Map 4: The Bight of California

Regional locator for the Southern California Bight

Rendered Map Plate

Map 4 The Bight of California

Map 4: Southern California Bight elevation, ocean hillshade, populated places, and UCSB extent

Technical Summary

  • Objective: Serve as the middle locator panel (Inset 2 of the Map 7 tryptic), focusing from the Western US down to the Southern California Bight (Point Conception to the Mexican border), with a red locator box indicating the UCSB campus extent.
  • Key Packages: terra, tidyverse, tidyterra, sf, geojsonsf
  • Data Sources:
    • 90m Western US DEM cropped to Southern California AOI (source_data/socal_aoi.geojson)
    • Global shaded relief ocean hillshade (source_data/global_raster/GRAY_HR_SR_OB.tif)
    • California Populated Places vector (source_data/tl_2023_06_place/)
    • Campus DEM bounding extent box (zoom_3_extent)
  • Styling Decisions:
    • Portrait 3 wide x 4 tall aspect ratio (width = 3, height = 4) matching the Map 7 row 1 layout.
    • Axis degree markings, coordinate labels, and legends removed for clean inset display.
    • White background set explicitly in ggsave to ensure consistent presentation across light and dark display modes.

Step-by-Step Cartographic Workflow & Intermediate Outputs

The script scripts/map_04.r refines the sub-regional Southern California Bight scale (Zoom 2) bridging continental California (Map 3) and local campus topography (Map 5).

Step 1: Cropping Regional Rasters to the Bight AOI

The 90m DEM and global shaded relief raster are cropped to the Southern California Area of Interest (socal_aoi.geojson). The extents and coordinate systems are matched.

# Crop DEM and hillshade to SoCal Bight
socal_aoi <- geojson_sf("source_data/socal_aoi.geojson")
zoom_2_cropped <- crop(dem90, socal_aoi)
zoom_2_hillshade <- crop(world_hillshade, socal_aoi)

Step 2: Intermediate Plot — Solid Gray Census Places Overlay

The census places vector layer was reprojected and plotted over the raster base. Initially, solid gray fills obscured the underlying topography of the Los Angeles Basin and Santa Barbara coastal plain.

# Intermediate plot with solid gray places
ggplot() +
  geom_raster(data = zoom_2_DEM_df, aes(x = x, y = y, fill = dem90_hf)) +
  geom_raster(data = zoom_2_hillshade_df, aes(x = x, y = y, alpha = GRAY_HR_SR_OB)) +
  geom_spatvector(data = zoom_2_places, fill = "gray") +
  geom_spatvector(data = zoom_3_extent, color = "red", fill = NA) +
  coord_sf()

Map 4 Intermediate Solid Fill

Intermediate Output: Solid gray populated place polygons covering the coastal terrain

Step 3: Polishing Alpha Transparency & Campus Extent Box

To retain topographic visibility beneath urban centers: 1. Populated place fills are made transparent (fill = NA, color = "#EEEEEE40"), with thin outlines (linewidth = 0.25). 2. The greater campus bounding box (zoom_3_extent) is reprojected and traced with a vivid red rectangle (linewidth = 1.2). 3. Axis coordinates and tick marks are eliminated (axis.text = element_blank(), axis.ticks = element_blank()). 4. An informative subtitle anchors the geographic boundaries: “Point Conception to Mexico”.

# Finalizing transparent vectors and red zoom 3 extent
zoom_2_final_plot <- ggplot() +
  geom_raster(data = zoom_2_DEM_df, aes(x = x, y = y, fill = dem90_hf)) +
  scale_fill_viridis_c(guide = "none") +
  geom_raster(data = zoom_2_hillshade_df, aes(x = x, y = y, alpha = GRAY_HR_SR_OB)) +
  scale_alpha(range = c(0.05, 0.5), guide = "none") +
  geom_spatvector(data = zoom_2_places, fill = NA, color = "#EEEEEE40", linewidth = 0.25) +
  geom_spatvector(data = zoom_3_extent_proj, color = "red", fill = NA, linewidth = 1.2) +
  theme_minimal() +
  coord_sf(expand = FALSE) +
  ggtitle("On the Bight of California", subtitle = "Point Conception to Mexico")

Map 4 Final Inset

Final Zoom 2 Output Panel

Full R Script (scripts/map_04.r)

Show R Code 
# map 4
# clean the environment and hidden objects

rm(list = ls())

library(sf)
library(terra)
library(tidyterra)
library(geojsonsf)
library(ggplot2)
library(dplyr)

# set map number
current_sheet <- 4
# set ggplot counter
current_ggplot <- 0

# our auto ggtitle maker
gg_labelmaker <- function(plot_num) {
  gg_title <- c("Map:", current_sheet, " ggplot:", plot_num)
  plot_text <- paste(gg_title, collapse = " ")
  print(plot_text)
  current_ggplot <<- plot_num
  return(plot_text)
}
# every ggtitle should be:
# ggtitle(gg_labelmaker(current_ggplot+1))
# end automagic ggtitle


# ############################
# Map 4
# Zoom 2: Bite of California

# use campus CRS as standard
campus_DEM <- rast("source_data/campus_DEM.tif")
crs(campus_DEM)
campus_crs <- crs(campus_DEM)

# the extent of the campus_DEM
# is the zoom 3 indicator,
zoom_3_extent <- ext(campus_DEM) %>% vect()
crs(zoom_3_extent) <- campus_crs


# Get the west coast DEM and
# Crop it to zoom 2 AOI
# socal_aoi.geojson
zoom_2 <- rast("source_data/dem90_hf/dem90_hf.tif")
plot(zoom_2)

# AOI came from a Planet harvest that we did
zoom_2_crop_extent <- geojson_sf("source_data/socal_aoi.geojson")
zoom_2_crop_extent <- vect(zoom_2_crop_extent)

crs(zoom_2_crop_extent) == crs(zoom_2)

# project it to match west_us
# this will also 'rotate' southern california
# when we crop it, making it visually more readable
zoom_2_crop_extent <- project(zoom_2_crop_extent, crs(zoom_2))
crs(zoom_2_crop_extent) == crs(zoom_2)

# plot them together
# to confirm that's the correct extent
# that you want to crop to
plot(zoom_2)
polys(zoom_2_crop_extent)

# now crop to that extent
zoom_2_cropped <- crop(x = zoom_2, y = zoom_2_crop_extent)
plot(zoom_2_cropped)
# we need water! #####################

# batho-topo / SB_bath won't be big enough
bath <- rast("source_data/SB_bath.tif")
plot(bath)


# let's try the global hillshade?
# is it a hillshade? it looks like it.
zoom_2_water <- rast("source_data/global_raster/GRAY_HR_SR_OB.tif")
plot(zoom_2_water)

zoom_2_crop_extent <- project(zoom_2_crop_extent, crs(zoom_2_water))
zoom_2_water <- crop(x = zoom_2_water, y = (zoom_2_crop_extent))
plot(zoom_2_water)

crs(zoom_2_water) == crs(zoom_2_cropped)
zoom_2_water <- project(zoom_2_water, crs(zoom_2_cropped))
crs(zoom_2_water) == crs(zoom_2_cropped)


# make dataframes for ggplotting
zoom_2_DEM_df <- as.data.frame(zoom_2_cropped, xy = TRUE)
zoom_2_hillshade_df <- as.data.frame(zoom_2_water, xy = TRUE)
str(zoom_2_hillshade_df)
str(zoom_2_DEM_df)


# let's START
# with the graticule that we ended map 3 with:

ggplot() +
  geom_raster(
    data = zoom_2_hillshade_df,
    aes(x = x, y = y, alpha = GRAY_HR_SR_OB)
  ) +
  scale_alpha(range = c(0.05, 0.55), guide = "none") +
  coord_sf() +
  theme(
    axis.title.x = element_blank(),
    axis.title.y = element_blank(),
    legend.position = "none",
    panel.ontop = TRUE,
    panel.grid.major = element_line(color = "#FFFFFF33"),
    panel.background = element_blank()
  ) +
  ggtitle("Map 4: zm 2: hillshade", subtitle = gg_labelmaker(current_ggplot + 1))

ggplot() +
  geom_raster(
    data = zoom_2_DEM_df,
    aes(x = x, y = y, fill = dem90_hf)
  ) +
  scale_fill_viridis_c() +
  coord_sf() +
  theme(
    axis.title.x = element_blank(),
    axis.title.y = element_blank(),
    legend.position = "none",
    panel.ontop = TRUE,
    panel.grid.major = element_line(color = "#FFFFFF33"),
    panel.background = element_blank()
  ) +
  ggtitle("Map 4: zm 2: dem", subtitle = gg_labelmaker(current_ggplot + 1))

# try to overlay
ggplot() +
  geom_raster(
    data = zoom_2_DEM_df,
    aes(x = x, y = y, fill = dem90_hf)
  ) +
  scale_fill_viridis_c() +
  geom_raster(
    data = zoom_2_hillshade_df,
    aes(x = x, y = y, alpha = GRAY_HR_SR_OB)
  ) +
  scale_alpha(range = c(0.05, 0.55), guide = "none") +
  coord_sf() +
  theme(
    axis.title.x = element_blank(),
    axis.title.y = element_blank(),
    legend.position = "none",
    panel.ontop = TRUE,
    panel.grid.major = element_line(color = "#FFFFFF33"),
    panel.background = element_blank()
  ) +
  ggtitle("Map 4: zm 2: Overlay test", subtitle = gg_labelmaker(current_ggplot + 1))

# so close!!!!!!


# now I need the next zoom indicator
# I need to project that too.
crs(zoom_3_extent) == crs(zoom_2_cropped)
zoom_3_extent <- project(zoom_3_extent, zoom_2_cropped)
plot(zoom_3_extent)

ggplot() +
  geom_raster(
    data = zoom_2_DEM_df,
    aes(x = x, y = y, fill = dem90_hf)
  ) +
  scale_fill_viridis_c() +
  geom_raster(
    data = zoom_2_hillshade_df,
    aes(x = x, y = y, alpha = GRAY_HR_SR_OB)
  ) +
  scale_alpha(range = c(0.05, 0.55), guide = "none") +
  coord_sf() +
  theme(
    axis.title.x = element_blank(),
    axis.title.y = element_blank(),
    legend.position = "none",
    panel.ontop = TRUE,
    panel.grid.major = element_line(color = "#FFFFFF33"),
    panel.background = element_blank()
  ) +
  ggtitle("Map 4: zm 2: Overlay test", subtitle = gg_labelmaker(current_ggplot + 1))


# add the zoom indicator to the ggplot
ggplot() +
  geom_spatvector(data = zoom_3_extent, color = "red", fill = NA, lwd = 1) +
  theme(
    panel.grid.major = element_line(color = "#FFFFFF33"),
    panel.background = element_blank()
  ) +
  coord_sf()

# now that I've added tidyterra, both the above geom_spatvecor
# and the below geom_sf work

ggplot() +
  geom_raster(
    data = zoom_2_DEM_df,
    aes(x = x, y = y, fill = dem90_hf)
  ) +
  scale_fill_viridis_c() +
  geom_raster(
    data = zoom_2_hillshade_df,
    aes(x = x, y = y, alpha = GRAY_HR_SR_OB)
  ) +
  scale_alpha(range = c(0.05, 0.55), guide = "none") +
  #  geom_spatvector(data=zoom_3_extent, color="red", fill=NA, lwd=1)+
  geom_sf(data = zoom_3_extent, color = "red", fill = NA, lwd = 1) +
  coord_sf() +
  theme(
    axis.title.x = element_blank(),
    axis.title.y = element_blank(),
    legend.position = "none",
    panel.ontop = TRUE,
    panel.grid.major = element_line(color = "#FFFFFF33"),
    panel.background = element_blank()
  ) +
  ggtitle("Map 4: zm 2: Overlay with Indicator", subtitle = gg_labelmaker(current_ggplot + 1))


ggplot() +
  geom_raster(
    data = zoom_2_DEM_df,
    aes(x = x, y = y, fill = dem90_hf)
  ) +
  scale_fill_viridis_c() +
  geom_raster(
    data = zoom_2_hillshade_df,
    aes(x = x, y = y, alpha = GRAY_HR_SR_OB)
  ) +
  scale_alpha(range = c(0.05, 0.55), guide = "none") +
  geom_sf(data = zoom_3_extent, color = "red", fill = NA, lwd = 1) +
  theme(
    axis.title.x = element_blank(),
    axis.title.y = element_blank(),
    legend.position = "none",
    panel.ontop = TRUE,
    panel.grid.major = element_line(color = "#FFFFFF33"),
    panel.background = element_blank()
  ) +
  coord_sf() +
  ggtitle("Map 4: zm 2: Different hillshade", subtitle = gg_labelmaker(current_ggplot + 1))


# 'california populated places'
# which is census data
# for the sake of a nice vizualization
places <- vect("source_data/tl_2023_06_place/tl_2023_06_place.shp")
plot(places)
crs(places) == campus_crs
places <- project(places, campus_crs)

# places still not showing up
#---------------------------------------

str(zoom_2_hillshade_df)
# For zoom 2, places does not overlay nicely.
# this is another CRS error
ggplot() +
  geom_raster(
    data = zoom_2_DEM_df,
    aes(x = x, y = y, fill = dem90_hf)
  ) +
  scale_fill_viridis_c() +
  geom_raster(
    data = zoom_2_hillshade_df,
    aes(x = x, y = y, alpha = GRAY_HR_SR_OB)
  ) +
  scale_alpha(range = c(0.05, 0.5), guide = "none") +
  geom_spatvector(data = places, fill = "gray") +
  geom_spatvector(data = zoom_3_extent, color = "red", fill = NA) +
  theme(
    axis.title.x = element_blank(),
    axis.title.y = element_blank(),
    legend.position = "none",
    panel.ontop = TRUE,
    panel.grid.major = element_line(color = "#FFFFFF33"),
    panel.background = element_blank()
  ) +
  coord_sf() +
  ggtitle("Map 4: zm 2: Zoom test 2", subtitle = gg_labelmaker(current_ggplot + 1))

crs(zoom_2_cropped) == campus_crs
crs(zoom_2_water) == campus_crs
crs(zoom_2_cropped) == crs(zoom_2_water)
crs(places) == campus_crs
# places is the one to reproject right now.

places <- project(places, crs(zoom_2_cropped))

ggplot() +
  geom_raster(
    data = zoom_2_DEM_df,
    aes(x = x, y = y, fill = dem90_hf)
  ) +
  scale_fill_viridis_c() +
  geom_raster(
    data = zoom_2_hillshade_df,
    aes(x = x, y = y, alpha = GRAY_HR_SR_OB)
  ) +
  scale_alpha(range = c(0.05, 0.5), guide = "none") +
  geom_spatvector(data = places, fill = "gray") +
  geom_spatvector(data = zoom_3_extent, color = "red", fill = NA) +
  theme(
    axis.title.x = element_blank(),
    axis.title.y = element_blank(),
    legend.position = "none",
    panel.ontop = TRUE,
    panel.grid.major = element_line(color = "#FFFFFF33"),
    panel.background = element_blank()
  ) +
  coord_sf() +
  ggtitle("Map 4: zm 2: re-projected places", subtitle = gg_labelmaker(current_ggplot + 1))

# this plots, but to the full extent of california.
# we are gonna need to crop places

# this also plots, but at the full extent of california.

zoom_2_places <- crop(places, zoom_2_cropped)

ggplot() +
  geom_raster(
    data = zoom_2_DEM_df,
    aes(x = x, y = y, fill = dem90_hf)
  ) +
  scale_fill_viridis_c() +
  geom_raster(
    data = zoom_2_hillshade_df,
    aes(x = x, y = y, alpha = GRAY_HR_SR_OB)
  ) +
  scale_alpha(range = c(0.05, 0.5), guide = "none") +
  geom_spatvector(data = zoom_2_places, fill = "gray") +
  geom_spatvector(data = zoom_3_extent, color = "red", fill = NA) +
  theme(
    axis.title.x = element_blank(),
    axis.title.y = element_blank(),
    legend.position = "none",
    panel.ontop = TRUE,
    panel.grid.major = element_line(color = "#FFFFFF33"),
    panel.background = element_blank()
  ) +
  coord_sf() +
  ggtitle("Map 4: zm 2: re-projected places", subtitle = gg_labelmaker(current_ggplot + 1))

# it plots!!!!! but ugly.
ggsave("images/map4.png", width = 3, height = 4, plot = last_plot(), bg = "white")

# how can I make the fill transparent?

ggplot() +
  geom_spatvector(data = zoom_2_places, color = "#D3D3D380", fill = "#D4D4D450") +
  coord_sf() +
  ggtitle("Map 4: zm 2: re-projected places", subtitle = gg_labelmaker(current_ggplot + 1))


# better
# and add places viz from map 3
ggplot() +
  geom_raster(
    data = zoom_2_DEM_df,
    aes(x = x, y = y, fill = dem90_hf)
  ) +
  scale_fill_viridis_c() +
  geom_raster(
    data = zoom_2_hillshade_df,
    aes(x = x, y = y, alpha = GRAY_HR_SR_OB)
  ) +
  scale_alpha(range = c(0.05, 0.5), guide = "none") +
  geom_spatvector(data = zoom_2_places, fill = "NA", color = "#EEEEEE33") +
  geom_spatvector(data = zoom_3_extent, color = "red", fill = NA) +
  theme_minimal() +
  theme(
    axis.title.x = element_blank(),
    axis.title.y = element_blank(),
    legend.position = "none",
    panel.ontop = TRUE,
    panel.grid.major = element_line(color = "#FFFFFF33"),
    panel.background = element_blank()
  ) +
  coord_sf() +
  ggtitle("Map 4: zm 2: The Bight of California", subtitle = gg_labelmaker(current_ggplot + 1))

# and a final one for saving
zoom_3_extent_proj <- project(zoom_3_extent, crs(zoom_2_cropped))

zoom_2_final_plot <- ggplot() +
  geom_raster(
    data = zoom_2_DEM_df,
    aes(x = x, y = y, fill = dem90_hf)
  ) +
  scale_fill_viridis_c(guide = "none") +
  geom_raster(
    data = zoom_2_hillshade_df,
    aes(x = x, y = y, alpha = GRAY_HR_SR_OB)
  ) +
  scale_alpha(range = c(0.05, 0.5), guide = "none") +
  geom_spatvector(data = zoom_2_places, fill = "NA", color = "#EEEEEE40", linewidth = 0.25) +
  geom_spatvector(data = zoom_3_extent_proj, color = "red", fill = NA, linewidth = 1.2) +
  theme_minimal() +
  theme(
    axis.title = element_blank(),
    axis.text = element_blank(),
    axis.ticks = element_blank(),
    legend.position = "none",
    panel.ontop = TRUE,
    panel.grid.major = element_line(color = "#FFFFFF33"),
    panel.background = element_blank()
  ) +
  coord_sf(expand = FALSE) +
  ggtitle("On the Bight of California",
    subtitle = "Point Conception to Mexico"
  )

zoom_2_final_plot

ggsave("images/map4.png", width = 3, height = 4, plot = zoom_2_final_plot, bg = "white")
ggsave("images/map_04.png", width = 3, height = 4, plot = zoom_2_final_plot, bg = "white")
ggsave("final_output/map_04.png", width = 3, height = 4, plot = zoom_2_final_plot, bg = "white")