Calculating effect of areal closure

• Catch distribution by depth
• Catch composition by depth and longitude

library(duckdbfs)
library(sf)
library(tidyverse)
library(stars)
library(terra)
library(tmap)
tmap_mode("view")
library(here)

dx <- 0.005
dy <- dx / 2   # grid resolution approximately 275 x 275 meters
q <- 
  open_dataset("/home/haf/einarhj/stasi/fishydata/data//ais/trail") |> 
  # Not in harbour
  filter(.cid > 0,                           # .cid positive -> not in harbour
         whack == FALSE,
         between(year, 2008, 2024),
         between(speed, s1, s2),
         between(time, t1, t2)) |> 
  mutate(x = lon %/% dx * dx + dx/2,
         y = lat %/% dy * dy + dy/2) |> 
  group_by(year, gid_trip, x, y) |> 
  summarise(dt = sum(dt, na.rm = TRUE) / 60,    # effort as time
            catch = sum(catch_total, na.rm = TRUE),
            .groups = "drop")
g <- 
  q |> 
  group_by(gid_trip, x, y) |> 
  summarise(dt = sum(dt, na.rm = TRUE),
            catch = sum(catch, na.rm = TRUE),
            .groups = "drop") |> 
  collect()
library(here)
v1 <- read_sf(here("vernd1.gpkg")) |> st_cast("POLYGON")
v2 <- read_sf(here("vernd2.gpkg")) |> st_cast("POLYGON")
v <- st_union(v1, v2)
z <- 
  read_sf("/u3/haf/gisland/data/depth/sjomaelingar_dypislinur.gpkg") |> 
  filter(depth %in% c(300, 400, 500))
zr <- rast("/u3/haf/gisland/data/gebco_2024_n89.0_s34.0_w-83.0_e69.0.tif")
g2 <- 
  g |> 
  filter(gid_trip == 6) |> 
  st_as_sf(coords = c("x", "y"),
           crs = 4326,
           remove = FALSE) |> 
  mutate(inside = ramb::rb_st_keep(geometry, v))
xyz <- terra::extract(zr, g2)
g2$z <- xyz$`gebco_2024_n89.0_s34.0_w-83.0_e69.0`
g2 |> 
  st_drop_geometry() |> 
  mutate(z = -z) |> 
  filter(z > 0) |> 
  mutate(z = santoku::chop(z, seq(0, 1000, by = 100))) |> 
  group_by(z) |> 
  reframe(catch = sum(catch, na.rm = TRUE)) |> 
  mutate(p = catch / sum(catch)) |> 
  ggplot(aes(z, p)) +
  geom_col() +
  coord_flip()


g2 |> 
  st_drop_geometry() |> 
  group_by(gid_trip, tmp) |> 
  summarise(dt = sum(dt, na.rm = TRUE),
            catch = sum(catch, na.rm = TRUE)) |> 
  group_by(gid_trip) |> 
  mutate(p = round(catch / sum(catch) * 100, 2)) |> 
  ungroup() |> 
  filter(tmp == TRUE)
  



g |> 
  filter(!gid_trip %in% c(9, 10)) |> 
  group_by(x, y) |> 
  reframe(z = sum(catch, na.rm = TRUE)) |> 
  filter(
       between(x, -30, -10),
       between(y, 62, 68.5)) |> 
  mutate(z = ramb::rb_cap_winsorize(z, 0.99)) |> 
  mutate(z = sqrt(z)) |> 
  rast(type = "xyz",
       crs = "epsg:4326") |> 
  st_as_stars() |> 
  tm_shape() +
  tm_raster("z", palette = "-inferno") +
  tm_shape(v1) +
  tm_borders() +
  tm_shape(v2) +
  tm_borders() +
  tm_shape(z) +
  tm_borders()