calculate_geographic_overlap_and_segregation: Analysis of geographic overlap and geographic segregation...

In brianwood1/xtracks: Xtracks: Software for Analysis of Movement and Socio-Spatial Patterns

Analysis of geographic overlap and geographic segregation between two groups of xtracks

Description

This analysis calculates measures of geographic overlap and geographic segregation between all the xtracks in one group and all the xtracks in another group. These groups could be gender groups (as done in Wood et al. 2021), or they could represent age groups, family groups, gender X age groups, all could be potentially interesting. This analysis should be done with two lists of xtrack objects, with each xtrack representing one day of travel. The lists can be of any length, but for an apples-to-apples empirical comparison, should be approx. equal in length.

Usage

calculate_geographic_overlap_and_segregation(
  xtrack_list_1,
  xtrack_list_2,
  cell_size_m = 10
)

Arguments

xtrack_list_1	a list of xtracks representing 'group 1'
xtrack_list_2	a list of xtracks representing 'group 1'.
cell_size_m	The resolution of the raster analysis – i.e. the height and width of each cell in the raster representation of the landscape, in meters.

Value

A list presenting analysis results

square_meters_visited_1

square meters of unique landscape areas visited by all xtracks in group 1

square_meters_visited_2

square meters of unique landscape areas visited by all xtracks in group 2

square_meters_visited_1_or_2

square meters of unique landscape areas visited by 1 or 2 (geographic union)

square_meters_visited_by_1_and_2

square meters of unique landscape areas visited by 1 and 2 (geographic intersection)

percent_of_what_1_visited_that_was_visited_by_2

percent of land visited by group 1 that was visited by group 2

percent_of_what_2_visited_that_was_visited_by_1

percent of land visited by group 2 that was visited by group 1

percent_of_what_was_visited_by_1_or_2_that_was_visited_by_1

percent of unique land visited by 1 or 2 that was visited by 1

percent_of_what_was_visited_by_1_or_2_that_was_visited_by_2

percent of unique land visited by 1 or 2 that was visited by 2

percent_of_what_was_visited_by_1_or_2_that_was_visited_by_1_and_2

percent of unique land visited by 1 or 2 that was visited by both 1 and 2.

See Also

For example of geographic segregation and overlap analysis see figure 4 in Wood et al. 2021 publication see https://www.nature.com/articles/s41562-020-01002-7

Examples

data(d1,d2,d3,d4,d5,d6,d7,d8)
xt_1 <- xtrack(lat=d1$lat, lon=d1$lon, elevation_m=d1$elevation_m, in_camp=d1$in_camp, unix_time=d1$unix_time, distance_from_camp_m=d1$distance_from_camp_m, utm_epsg=32736)
xt_2 <- xtrack(lat=d2$lat, lon=d2$lon, elevation_m=d2$elevation_m, in_camp=d2$in_camp, unix_time=d2$unix_time, distance_from_camp_m=d2$distance_from_camp_m, utm_epsg=32736)
xt_3 <- xtrack(lat=d3$lat, lon=d3$lon, elevation_m=d3$elevation_m, in_camp=d3$in_camp, unix_time=d3$unix_time, distance_from_camp_m=d3$distance_from_camp_m, utm_epsg=32736)
xt_4 <- xtrack(lat=d4$lat, lon=d4$lon, elevation_m=d4$elevation_m, in_camp=d4$in_camp, unix_time=d4$unix_time, distance_from_camp_m=d4$distance_from_camp_m, utm_epsg=32736)
xt_5 <- xtrack(lat=d5$lat, lon=d5$lon, elevation_m=d5$elevation_m, in_camp=d5$in_camp, unix_time=d5$unix_time, distance_from_camp_m=d5$distance_from_camp_m, utm_epsg=32736)
xt_6 <- xtrack(lat=d6$lat, lon=d6$lon, elevation_m=d6$elevation_m, in_camp=d6$in_camp, unix_time=d6$unix_time, distance_from_camp_m=d6$distance_from_camp_m, utm_epsg=32736)
xt_7 <- xtrack(lat=d7$lat, lon=d7$lon, elevation_m=d7$elevation_m, in_camp=d7$in_camp, unix_time=d7$unix_time, distance_from_camp_m=d7$distance_from_camp_m, utm_epsg=32736)
xt_8 <- xtrack(lat=d8$lat, lon=d8$lon, elevation_m=d8$elevation_m, in_camp=d8$in_camp, unix_time=d8$unix_time, distance_from_camp_m=d8$distance_from_camp_m, utm_epsg=32736)
list_1 <- list(xt_1, xt_2, xt_3, xt_4)
list_2 <- list(xt_5, xt_6, xt_7, xt_8)
geo_seg_results <- calculate_geographic_overlap_and_segregation(list_1, list_2, cell_size_m = 10)

brianwood1/xtracks documentation built on Oct. 12, 2022, 7:42 a.m.