add MSSM 2x2 survey grid data

.Rbuildignore

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 ^scratch$
 ^NEWS\.md$
 ^\.github$
+^data-raw$

R/data.R

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+#' Multispecies Small-Mesh Bottom Trawl (MSSM) Survey Grid
+#'
+#' A 2x2 km grid for the Multispecies Small-Mesh Bottom Trawl Survey (MSSM; formerly
+#' known as 'shrimp survey'). This grid covers WCVI Shrimp Survey Areas 124 and 125.
+#' The `last_samp_year is the last year a grid cell was sampled as of 2023, with
+#' the most consistent resampling (spatially) occurring in grid cells last sampled
+#' after 2008 (GFBioField used used starting in 2009).
+#'
+#' @format ## `mssm_grid`
+#' A data frame with 493 rows and 5 columns:
+#' \describe{
+#'   \item{survey_abbrev}{Survey abbreviation}
+#'   \item{longitude, latitude}{Longitude and latitude of the centroid of 2x2 km
+#'     grid cells}
+#'   \item{area}{Area of the grid cells, in km^2}
+#'   \item{last_samp_year}{The last year a grid cell was sampled as of the date
+#'     this dataset was created (Oct 2023)}
+#' }
+"mssm_grid"

data-raw/mssm_grid.R

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+library(magrittr)
+
+# Spherical geometries problematic
+sf::sf_use_s2(FALSE)
+
+# Query GFBio - need DFO VPN access
+#pcod_dat <- gfdata::get_survey_sets(species = "pacific cod", ssid = 7)
+#saveRDS(pcod_dat, file.path('data-raw', 'pcod-mssm-survey-sets.rds'))
+pcod_dat <- readRDS(file.path('data-raw', 'pcod-mssm-survey-sets.rds'))
+pcod_dat <- pcod_dat |>
+  dplyr::filter(!is.na(longitude)) |>
+  sdmTMB::add_utm_columns(c('longitude', 'latitude')) |>
+  dplyr::mutate(row_id = dplyr::row_number())
+
+# Use equal distance projection
+pcod_sf <-
+  pcod_dat |>
+  dplyr::select(year, X, Y) |>
+  sf::st_as_sf(coords = c('X', 'Y'), crs = 32609)
+
+pcod_years <- dplyr::select(pcod_dat, row_id, year)
+
+# Use 2x2 km grid size in units of our polygon shape file
+grid_spacing <- 2
+
+# Create grid over the bounding box of the polygon
+full_grid <- pcod_sf |>
+  sf::st_make_grid(cellsize = c(grid_spacing, grid_spacing)) |>
+  sf::st_as_sf() |>
+  dplyr::rename(geometry = x)
+
+# Get grid cells that overlap with at least one sampling point
+intersected <- sf::st_intersects(full_grid, pcod_sf)
+
+id_intersect <- intersected |> purrr::map_dbl(length) > 0
+last_year <- intersected |>
+  purrr::map_dbl(\(row) if (length(row) > 0) {max(pcod_years[row, ]$year)} else {NA})
+
+full_grid$last_samp_year <- last_year
+
+mssm_grid_sf <- full_grid[id_intersect, ] |>
+  dplyr::mutate(survey_abbrev = "MSSM WCVI")
+
+mssm_grid <- mssm_grid_sf |>
+  sf::st_centroid() %>%
+  dplyr::mutate(survey_abbrev = "MSSM WCVI",
+                #ssid = 7,
+                longitude = sf::st_coordinates(.)[,1],
+                latitude = sf::st_coordinates(.)[,2],
+                area = grid_spacing * grid_spacing) |>
+  sf::st_drop_geometry() |>
+  dplyr::as_tibble() |>
+  dplyr::select(survey_abbrev, longitude, latitude, area, last_samp_year)
+
+# Option to save an SF object
+#saveRDS(mssm_grid_sf, file.path('data-raw', 'mssm_grid_sf.rds'))
+#usethis::use_data(mssm_grid)
+# Visualise grid before and after 2009
+# mssm_grid_sf |>
+#   mutate(last_samp_year = ifelse(last_samp_year >= 2009, ">= 2009", " < 2009")) |>
+# ggplot(data = _) +
+#   geom_sf(aes(fill = last_samp_year), alpha = 0.8) +
+#   viridis::scale_fill_viridis(discrete = TRUE) +
+#   gfplot::theme_pbs()
+
+usethis::use_data(mssm_grid, overwrite = TRUE)