Convert segments to spatial features

Builds an sf object from a segment_survey() result, either as the segment midpoints or as the trackline geometry of each segment.

Usage

segments_as_sf(x, what = c("midpoints", "lines"), crs = 4326)

Arguments

x

A distsamp_segments object.

what

"midpoints" (default) for one point per segment, or "lines" for the trackline each segment covers.

crs

Coordinate reference system for the result. Default 4326 (WGS 84), the datum NARWC coordinates are recorded in.

Value

An sf object with one feature per segment, carrying the segment attributes.

References

Pebesma, E. (2018) Simple features for R: standardized support for spatial vector data. The R Journal 10(1):439-446. doi:10.32614/RJ-2018-009

Examples

if (requireNamespace("sf", quietly = TRUE)) {
  path <- system.file("extdata", "narwc-example.csv", package = "distsamp")
  segs <- segment_survey(read_narwc(path), seg_length = 5, seed = 1)
  segments_as_sf(segs)
}
#> `read_narwc()` renamed 2 columns:
#>   LAT_DD  -> LATITUDE
#>   LONG_DD -> LONGITUDE
#> All matched an exact entry in the alias table; `narwc_column_mapping()` returns this, and `quiet = TRUE` silences it.
#> Simple feature collection with 20 features and 17 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: -69.1 ymin: 43.015 xmax: -68.6 ymax: 43.505
#> Geodetic CRS:  WGS 84
#> # A tibble: 20 × 18
#>    seg_id       DATE       FILEID LEGNO LEGNO2 LEGNO3 new_trackno seg_no seg_eff
#>  * <chr>        <date>     <chr>  <dbl> <chr>  <chr>  <chr>        <int>   <dbl>
#>  1 2024-04-01_… 2024-04-01 AA240…     1 1      1_2    2                1    7.78
#>  2 2024-04-01_… 2024-04-01 AA240…     1 1      1_2    2                2    5.56
#>  3 2024-04-01_… 2024-04-01 AA240…     1 1      1_2    2                3    3.33
#>  4 2024-04-01_… 2024-04-01 AA240…     1 1      1_2    2                4    5.56
#>  5 2024-04-01_… 2024-04-01 AA240…     2 2      2_3    4                1    4.44
#>  6 2024-04-01_… 2024-04-01 AA240…     2 2      2_3    4                2    3.33
#>  7 2024-04-01_… 2024-04-01 AA240…     2 2      2_3    6                1    4.44
#>  8 2024-04-01_… 2024-04-01 AA240…     2 2      2_3    6                2    4.44
#>  9 2024-04-02_… 2024-04-02 AA240…     3 3      3_4    1                1    3.33
#> 10 2024-04-02_… 2024-04-02 AA240…     3 3      3_4    1                2    4.44
#> 11 2024-04-02_… 2024-04-02 AA240…     3 3      3_4    1                3    5.56
#> 12 2024-04-02_… 2024-04-02 AA240…     3 3      3_4    1                4    4.44
#> 13 2024-04-02_… 2024-04-02 AA240…     3 3      3_4    1                5    6.67
#> 14 2024-04-02_… 2024-04-02 AA240…     3 3      3_4    1                6    4.44
#> 15 2024-04-02_… 2024-04-02 AA240…     3 3      3_4    1                7    4.44
#> 16 2024-04-02_… 2024-04-02 AA240…     4 4      4_5    2                1    3.33
#> 17 2024-04-02_… 2024-04-02 AA240…     5 5      5_6    4                1    5.56
#> 18 2024-04-02_… 2024-04-02 AA240…     5 5      5_6    4                2    2.22
#> 19 2024-04-02_… 2024-04-02 AA240…     4 4      4_7    5                1    3.33
#> 20 2024-04-02_… 2024-04-02 AA240…     4 4      4_7    5                2    5.56
#> # ℹ 9 more variables: mid_lat <dbl>, mid_lon <dbl>, mean_beaufort <dbl>,
#> #   wt_beaufort <dbl>, n_records <int>, start_time <dbl>, events <chr>,
#> #   case <chr>, geometry <POINT [°]>