library(moveVis) library(move)

data("move_data")

align movement to unique times and regular resolution

m.aligned <- align_move(move_data, res = 4, unit = "mins") m.split <- split(m.aligned)

let's use the first individual and colour it by behavioral segment

ts.m <- timestamps(m.split[[1]])

define behavioral change points and assoicate the segment with colours

cp.m <- list(green = min(ts.m), red = as.POSIXct("2018-05-15 12:00:00", tz = "UTC"), blue = as.POSIXct("2018-05-15 14:00:00", tz = "UTC"), orange = as.POSIXct("2018-05-15 16:00:00", tz = "UTC"))

iterate through change points and assign colours for segments between change points

col.m <- unlist(mapply(x = cp.m, y = c(cp.m[2:length(cp.m)], max(ts.m)), col = names(cp.m), function(x, y, col){ rep(col, length(which(ts.m >= x & ts.m < y))) }, SIMPLIFY = F, USE.NAMES = F))

add colour for the last timestamp to match lengths

col.m <- c(col.m, tail(col.m, n = 1))

assign colour column, which is recoginced by moveVis

m.split[[1]]$colour <- col.m

for the other individual, let's use static colours wihout changes

m.split[[2]]$colour <- rep("orange", nrow(m.split[[2]])) m.split[[3]]$colour <- rep("purple", nrow(m.split[[3]]))

stack the move split back together

m.stack <- moveStack(m.split)

create frames and disable path legend

legend would assoicate initial path colours with individual names: makes no sense, since colours for individual 1 are changing over time

frames <- frames_spatial(m.stack, map_service = "osm", map_type = "terrain_bg", path_legend = F)

check frame 80 to see, how individual 1 transits in colour

frames[[80]]

animate frames

animate_frames(frames, out_file = "animation.mov", overwrite = T)