explore_blocks

1 Goal

What are the spatial analytical units for which we should report sensitivity indicators?

2 Hierarchy: Shelf > Region > OPD > Block > Aliquot

spatial units: shlf > rgn > opd > blk > alq

And fields to apply to each: - {unit}_id (integer) - {unit}_key (character) - {unit}_name (character)

• opd Official Protraction Diagrams (OPDs) (2 degrees wide by one degree high)
  • blk Blocks (2304 hectares; 4800 x 4800 meters on a UTM).
    • alq Aliquot (144 hectares)

BUT very inconsistent – see:

• Google Drive
  msens/data/raw/boem.gov/blocks/README

3 Aliquots

• BOEM Block Aliquot | MarineCadastre: dense so requires pgis db to pg_tile service

These are numerous so probably require a database or other tiling strategy to serve (vs native R).

4 Wind Energy

Other:

• Wind Energy Areas

• Wind Energy Leases

• Wind Energy Planning Areas

Renewable Energy - GIS Data | BOEM
Renewable Energy Leases and Planning Areas
Boundaries of renewable energy lease areas, wind planning areas, and marine hydrokinetic planning areas.

Code

# libraries ----
librarian::shelf(
  dplyr, glue, janitor, here, knitr, 
  leaflet, leaflet.extras, # mapview, 
  rmapshaper, sf,
  quiet = T)

# paths ----
dir_data <- "/Users/bbest/My Drive/projects/msens/data"
wind_gdb <- glue("{dir_data}/raw/boem.gov/BOEMWindLayers_4Download.gdb")
lse_geo <- glue("{dir_data}/raw/boem.gov/BOEM_Wind_Leases_9_27_2023.geojson")
pln_geo <- glue("{dir_data}/raw/boem.gov/BOEM_Wind_Planning_Areas_10_06_2023.geojson")

(d_wind_lyrs <- st_layers(wind_gdb, do_count = T))

Driver: OpenFileGDB 
Available layers:
                                  layer_name geometry_type features fields
1             BOEM_MHKLeasesandPlanningAreas Multi Polygon       17     21
2 BOEM_Wind_Planning_Area_Outlines_8_30_2023 Multi Polygon       23      8
3                 BOEM_Wind_Leases_9_27_2023 Multi Polygon     3880     18
4              Wind_Lease_Outlines_9_27_2023 Multi Polygon       41     15
5        BOEM_Wind_Planning_Areas_10_06_2023 Multi Polygon     8685     11
  crs_name
1   WGS 84
2   WGS 84
3   WGS 84
4   WGS 84
5   WGS 84

Code

wind_lyrs <- d_wind_lyrs$name

ply_wind_lse <- read_sf(wind_gdb, wind_lyrs[3]) # BOEM_Wind_Leases_9_27_2023
ply_wind_pln <- read_sf(wind_gdb, wind_lyrs[5]) # BOEM_Wind_Planning_Areas_10_06_2023

ply_wind_lse_s05 <- ply_wind_lse |> 
  ms_simplify(keep=0.05, keep_shapes=F)
ply_wind_pln_s05 <- ply_wind_pln |> 
  ms_simplify(keep=0.05, keep_shapes=F)

# mapView(
#   ply_wind_lse_s05,
#   layer.name    = "Wind Leases",
#   col.regions   = "red") +
#   mapview(
#     ply_wind_pln_s05, 
#     layer.name  = "Wind Planning Areas",
#     col.regions = "green")
msens::ms_basemap() |> 
  addPolygons(
    data      = ply_wind_lse_s05, 
    weight    = 1,
    color     = "blue",
    fillColor = "blue",
    label     = ~glue("{COMPANY}: block {BLOCK_NUMBER}")) |> 
  addPolygons(
    data      = ply_wind_pln_s05, 
    weight    = 1,
    color     = "green",
    fillColor = "green",
    label     = ~glue("{PRIMARY_WPA_CATEGORY}: block {BLOCK_NUMBER}")) |> 
  addLegend(
    labels    = c("Leases", "Planning Areas"),
    colors    = c("blue", "green"),
    opacity   = 0.8,
    position  = "bottomright") |> 
  addFullscreenControl()

5 Oil & Gas Energy

Oil & Gas Energy - Maps and GIS Data | BOEM
GIS Data/Shapefiles
Download GIS data files for BOEM Offshore block grids, boundaries, active leases, wells, pipelines, and more.