless the point is located at less than 5 km from the previous location. This procedure enables retaining
good quality locations for which high swimming speeds result from location being taken
very close to each other in time. The default maximum speed threshold is 2 m/s.
The last step is optional, and enables to remove
unlikely spikes from the animal's path. The angles of the spikes should be specified
in ang, and their respective length in distlim. The default
is c(15,25) for ang and c(2500,5000) for distlim, meaning that all spikes
with angles smaller than 15 and 25 degrees will be removed if their extension is higher than
2500 m and 5000 m respectively. No spikes are removed if ang=-1. ang
and distlim vectors must have the same length.
Returns a vector with the following elements: "removed" (location removed by the filter),
"not" (location not removed) and "end_location" (location at the end
of the track where the algorithm could not be applied).
Carla Freitas, with contributions from Anne Goarant and Catriona MacLeod
Freitas, C., Lydersen, C., Ims, R.A., Fedak, M.A. and Kovacs, K.M. (2008) A simple new algorithm to filter marine mammal Argos locations Marine Mammal Science 24:315-325.
McConnell, B.J., Chambers, C. and Fedak, M.A. (1992) Foraging ecology of southern elephant seals in relation to the bathymetry and productivity of the Southern Ocean. Antarctic Science 4:393-398.
data(seal) lat<-seal$lat lon<-seal$lon dtime<-seal$dtime lc<-seal$lc # plot unfiltered data plot(lon,lat,col="lightgrey",type="l",xlim=c(5,18), ylim=c(77.1,79.1),xlab="Longitude",ylab="Latitude") # filter by speed only mfilter<-vmask(lat,lon,dtime,2) mfilter[1:10] lines(lon[which(mfilter=="not")],lat[which(mfilter=="not")],col="red") # filter data using sdafilter cfilter<-sdafilter(lat, lon, dtime, lc) cfilter[1:20] lines(lon[which(cfilter=="not")],lat[which(cfilter=="not")],col="blue") # check number of locations (by location class) removed by each filter table(lc,mfilter) table(lc,cfilter)data(seal) lat<-seal$lat lon<-seal$lon dtime<-seal$dtime lc<-seal$lc # plot unfiltered data plot(lon,lat,col="lightgrey",type="l",xlim=c(5,18), ylim=c(77.1,79.1),xlab="Longitude",ylab="Latitude") # filter by speed only mfilter<-vmask(lat,lon,dtime,2) mfilter[1:10] lines(lon[which(mfilter=="not")],lat[which(mfilter=="not")],col="red") # filter data using sdafilter cfilter<-sdafilter(lat, lon, dtime, lc) cfilter[1:20] lines(lon[which(cfilter=="not")],lat[which(cfilter=="not")],col="blue") # check number of locations (by location class) removed by each filter table(lc,mfilter) table(lc,cfilter)
Satellite tracking data from a ringed seal tagged in Svalbard, Norway. Data were provided by C. Lydersen and K. M. Kovacs (Norwegian Polar Institute).
data(seal)data(seal)
A data frame with 1561 observations on the following 4 variables.
dtimea vector of class POSIXt with date and time for each location
lata numeric vector with latitudes, in decimal degrees
lona numeric vector with longitudes, in decimal degrees
lca numeric vector with location classes LC (-9 refers to LC Z, -2 to LC B and -1 to LC A)
data(seal) lat<-seal$lat lon<-seal$lon # plot unfiltered data plot(lon,lat)data(seal) lat<-seal$lat lon<-seal$lon # plot unfiltered data plot(lon,lat)
This function filters location data obtained from Argos, using the MacConnell al. (1992) algorithm.
vmask(lat, lon, dtime, vmax)vmask(lat, lon, dtime, vmax)
lat |
a numeric vector of latitudes, in decimal degrees |
lon |
a numeric vector of longitudes, in decimal degrees |
dtime |
a vector of class POSIXct with date and time for each location |
vmax |
speed threshold, in m/s |
Locations are filtered using the algorithm described in MacConnell et al. (1992). Since this algorithm calculates for each location the root mean square (rms) of the speeds to the previous, 2nd previous, next and 2nd next location, high swimming speeds can be obtained for points that are adjacent to outlier locations. Therefore, when the algorithm is applied to a set of locations, only the peaks in rms (that are above the maximum speed) are removed. Other locations are not removed even if above the speed limit. rms is then recalculated n times until all locations are below the speed threshold.
Returns a vector with the following elements: "removed" (location removed by the filter),
"not" (location not removed) and "end_location" (location at the end
of the track where the algorithm could not be applied).
Carla Freitas
McConnell, B.J., Chambers, C. and Fedak, M.A. (1992) Foraging ecology of southern elephant seals in relation to the bathymetry and productivity of the Southern Ocean. Antarctic Science 4:393-398.
data(seal) lat<-seal$lat lon<-seal$lon dtime<-seal$dtime lc<-seal$lc # filter by speed mfilter<-vmask(lat,lon,dtime,2) # plot unfiltered (grey) and filtered data (green) plot(lon,lat,col="lightgrey",type="l",xlim=c(5,18), ylim=c(77.1,79.1),xlab="Longitude",ylab="Latitude") lines(lon[which(mfilter=="not")],lat[which(mfilter=="not")],col="darkgreen")data(seal) lat<-seal$lat lon<-seal$lon dtime<-seal$dtime lc<-seal$lc # filter by speed mfilter<-vmask(lat,lon,dtime,2) # plot unfiltered (grey) and filtered data (green) plot(lon,lat,col="lightgrey",type="l",xlim=c(5,18), ylim=c(77.1,79.1),xlab="Longitude",ylab="Latitude") lines(lon[which(mfilter=="not")],lat[which(mfilter=="not")],col="darkgreen")