vignettes/RMIAnalysis.md
In umd-lib/animalmove: Analysis of animal population-level movement patterns
Realized Mobility Index
Load package library
library(lubridate)
library(animalmove)
library(plyr)
Subsample Data
Buffalo dataset has been saved in the package data directory , and loaded on the package load.
Raw buffalo dataset contains unaltered original data.
data(buffalo)
head(buffalo)
## event.id visible timestamp location.long location.lat
## 1 10210419 true 2005-02-17 05:05:00.000 31.77 -24.54
## 2 10210423 true 2005-02-17 05:05:00.000 31.77 -24.54
## 3 10210428 true 2005-02-17 06:08:00.000 31.76 -24.54
## 4 10210434 true 2005-02-17 06:08:00.000 31.76 -24.54
## 5 10210456 true 2005-02-17 07:05:00.000 31.76 -24.55
## 6 10210458 true 2005-02-17 08:05:00.000 31.76 -24.55
## behavioural.classification comments manually.marked.outlier sensor.type
## 1 0 24.3 NA gps
## 2 0 24.3 NA gps
## 3 0 29.5 NA gps
## 4 0 29.5 NA gps
## 5 0 35.8 NA gps
## 6 0 37.3 NA gps
## individual.taxon.canonical.name tag.local.identifier
## 1 Syncerus caffer #1764820
## 2 Syncerus caffer #1764820
## 3 Syncerus caffer #1764820
## 4 Syncerus caffer #1764820
## 5 Syncerus caffer #1764820
## 6 Syncerus caffer #1764820
## individual.local.identifier
## 1 Queen
## 2 Queen
## 3 Queen
## 4 Queen
## 5 Queen
## 6 Queen
## study.name utm.easting
## 1 Kruger African Buffalo, GPS tracking, South Africa 375051
## 2 Kruger African Buffalo, GPS tracking, South Africa 375051
## 3 Kruger African Buffalo, GPS tracking, South Africa 374851
## 4 Kruger African Buffalo, GPS tracking, South Africa 374851
## 5 Kruger African Buffalo, GPS tracking, South Africa 374527
## 6 Kruger African Buffalo, GPS tracking, South Africa 374492
## utm.northing utm.zone study.timezone study.local.timestamp
## 1 7285726 36S South Africa Standard Time 2005-02-17 07:05:00.000
## 2 7285726 36S South Africa Standard Time 2005-02-17 07:05:00.000
## 3 7285502 36S South Africa Standard Time 2005-02-17 08:08:00.000
## 4 7285502 36S South Africa Standard Time 2005-02-17 08:08:00.000
## 5 7284538 36S South Africa Standard Time 2005-02-17 09:05:00.000
## 6 7284644 36S South Africa Standard Time 2005-02-17 10:05:00.000
nrow(buffalo)
## [1] 28410
currentnames <- colnames(buffalo)
currentnames
## [1] "event.id" "visible"
## [3] "timestamp" "location.long"
## [5] "location.lat" "behavioural.classification"
## [7] "comments" "manually.marked.outlier"
## [9] "sensor.type" "individual.taxon.canonical.name"
## [11] "tag.local.identifier" "individual.local.identifier"
## [13] "study.name" "utm.easting"
## [15] "utm.northing" "utm.zone"
## [17] "study.timezone" "study.local.timestamp"
names(buffalo)[names(buffalo) == "timestamp"] <- "time"
names(buffalo)[names(buffalo) == "utm.easting"] <- "x"
names(buffalo)[names(buffalo) == "utm.northing"] <- "y"
names(buffalo)[names(buffalo) == "tag.local.identifier"] <- "id"
names(buffalo)[names(buffalo) == "individual.taxon.canonical.name"] <- "pop.type"
# Data Conversion
buffalo$time <- as.POSIXct(strptime(buffalo$time, format = "%Y-%m-%d %H:%M",
tz = "GMT"))
# Display new names
newnames <- colnames(buffalo)
newnames
## [1] "event.id" "visible"
## [3] "time" "location.long"
## [5] "location.lat" "behavioural.classification"
## [7] "comments" "manually.marked.outlier"
## [9] "sensor.type" "pop.type"
## [11] "id" "individual.local.identifier"
## [13] "study.name" "x"
## [15] "y" "utm.zone"
## [17] "study.timezone" "study.local.timestamp"
head(buffalo)
## event.id visible time location.long location.lat
## 1 10210419 true 2005-02-17 05:05:00 31.77 -24.54
## 2 10210423 true 2005-02-17 05:05:00 31.77 -24.54
## 3 10210428 true 2005-02-17 06:08:00 31.76 -24.54
## 4 10210434 true 2005-02-17 06:08:00 31.76 -24.54
## 5 10210456 true 2005-02-17 07:05:00 31.76 -24.55
## 6 10210458 true 2005-02-17 08:05:00 31.76 -24.55
## behavioural.classification comments manually.marked.outlier sensor.type
## 1 0 24.3 NA gps
## 2 0 24.3 NA gps
## 3 0 29.5 NA gps
## 4 0 29.5 NA gps
## 5 0 35.8 NA gps
## 6 0 37.3 NA gps
## pop.type id individual.local.identifier
## 1 Syncerus caffer #1764820 Queen
## 2 Syncerus caffer #1764820 Queen
## 3 Syncerus caffer #1764820 Queen
## 4 Syncerus caffer #1764820 Queen
## 5 Syncerus caffer #1764820 Queen
## 6 Syncerus caffer #1764820 Queen
## study.name x y
## 1 Kruger African Buffalo, GPS tracking, South Africa 375051 7285726
## 2 Kruger African Buffalo, GPS tracking, South Africa 375051 7285726
## 3 Kruger African Buffalo, GPS tracking, South Africa 374851 7285502
## 4 Kruger African Buffalo, GPS tracking, South Africa 374851 7285502
## 5 Kruger African Buffalo, GPS tracking, South Africa 374527 7284538
## 6 Kruger African Buffalo, GPS tracking, South Africa 374492 7284644
## utm.zone study.timezone study.local.timestamp
## 1 36S South Africa Standard Time 2005-02-17 07:05:00.000
## 2 36S South Africa Standard Time 2005-02-17 07:05:00.000
## 3 36S South Africa Standard Time 2005-02-17 08:08:00.000
## 4 36S South Africa Standard Time 2005-02-17 08:08:00.000
## 5 36S South Africa Standard Time 2005-02-17 09:05:00.000
## 6 36S South Africa Standard Time 2005-02-17 10:05:00.000
Number of rows in the buffalo data & data set structure
length(table((buffalo$id)))
## [1] 6
str(buffalo)
## 'data.frame': 28410 obs. of 18 variables:
## $ event.id : int 10210419 10210423 10210428 10210434 10210456 10210458 10210483 10210535 10210544 10210558 ...
## $ visible : chr "true" "true" "true" "true" ...
## $ time : POSIXct, format: "2005-02-17 05:05:00" "2005-02-17 05:05:00" ...
## $ location.long : num 31.8 31.8 31.8 31.8 31.8 ...
## $ location.lat : num -24.5 -24.5 -24.5 -24.5 -24.5 ...
## $ behavioural.classification : int 0 0 0 0 0 0 0 0 0 0 ...
## $ comments : num 24.3 24.3 29.5 29.5 35.8 37.3 38.9 39.6 40 38.1 ...
## $ manually.marked.outlier : logi NA NA NA NA NA NA ...
## $ sensor.type : chr "gps" "gps" "gps" "gps" ...
## $ pop.type : chr "Syncerus caffer" "Syncerus caffer" "Syncerus caffer" "Syncerus caffer" ...
## $ id : chr "#1764820" "#1764820" "#1764820" "#1764820" ...
## $ individual.local.identifier: chr "Queen" "Queen" "Queen" "Queen" ...
## $ study.name : chr "Kruger African Buffalo, GPS tracking, South Africa" "Kruger African Buffalo, GPS tracking, South Africa" "Kruger African Buffalo, GPS tracking, South Africa" "Kruger African Buffalo, GPS tracking, South Africa" ...
## $ x : num 375051 375051 374851 374851 374527 ...
## $ y : num 7285726 7285726 7285502 7285502 7284538 ...
## $ utm.zone : chr "36S" "36S" "36S" "36S" ...
## $ study.timezone : chr "South Africa Standard Time" "South Africa Standard Time" "South Africa Standard Time" "South Africa Standard Time" ...
## $ study.local.timestamp : chr "2005-02-17 07:05:00.000" "2005-02-17 07:05:00.000" "2005-02-17 08:08:00.000" "2005-02-17 08:08:00.000" ...
Subsample data within time interval
We select at most 6 individuals within 2009, time interval 50 hours, and accuracy 50 hours, and subsampling scheme for Realized Mobility Index
rmi.subsample.data <- subsample(dat = buffalo, start = c("2005-02-17 00:00:00"),
end = "2006-12-31 00:00:00", interval = c("48 hours"), accuracy = c("3 hours"),
minIndiv = 3, maxIndiv = 6, mustIndiv = NULL, index.type = "rmi")
## [1] "48 hours"
## [1] "3 hours"
## [1] "2005-02-17 00:00:00"
## 'data.frame': 6 obs. of 9 variables:
## $ numberOfIndividuals: int 3 4 6 5 4 3
## $ pairsOfCompleteSets: int 32 20 10 21 41 52
## $ completeSets : int 34 22 11 22 42 54
## $ scanInterval : chr "48 hours" "48 hours" "48 hours" "48 hours" ...
## $ scanAccuracy : chr "3 hours" "3 hours" "3 hours" "3 hours" ...
## $ firstScantime : chr "2005-02-17 00:00:00" "2005-02-17 00:00:00" "2005-02-17 00:00:00" "2005-02-17 00:00:00" ...
## $ firstOverlap : chr "2005-07-29 00:00" "2005-08-24 00:00" "2005-09-17 00:00" "2005-09-17 00:00" ...
## $ lastOverlap : chr "2005-10-07 00:00" "2005-10-07 00:00" "2005-10-07 00:00" "2005-10-29 00:00" ...
## $ lastScantime : chr "2006-12-31 00:00:00" "2006-12-31 00:00:00" "2006-12-31 00:00:00" "2006-12-31 00:00:00" ...
buffalo.indiv <- Individuals(rmi.subsample.data, id = "id", time = "time", x = "x",
y = "y", group.by = "pop.type", proj4string = CRS("+proj=utm +zone=28 +datum=WGS84"))
head(coordinates(buffalo.indiv))
## x y
## [1,] 379376 7285046
## [2,] 382845 7229739
## [3,] 381304 7229397
## [4,] 389364 7238737
## [5,] 375582 7314786
## [6,] 379448 7285020
bbox(buffalo.indiv)
## min max
## x 370033 395074
## y 7217891 7317506
head(show(buffalo.indiv), 2)
## class : Individuals
## features : 66
## extent : 370033, 395074, 7217891, 7317506 (xmin, xmax, ymin, ymax)
## coord. ref. : NA
## variables : 19
## names : overlapID, scantimes, event.id, visible, time, location.long, location.lat, behavioural.classification, comments, manually.marked.outlier, sensor.type, pop.type, id, individual.local.identifier, study.name, ...
## min values : 107, 2005-09-17, 10204234, true, 2005-09-16 23:32:00, 31.72, -24.25, 0, 17.0, NA, gps, Syncerus caffer, #1764820, Cilla, Kruger African Buffalo, GPS tracking, South Africa, ...
## max values : 117, 2005-10-07, 10231296, true, 2005-10-07 02:07:00, 31.96, -25.15, 0, 29.9, NA, gps, Syncerus caffer, #1764835, Toni, Kruger African Buffalo, GPS tracking, South Africa, ...
## NULL
head(SpatialPoints(buffalo.indiv), 2)
## class : SpatialPoints
## features : 1
## extent : 379376, 379376, 7285046, 7285046 (xmin, xmax, ymin, ymax)
## coord. ref. : NA
coordnames(buffalo.indiv)
## [1] "x" "y"
buffalo.data.attr <- as.data.frame(buffalo.indiv)
head(buffalo.data.attr)
## x y overlapID scantimes event.id visible time
## 1 379376 7285046 107 2005-09-17 10211590 true 2005-09-16 23:40:00
## 2 382845 7229739 107 2005-09-17 10229079 true 2005-09-16 23:59:00
## 3 381304 7229397 107 2005-09-17 10224823 true 2005-09-17 00:26:00
## 4 389364 7238737 107 2005-09-17 10204234 true 2005-09-16 23:54:00
## 5 375582 7314786 107 2005-09-17 10220006 true 2005-09-16 23:32:00
## 6 379448 7285020 107 2005-09-17 10205446 true 2005-09-17 00:16:00
## location.long location.lat behavioural.classification comments
## 1 31.81 -24.54 0 20.9
## 2 31.84 -25.04 0 20.9
## 3 31.82 -25.05 0 18.6
## 4 31.90 -24.96 0 19.8
## 5 31.77 -24.27 0 18.6
## 6 31.81 -24.54 0 21.7
## manually.marked.outlier sensor.type pop.type id
## 1 NA gps Syncerus caffer #1764820
## 2 NA gps Syncerus caffer #1764823
## 3 NA gps Syncerus caffer #1764826
## 4 NA gps Syncerus caffer #1764829
## 5 NA gps Syncerus caffer #1764832
## 6 NA gps Syncerus caffer #1764835
## individual.local.identifier
## 1 Queen
## 2 Gabs
## 3 Cilla
## 4 Mvubu
## 5 Toni
## 6 Pepper
## study.name utm.zone
## 1 Kruger African Buffalo, GPS tracking, South Africa 36S
## 2 Kruger African Buffalo, GPS tracking, South Africa 36S
## 3 Kruger African Buffalo, GPS tracking, South Africa 36S
## 4 Kruger African Buffalo, GPS tracking, South Africa 36S
## 5 Kruger African Buffalo, GPS tracking, South Africa 36S
## 6 Kruger African Buffalo, GPS tracking, South Africa 36S
## study.timezone study.local.timestamp time.lag
## 1 South Africa Standard Time 2005-09-17 01:40:00.000 49.99 days
## 2 South Africa Standard Time 2005-09-17 01:59:00.000 50.00 days
## 3 South Africa Standard Time 2005-09-17 02:26:00.000 50.02 days
## 4 South Africa Standard Time 2005-09-17 01:54:00.000 50.00 days
## 5 South Africa Standard Time 2005-09-17 01:32:00.000 49.98 days
## 6 South Africa Standard Time 2005-09-17 02:16:00.000 50.01 days
buffalo.individual.mcp <- mcp(buffalo.indiv[, "id"], percent = 100)
buffalo.individual.mcp
## Object of class "SpatialPolygonsDataFrame" (package sp):
##
## Number of SpatialPolygons: 6
##
## Variables measured:
## id area
## #1764820 #1764820 10170.1
## #1764823 #1764823 842.2
## #1764826 #1764826 8280.5
## #1764829 #1764829 13887.4
## #1764832 #1764832 3304.2
## #1764835 #1764835 10222.6
buffalo.population.mcp <- mcp.population(buffalo.indiv, percent = 100)
buffalo.population.mcp
## Object of class "SpatialPolygonsDataFrame" (package sp):
##
## Number of SpatialPolygons: 1
##
## Variables measured:
## id area
## Syncerus caffer Syncerus caffer 116502
show.mcp(buffalo.indiv, percent = 100, id = "id")
## [1] "Individual MCPs:"
## class : SpatialPolygonsDataFrame
## features : 6
## extent : 370033, 395074, 7217891, 7317506 (xmin, xmax, ymin, ymax)
## coord. ref. : NA
## variables : 2
## names : id, area
## min values : #1764820, 842.2
## max values : #1764835, 13887.4
## [1] "Population MCPs:"
## Syncerus caffer
## 100 116502
print(buffalo.indiv)
## [1] "coordinates names:"
## x y
## ...........
## [1] "bbox:"
## min max
## x 370033 395074
## y 7217891 7317506
Note, a number of rows in the rmi subsample dataset
nrow(rmi.subsample.data)
## [1] 66
Analysis
Compute Realized Mobility Index
fg.pal <- color.palette(length(unique(buffalo.data.attr$pop.type)))
bg.pal <- color.palette(length(unique(buffalo.data.attr$pop.type)), palette = c("Dark2"))
plot(buffalo.individual.mcp, col = fg.pal)
plot(buffalo.indiv, col = "green")
rmi.index.population <- rmi.index(buffalo.indiv, percent = 100, id = "id")
## class : SpatialPolygonsDataFrame
## features : 1
## extent : 370033, 395074, 7217891, 7317506 (xmin, xmax, ymin, ymax)
## coord. ref. : NA
## variables : 2
## names : id, area
## min values : Syncerus caffer, 116502
## max values : Syncerus caffer, 116502
plot(rmi.index.population)
RMI Data
rmi.index.population
## An object of class "RMIndex"
## Slot "data":
## id pop.type ind.home.range pop.home.range rmi.index
## 1 #1764820 Syncerus caffer 10170.1 116502 0.087295
## 2 #1764823 Syncerus caffer 842.2 116502 0.007229
## 3 #1764826 Syncerus caffer 8280.5 116502 0.071076
## 4 #1764829 Syncerus caffer 13887.4 116502 0.119202
## 5 #1764832 Syncerus caffer 3304.2 116502 0.028361
## 6 #1764835 Syncerus caffer 10222.6 116502 0.087746
RMI Summary
rmi.index.population
## An object of class "RMIndex"
## Slot "data":
## id pop.type ind.home.range pop.home.range rmi.index
## 1 #1764820 Syncerus caffer 10170.1 116502 0.087295
## 2 #1764823 Syncerus caffer 842.2 116502 0.007229
## 3 #1764826 Syncerus caffer 8280.5 116502 0.071076
## 4 #1764829 Syncerus caffer 13887.4 116502 0.119202
## 5 #1764832 Syncerus caffer 3304.2 116502 0.028361
## 6 #1764835 Syncerus caffer 10222.6 116502 0.087746
summary(rmi.index.population)
## $`Syncerus caffer`
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00723 0.03900 0.07920 0.06680 0.08760 0.11900
Plot Results
plot(rmi.index.population)
umd-lib/animalmove documentation built on May 3, 2019, 2:24 p.m.
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Realized Mobility Index
Load package library
library(lubridate)
library(animalmove)
library(plyr)
Subsample Data
Buffalo dataset has been saved in the package data directory , and loaded on the package load.
Raw buffalo dataset contains unaltered original data.
data(buffalo)
head(buffalo)
## event.id visible timestamp location.long location.lat
## 1 10210419 true 2005-02-17 05:05:00.000 31.77 -24.54
## 2 10210423 true 2005-02-17 05:05:00.000 31.77 -24.54
## 3 10210428 true 2005-02-17 06:08:00.000 31.76 -24.54
## 4 10210434 true 2005-02-17 06:08:00.000 31.76 -24.54
## 5 10210456 true 2005-02-17 07:05:00.000 31.76 -24.55
## 6 10210458 true 2005-02-17 08:05:00.000 31.76 -24.55
## behavioural.classification comments manually.marked.outlier sensor.type
## 1 0 24.3 NA gps
## 2 0 24.3 NA gps
## 3 0 29.5 NA gps
## 4 0 29.5 NA gps
## 5 0 35.8 NA gps
## 6 0 37.3 NA gps
## individual.taxon.canonical.name tag.local.identifier
## 1 Syncerus caffer #1764820
## 2 Syncerus caffer #1764820
## 3 Syncerus caffer #1764820
## 4 Syncerus caffer #1764820
## 5 Syncerus caffer #1764820
## 6 Syncerus caffer #1764820
## individual.local.identifier
## 1 Queen
## 2 Queen
## 3 Queen
## 4 Queen
## 5 Queen
## 6 Queen
## study.name utm.easting
## 1 Kruger African Buffalo, GPS tracking, South Africa 375051
## 2 Kruger African Buffalo, GPS tracking, South Africa 375051
## 3 Kruger African Buffalo, GPS tracking, South Africa 374851
## 4 Kruger African Buffalo, GPS tracking, South Africa 374851
## 5 Kruger African Buffalo, GPS tracking, South Africa 374527
## 6 Kruger African Buffalo, GPS tracking, South Africa 374492
## utm.northing utm.zone study.timezone study.local.timestamp
## 1 7285726 36S South Africa Standard Time 2005-02-17 07:05:00.000
## 2 7285726 36S South Africa Standard Time 2005-02-17 07:05:00.000
## 3 7285502 36S South Africa Standard Time 2005-02-17 08:08:00.000
## 4 7285502 36S South Africa Standard Time 2005-02-17 08:08:00.000
## 5 7284538 36S South Africa Standard Time 2005-02-17 09:05:00.000
## 6 7284644 36S South Africa Standard Time 2005-02-17 10:05:00.000
nrow(buffalo)
## [1] 28410
currentnames <- colnames(buffalo)
currentnames
## [1] "event.id" "visible"
## [3] "timestamp" "location.long"
## [5] "location.lat" "behavioural.classification"
## [7] "comments" "manually.marked.outlier"
## [9] "sensor.type" "individual.taxon.canonical.name"
## [11] "tag.local.identifier" "individual.local.identifier"
## [13] "study.name" "utm.easting"
## [15] "utm.northing" "utm.zone"
## [17] "study.timezone" "study.local.timestamp"
names(buffalo)[names(buffalo) == "timestamp"] <- "time"
names(buffalo)[names(buffalo) == "utm.easting"] <- "x"
names(buffalo)[names(buffalo) == "utm.northing"] <- "y"
names(buffalo)[names(buffalo) == "tag.local.identifier"] <- "id"
names(buffalo)[names(buffalo) == "individual.taxon.canonical.name"] <- "pop.type"
# Data Conversion
buffalo$time <- as.POSIXct(strptime(buffalo$time, format = "%Y-%m-%d %H:%M",
tz = "GMT"))
# Display new names
newnames <- colnames(buffalo)
newnames
## [1] "event.id" "visible"
## [3] "time" "location.long"
## [5] "location.lat" "behavioural.classification"
## [7] "comments" "manually.marked.outlier"
## [9] "sensor.type" "pop.type"
## [11] "id" "individual.local.identifier"
## [13] "study.name" "x"
## [15] "y" "utm.zone"
## [17] "study.timezone" "study.local.timestamp"
head(buffalo)
## event.id visible time location.long location.lat
## 1 10210419 true 2005-02-17 05:05:00 31.77 -24.54
## 2 10210423 true 2005-02-17 05:05:00 31.77 -24.54
## 3 10210428 true 2005-02-17 06:08:00 31.76 -24.54
## 4 10210434 true 2005-02-17 06:08:00 31.76 -24.54
## 5 10210456 true 2005-02-17 07:05:00 31.76 -24.55
## 6 10210458 true 2005-02-17 08:05:00 31.76 -24.55
## behavioural.classification comments manually.marked.outlier sensor.type
## 1 0 24.3 NA gps
## 2 0 24.3 NA gps
## 3 0 29.5 NA gps
## 4 0 29.5 NA gps
## 5 0 35.8 NA gps
## 6 0 37.3 NA gps
## pop.type id individual.local.identifier
## 1 Syncerus caffer #1764820 Queen
## 2 Syncerus caffer #1764820 Queen
## 3 Syncerus caffer #1764820 Queen
## 4 Syncerus caffer #1764820 Queen
## 5 Syncerus caffer #1764820 Queen
## 6 Syncerus caffer #1764820 Queen
## study.name x y
## 1 Kruger African Buffalo, GPS tracking, South Africa 375051 7285726
## 2 Kruger African Buffalo, GPS tracking, South Africa 375051 7285726
## 3 Kruger African Buffalo, GPS tracking, South Africa 374851 7285502
## 4 Kruger African Buffalo, GPS tracking, South Africa 374851 7285502
## 5 Kruger African Buffalo, GPS tracking, South Africa 374527 7284538
## 6 Kruger African Buffalo, GPS tracking, South Africa 374492 7284644
## utm.zone study.timezone study.local.timestamp
## 1 36S South Africa Standard Time 2005-02-17 07:05:00.000
## 2 36S South Africa Standard Time 2005-02-17 07:05:00.000
## 3 36S South Africa Standard Time 2005-02-17 08:08:00.000
## 4 36S South Africa Standard Time 2005-02-17 08:08:00.000
## 5 36S South Africa Standard Time 2005-02-17 09:05:00.000
## 6 36S South Africa Standard Time 2005-02-17 10:05:00.000
Number of rows in the buffalo data & data set structure
length(table((buffalo$id)))
## [1] 6
str(buffalo)
## 'data.frame': 28410 obs. of 18 variables:
## $ event.id : int 10210419 10210423 10210428 10210434 10210456 10210458 10210483 10210535 10210544 10210558 ...
## $ visible : chr "true" "true" "true" "true" ...
## $ time : POSIXct, format: "2005-02-17 05:05:00" "2005-02-17 05:05:00" ...
## $ location.long : num 31.8 31.8 31.8 31.8 31.8 ...
## $ location.lat : num -24.5 -24.5 -24.5 -24.5 -24.5 ...
## $ behavioural.classification : int 0 0 0 0 0 0 0 0 0 0 ...
## $ comments : num 24.3 24.3 29.5 29.5 35.8 37.3 38.9 39.6 40 38.1 ...
## $ manually.marked.outlier : logi NA NA NA NA NA NA ...
## $ sensor.type : chr "gps" "gps" "gps" "gps" ...
## $ pop.type : chr "Syncerus caffer" "Syncerus caffer" "Syncerus caffer" "Syncerus caffer" ...
## $ id : chr "#1764820" "#1764820" "#1764820" "#1764820" ...
## $ individual.local.identifier: chr "Queen" "Queen" "Queen" "Queen" ...
## $ study.name : chr "Kruger African Buffalo, GPS tracking, South Africa" "Kruger African Buffalo, GPS tracking, South Africa" "Kruger African Buffalo, GPS tracking, South Africa" "Kruger African Buffalo, GPS tracking, South Africa" ...
## $ x : num 375051 375051 374851 374851 374527 ...
## $ y : num 7285726 7285726 7285502 7285502 7284538 ...
## $ utm.zone : chr "36S" "36S" "36S" "36S" ...
## $ study.timezone : chr "South Africa Standard Time" "South Africa Standard Time" "South Africa Standard Time" "South Africa Standard Time" ...
## $ study.local.timestamp : chr "2005-02-17 07:05:00.000" "2005-02-17 07:05:00.000" "2005-02-17 08:08:00.000" "2005-02-17 08:08:00.000" ...
Subsample data within time interval
We select at most 6 individuals within 2009, time interval 50 hours, and accuracy 50 hours, and subsampling scheme for Realized Mobility Index
rmi.subsample.data <- subsample(dat = buffalo, start = c("2005-02-17 00:00:00"),
end = "2006-12-31 00:00:00", interval = c("48 hours"), accuracy = c("3 hours"),
minIndiv = 3, maxIndiv = 6, mustIndiv = NULL, index.type = "rmi")
## [1] "48 hours"
## [1] "3 hours"
## [1] "2005-02-17 00:00:00"
## 'data.frame': 6 obs. of 9 variables:
## $ numberOfIndividuals: int 3 4 6 5 4 3
## $ pairsOfCompleteSets: int 32 20 10 21 41 52
## $ completeSets : int 34 22 11 22 42 54
## $ scanInterval : chr "48 hours" "48 hours" "48 hours" "48 hours" ...
## $ scanAccuracy : chr "3 hours" "3 hours" "3 hours" "3 hours" ...
## $ firstScantime : chr "2005-02-17 00:00:00" "2005-02-17 00:00:00" "2005-02-17 00:00:00" "2005-02-17 00:00:00" ...
## $ firstOverlap : chr "2005-07-29 00:00" "2005-08-24 00:00" "2005-09-17 00:00" "2005-09-17 00:00" ...
## $ lastOverlap : chr "2005-10-07 00:00" "2005-10-07 00:00" "2005-10-07 00:00" "2005-10-29 00:00" ...
## $ lastScantime : chr "2006-12-31 00:00:00" "2006-12-31 00:00:00" "2006-12-31 00:00:00" "2006-12-31 00:00:00" ...
buffalo.indiv <- Individuals(rmi.subsample.data, id = "id", time = "time", x = "x",
y = "y", group.by = "pop.type", proj4string = CRS("+proj=utm +zone=28 +datum=WGS84"))
head(coordinates(buffalo.indiv))
## x y
## [1,] 379376 7285046
## [2,] 382845 7229739
## [3,] 381304 7229397
## [4,] 389364 7238737
## [5,] 375582 7314786
## [6,] 379448 7285020
bbox(buffalo.indiv)
## min max
## x 370033 395074
## y 7217891 7317506
head(show(buffalo.indiv), 2)
## class : Individuals
## features : 66
## extent : 370033, 395074, 7217891, 7317506 (xmin, xmax, ymin, ymax)
## coord. ref. : NA
## variables : 19
## names : overlapID, scantimes, event.id, visible, time, location.long, location.lat, behavioural.classification, comments, manually.marked.outlier, sensor.type, pop.type, id, individual.local.identifier, study.name, ...
## min values : 107, 2005-09-17, 10204234, true, 2005-09-16 23:32:00, 31.72, -24.25, 0, 17.0, NA, gps, Syncerus caffer, #1764820, Cilla, Kruger African Buffalo, GPS tracking, South Africa, ...
## max values : 117, 2005-10-07, 10231296, true, 2005-10-07 02:07:00, 31.96, -25.15, 0, 29.9, NA, gps, Syncerus caffer, #1764835, Toni, Kruger African Buffalo, GPS tracking, South Africa, ...
## NULL
head(SpatialPoints(buffalo.indiv), 2)
## class : SpatialPoints
## features : 1
## extent : 379376, 379376, 7285046, 7285046 (xmin, xmax, ymin, ymax)
## coord. ref. : NA
coordnames(buffalo.indiv)
## [1] "x" "y"
buffalo.data.attr <- as.data.frame(buffalo.indiv)
head(buffalo.data.attr)
## x y overlapID scantimes event.id visible time
## 1 379376 7285046 107 2005-09-17 10211590 true 2005-09-16 23:40:00
## 2 382845 7229739 107 2005-09-17 10229079 true 2005-09-16 23:59:00
## 3 381304 7229397 107 2005-09-17 10224823 true 2005-09-17 00:26:00
## 4 389364 7238737 107 2005-09-17 10204234 true 2005-09-16 23:54:00
## 5 375582 7314786 107 2005-09-17 10220006 true 2005-09-16 23:32:00
## 6 379448 7285020 107 2005-09-17 10205446 true 2005-09-17 00:16:00
## location.long location.lat behavioural.classification comments
## 1 31.81 -24.54 0 20.9
## 2 31.84 -25.04 0 20.9
## 3 31.82 -25.05 0 18.6
## 4 31.90 -24.96 0 19.8
## 5 31.77 -24.27 0 18.6
## 6 31.81 -24.54 0 21.7
## manually.marked.outlier sensor.type pop.type id
## 1 NA gps Syncerus caffer #1764820
## 2 NA gps Syncerus caffer #1764823
## 3 NA gps Syncerus caffer #1764826
## 4 NA gps Syncerus caffer #1764829
## 5 NA gps Syncerus caffer #1764832
## 6 NA gps Syncerus caffer #1764835
## individual.local.identifier
## 1 Queen
## 2 Gabs
## 3 Cilla
## 4 Mvubu
## 5 Toni
## 6 Pepper
## study.name utm.zone
## 1 Kruger African Buffalo, GPS tracking, South Africa 36S
## 2 Kruger African Buffalo, GPS tracking, South Africa 36S
## 3 Kruger African Buffalo, GPS tracking, South Africa 36S
## 4 Kruger African Buffalo, GPS tracking, South Africa 36S
## 5 Kruger African Buffalo, GPS tracking, South Africa 36S
## 6 Kruger African Buffalo, GPS tracking, South Africa 36S
## study.timezone study.local.timestamp time.lag
## 1 South Africa Standard Time 2005-09-17 01:40:00.000 49.99 days
## 2 South Africa Standard Time 2005-09-17 01:59:00.000 50.00 days
## 3 South Africa Standard Time 2005-09-17 02:26:00.000 50.02 days
## 4 South Africa Standard Time 2005-09-17 01:54:00.000 50.00 days
## 5 South Africa Standard Time 2005-09-17 01:32:00.000 49.98 days
## 6 South Africa Standard Time 2005-09-17 02:16:00.000 50.01 days
buffalo.individual.mcp <- mcp(buffalo.indiv[, "id"], percent = 100)
buffalo.individual.mcp
## Object of class "SpatialPolygonsDataFrame" (package sp):
##
## Number of SpatialPolygons: 6
##
## Variables measured:
## id area
## #1764820 #1764820 10170.1
## #1764823 #1764823 842.2
## #1764826 #1764826 8280.5
## #1764829 #1764829 13887.4
## #1764832 #1764832 3304.2
## #1764835 #1764835 10222.6
buffalo.population.mcp <- mcp.population(buffalo.indiv, percent = 100)
buffalo.population.mcp
## Object of class "SpatialPolygonsDataFrame" (package sp):
##
## Number of SpatialPolygons: 1
##
## Variables measured:
## id area
## Syncerus caffer Syncerus caffer 116502
show.mcp(buffalo.indiv, percent = 100, id = "id")
## [1] "Individual MCPs:"
## class : SpatialPolygonsDataFrame
## features : 6
## extent : 370033, 395074, 7217891, 7317506 (xmin, xmax, ymin, ymax)
## coord. ref. : NA
## variables : 2
## names : id, area
## min values : #1764820, 842.2
## max values : #1764835, 13887.4
## [1] "Population MCPs:"
## Syncerus caffer
## 100 116502
print(buffalo.indiv)
## [1] "coordinates names:"
## x y
## ...........
## [1] "bbox:"
## min max
## x 370033 395074
## y 7217891 7317506
Note, a number of rows in the rmi subsample dataset
nrow(rmi.subsample.data)
## [1] 66
Analysis
Compute Realized Mobility Index
fg.pal <- color.palette(length(unique(buffalo.data.attr$pop.type)))
bg.pal <- color.palette(length(unique(buffalo.data.attr$pop.type)), palette = c("Dark2"))
plot(buffalo.individual.mcp, col = fg.pal)
plot(buffalo.indiv, col = "green")
rmi.index.population <- rmi.index(buffalo.indiv, percent = 100, id = "id")
## class : SpatialPolygonsDataFrame
## features : 1
## extent : 370033, 395074, 7217891, 7317506 (xmin, xmax, ymin, ymax)
## coord. ref. : NA
## variables : 2
## names : id, area
## min values : Syncerus caffer, 116502
## max values : Syncerus caffer, 116502
plot(rmi.index.population)
RMI Data
rmi.index.population
## An object of class "RMIndex"
## Slot "data":
## id pop.type ind.home.range pop.home.range rmi.index
## 1 #1764820 Syncerus caffer 10170.1 116502 0.087295
## 2 #1764823 Syncerus caffer 842.2 116502 0.007229
## 3 #1764826 Syncerus caffer 8280.5 116502 0.071076
## 4 #1764829 Syncerus caffer 13887.4 116502 0.119202
## 5 #1764832 Syncerus caffer 3304.2 116502 0.028361
## 6 #1764835 Syncerus caffer 10222.6 116502 0.087746
RMI Summary
rmi.index.population
## An object of class "RMIndex"
## Slot "data":
## id pop.type ind.home.range pop.home.range rmi.index
## 1 #1764820 Syncerus caffer 10170.1 116502 0.087295
## 2 #1764823 Syncerus caffer 842.2 116502 0.007229
## 3 #1764826 Syncerus caffer 8280.5 116502 0.071076
## 4 #1764829 Syncerus caffer 13887.4 116502 0.119202
## 5 #1764832 Syncerus caffer 3304.2 116502 0.028361
## 6 #1764835 Syncerus caffer 10222.6 116502 0.087746
summary(rmi.index.population)
## $`Syncerus caffer`
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00723 0.03900 0.07920 0.06680 0.08760 0.11900
Plot Results
plot(rmi.index.population)
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