library("sf")Linking to GEOS 3.11.0, GDAL 3.5.3, PROJ 9.1.0; sf_use_s2() is TRUElibrary("dplyr")
Attaching package: 'dplyr'The following objects are masked from 'package:stats':
filter, lagThe following objects are masked from 'package:base':
intersect, setdiff, setequal, unionlibrary("readr")
library(ggplot2)wildschwein <- read_delim("wildschwein_BE_2056.csv", ",")Rows: 51246 Columns: 6
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (2): TierID, TierName
dbl (3): CollarID, E, N
dttm (1): DatetimeUTC
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.ruth <- wildschwein |>
st_as_sf(coords = c("E", "N"), crs = 2056, remove = FALSE) |> # remove = F Keeps "E" and "N" columns
filter(
TierName == "Ruth",
DatetimeUTC >= "2015-07-01",
DatetimeUTC < "2015-07-03"
)Visualize
ggplot(ruth) +
geom_sf() +
geom_path(aes(E,N))
Fixes are taken every 15 minutes. Calculate: pos[n-3] to pos[n] pos[n-2] to pos[n] pos[n-1] to pos[n] pos[n] to pos[n+1] pos[n] to pos[n+2] pos[n] to pos[n+3]
Function
distance_by_element <- function(later, now) {
as.numeric(
st_distance(later, now, by_element = TRUE)
)
}Store distances
ruth <- ruth |>
mutate(
nMinus3 = distance_by_element(lag(geometry, 3), geometry), # distance to pos -45 minutes
nMinus2 = distance_by_element(lag(geometry, 2), geometry), # distance to pos -30 minutes
nMinus1 = distance_by_element(lag(geometry, 1), geometry), # distance to pos -15 minutes
nPlus1 = distance_by_element(geometry, lead(geometry, 1)), # distance to pos +15 mintues
nPlus2 = distance_by_element(geometry, lead(geometry, 2)), # distance to pos +30 minutes
nPlus3 = distance_by_element(geometry, lead(geometry, 3)) # distance to pos +45 minutes
)Calculate mean distance
ruth <- ruth |>
rowwise() |> # rowwise, because it cannot be calculated for rows with NAs
mutate(
stepMean = mean(c(nMinus3, nMinus2, nMinus1, nPlus1, nPlus2, nPlus3))
) |>
ungroup()
ruthSimple feature collection with 180 features and 13 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 2568161 ymin: 1205617 xmax: 2570123 ymax: 1207095
Projected CRS: CH1903+ / LV95
# A tibble: 180 × 14
TierID TierName CollarID DatetimeUTC E N
<chr> <chr> <dbl> <dttm> <dbl> <dbl>
1 018A Ruth 13974 2015-06-30 22:01:14 2570123. 1206473.
2 018A Ruth 13974 2015-06-30 22:15:32 2570031. 1206402.
3 018A Ruth 13974 2015-06-30 22:31:41 2569584. 1206247.
4 018A Ruth 13974 2015-06-30 22:46:38 2569207. 1206117.
5 018A Ruth 13974 2015-06-30 23:01:46 2568947. 1206275.
6 018A Ruth 13974 2015-06-30 23:16:39 2568911. 1206339.
7 018A Ruth 13974 2015-06-30 23:30:22 2568992. 1206293.
8 018A Ruth 13974 2015-06-30 23:45:09 2568914. 1206338.
9 018A Ruth 13974 2015-07-01 00:00:13 2568906. 1206297.
10 018A Ruth 13974 2015-07-01 00:15:41 2568951. 1206308.
# ℹ 170 more rows
# ℹ 8 more variables: geometry <POINT [m]>, nMinus3 <dbl>, nMinus2 <dbl>,
# nMinus1 <dbl>, nPlus1 <dbl>, nPlus2 <dbl>, nPlus3 <dbl>, stepMean <dbl>summary(ruth) TierID TierName CollarID
Length:180 Length:180 Min. :13974
Class :character Class :character 1st Qu.:13974
Mode :character Mode :character Median :13974
Mean :13974
3rd Qu.:13974
Max. :13974
DatetimeUTC E N
Min. :2015-06-30 22:01:14.0 Min. :2568162 Min. :1205617
1st Qu.:2015-07-01 09:27:08.5 1st Qu.:2568471 1st Qu.:1205917
Median :2015-07-01 22:23:19.0 Median :2568877 Median :1206042
Mean :2015-07-01 22:03:18.7 Mean :2568801 Mean :1206102
3rd Qu.:2015-07-02 10:35:05.5 3rd Qu.:2568919 3rd Qu.:1206090
Max. :2015-07-02 21:46:01.0 Max. :2570123 Max. :1207095
geometry nMinus3 nMinus2
POINT :180 Min. : 0.7328 Min. : 0.3887
epsg:2056 : 0 1st Qu.: 5.3496 1st Qu.: 4.7802
+proj=some...: 0 Median : 21.6565 Median : 15.6777
Mean : 146.1967 Mean : 108.7790
3rd Qu.: 137.1378 3rd Qu.: 71.0626
Max. :1370.0820 Max. :1339.5191
NA's :3 NA's :2
nMinus1 nPlus1 nPlus2
Min. : 0.1296 Min. : 0.1296 Min. : 0.3887
1st Qu.: 4.4568 1st Qu.: 4.4568 1st Qu.: 4.7802
Median : 11.6751 Median : 11.6751 Median : 15.6777
Mean : 64.5200 Mean : 64.5200 Mean : 108.7790
3rd Qu.: 48.0356 3rd Qu.: 48.0356 3rd Qu.: 71.0626
Max. :1155.2635 Max. :1155.2635 Max. :1339.5191
NA's :1 NA's :1 NA's :2
nPlus3 stepMean
Min. : 0.7328 Min. : 1.708
1st Qu.: 5.3496 1st Qu.: 6.348
Median : 21.6565 Median : 23.815
Mean : 146.1967 Mean : 95.157
3rd Qu.: 137.1378 3rd Qu.:109.299
Max. :1370.0820 Max. :757.062
NA's :3 NA's :6 ggplot(ruth, aes(x = stepMean)) +
geom_histogram()`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.Warning: Removed 6 rows containing non-finite outside the scale range
(`stat_bin()`).
ggplot(ruth, aes(y = stepMean)) +
geom_boxplot()Warning: Removed 6 rows containing non-finite outside the scale range
(`stat_boxplot()`).
Static points defined as the points for which stepMean is smaller than the average stepMean.
ruth <- ruth |>
mutate(static = stepMean < mean(stepMean, na.rm = TRUE))ruth |>
ggplot(aes(E, N, colour = static)) +
geom_path() +
geom_point() +
coord_fixed() +
theme(legend.position = "bottom")
Function to assign ID to segments
rle_id <- function(vec) { #Input is a vector of the data frame (e.g. static)
x <- rle(vec)$lengths
as.factor(rep(seq_along(x), times = x))
}Assign segement IDs to ruth
ruth <- ruth |>
mutate(segment_id = rle_id(static))Visualize moving segments colorizing segment IDs
ruth_filter <- ruth |>
filter(!static)
ruth_filter |>
ggplot(aes(E, N, colour = segment_id)) +
geom_path() +
geom_point() +
coord_fixed() +
theme(legend.position = "bottom")