# Isobath corridors

    library(blueterra)

Isobath corridors summarize terrain along depth horizons. They are useful when observations are collected along contours or when terrain structure needs to be compared at equivalent depths while retaining along-contour variability.

    bathy <- read_bathy(blueterra_example("hitw"))
    prepared <- prepare_bathy(bathy, depth_range = c(-220, -25), smooth = TRUE)
    terrain <- derive_terrain(
      prepared,
      metrics = c("slope", "bpi", "curvature", "surface_area_ratio")
    )

The example bathymetry stores depth as negative elevation, so contour depths are passed as negative values.

    isobaths <- extract_isobaths(prepared, depths = c(-50, -80, -120))
    isobaths[, c("contour_value", "depth_label")]
    #> class       : SpatVector
    #> geometry    : lines
    #> dimensions  : 3, 2  (geometries, attributes)
    #> extent      : 137476.2, 137772, 205669.4, 205756.6  (xmin, xmax, ymin, ymax)
    #> coord. ref. : NAD83 / Puerto Rico & Virgin Is. (EPSG:32161)
    #> names       : contour_value depth_label
    #> type        :         <num>       <num>
    #> values      :           -50         -50
    #>                         -80         -80
    #>                        -120        -120

    plot_bathy(
      prepared,
      contours = TRUE,
      contour_interval = 25,
      vectors = isobaths,
      vector_color = "black",
      title = "Isobaths Over Hillshaded Bathymetry"
    )

Buffers are measured in map units, so the raster should use a projected CRS. The example raster is projected; other rasters should be reprojected explicitly when needed. Corridors use a 5 m buffer around each source isobath.

    corridors <- make_isobath_corridors(
      prepared,
      depths = c(-50, -80, -120),
      width = 5
    )
    corridors[, c("contour_value", "depth_label", "corridor_id")]
    #> class       : SpatVector
    #> geometry    : polygons
    #> dimensions  : 3, 3  (geometries, attributes)
    #> extent      : 137471.2, 137777, 205664.4, 205761.6  (xmin, xmax, ymin, ymax)
    #> coord. ref. : NAD83 / Puerto Rico & Virgin Is. (EPSG:32161)
    #> names       : contour_value depth_label corridor_id
    #> type        :         <num>       <num>       <int>
    #> values      :           -50         -50           1
    #>                         -80         -80           2
    #>                        -120        -120           3

    plot_isobath_corridors(
      corridors,
      prepared,
      isobaths = isobaths,
      background_contours = FALSE,
      title = "Isobath Corridors and Source Isobaths",
      subtitle = "Corridors use a 5 m buffer around each source isobath"
    )

The black lines are the source isobaths. The corridor polygons buffer those depth horizons by 5 m and define the terrain extraction zones used in the summary.

## Extract and Summarize Terrain

    cells <- extract_isobath_corridors(terrain, corridors)
    head(cells)
    #> # A tibble: 6 × 10
    #>      ID level contour_value depth_label corridor_id slope_deg bpi_3x3 bpi_11x11
    #>   <int> <dbl>         <dbl>       <dbl>       <int>     <dbl>   <dbl>     <dbl>
    #> 1     1   -50           -50         -50           1      47.1  -0.336      4.82
    #> 2     1   -50           -50         -50           1      46.9  -0.436      4.35
    #> 3     1   -50           -50         -50           1      47.0  -0.428      3.78
    #> 4     1   -50           -50         -50           1      47.8  -0.378      3.35
    #> 5     1   -50           -50         -50           1      48.4  -0.419      3.06
    #> 6     1   -50           -50         -50           1      48.2  -0.676      2.73
    #> # ℹ 2 more variables: curvature <dbl>, surface_area_ratio <dbl>

    summary <- summarize_isobath_terrain(terrain, corridors)
    summary[, c("contour_value", "slope_deg_mean", "bpi_3x3_mean", "curvature_mean")]
    #> # A tibble: 3 × 4
    #>   contour_value slope_deg_mean bpi_3x3_mean curvature_mean
    #>           <dbl>          <dbl>        <dbl>          <dbl>
    #> 1           -50           46.2     -0.01000         0.0163
    #> 2           -80           40.0     -0.0209          0.0629
    #> 3          -120           77.7      1.25           -3.77

The summary compares terrain structure at the selected depth horizons. BPI values should be interpreted using the raster’s stored vertical convention.