## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(echo = TRUE, error = FALSE, fig.retina = 1, dpi = 100) ## ----load packages, message=FALSE, warning=FALSE------------------------------ library(voluModel) # Since this is the package this vignette is about. library(tibble) # For data organization library(ggplot2) # For supplementary visualization library(fields) # For raster interpolation library(terra) # Now being transitioned in ## ----environmental data loading temperature, eval=T, message=FALSE, warning=FALSE, asis=T---- # Temperature td <- tempdir() unzip(system.file("extdata/woa18_decav_t00mn01_cropped.zip", package = "voluModel"), exdir = paste0(td, "/temperature"), junkpaths = T) temperature <- vect(paste0(td, "/temperature/woa18_decav_t00mn01_cropped.shp")) # Looking at the dataset as.data.frame(temperature[1:5,1:10]) # Plotting the dataset layout(matrix(c(1, 2), ncol=2, byrow=TRUE), widths=c(4, 1)) land <- rnaturalearth::ne_countries(scale = "small", returnclass = "sf")[1] temperatureForPlot <- temperature crs(temperatureForPlot) <- crs(land) ext <- ext(temperatureForPlot) plot(temperatureForPlot, main = "Distribution of voluModel Subset\nof WOA Temperature 2018", pch = 20, col = "red", xlim = ext[1:2], ylim = ext[3:4], cex = .6, mar = c(2,2,3,2)) plot(land, col = "black", add = T) # What does the WOA depth structure look like? depths <- names(temperatureForPlot) depths <- as.numeric(gsub(depths[-1], pattern = "[d,M]", replacement = "")) plot(0, xlim = c(0,1), ylim = c(0-max(depths), 0), axes=FALSE, type = "n", xlab = "", ylab = "Depth Intervals (m)") axis(2, at = 0-depths, labels = depths) ## ----temperature processing, eval=TRUE---------------------------------------- # Creating a bottom raster temperatureBottom <- bottomRaster(temperature) # Creating a SpatRaster vector template <- centerPointRasterTemplate(temperature) tempTerVal <- rasterize(x = temperature, y = template, field = names(temperature)) # Get names of depths envtNames <- gsub("[d,M]", "", names(temperature)) envtNames[[1]] <- "0" names(tempTerVal) <- envtNames temperature <- tempTerVal rm(tempTerVal) # How do these files look? par(mfrow=c(1,2)) p1 <- oneRasterPlot(temperature[[1]], land = land, landCol = "black", title= "Surface Temperature (C)") p2 <- oneRasterPlot(temperatureBottom,land = land, landCol = "black", title = "Bottom Temperature (C)") ## ----environmental data loading oxygen, eval=T, message=FALSE, warning=FALSE, asis=T---- td <- tempdir() unzip(system.file("extdata/woa18_all_A00mn01_cropped.zip", package = "voluModel"), exdir = paste0(td, "/oxygen"), junkpaths = T) oxygen <- vect(paste0(td, "/oxygen/woa18_all_A00mn01_cropped.shp")) plot(oxygen, main = "Distribution of voluModel subset of WOA AOU 2018", pch = 20, col = "red", xlim = ext[1:2], ylim = ext[3:4], cex = .6) plot(land, col = "black", add = T) ## ----interpolate oxygen, warning=FALSE, eval = T------------------------------ # Creating a SpatRaster vector for the first 10 depth layers oxygen <- oxygen[,1:10] # Remove this line if you want to process the whole file oxygen <- rasterize(x = oxygen, y = template, field = names(oxygen)) #Uses same raster template as temperature for (i in 1:nlyr(oxygen)){ oxygen[[i]] <- interpolateRaster(oxygen[[i]], lon.lat = T, fast = T, aRange = 30) #Thin plate spline interpolation oxygen[[i]] <- crop(mask(x = oxygen[[i]], mask = temperature[[i]]), temperature[[i]]) } # Change names to match tempT names(oxygen) <- envtNames[1:nlyr(oxygen)] ## ----smoothing oxygen, eval=TRUE---------------------------------------------- # Smoothing tempO and saving oxygenSmooth <- oxygen for (i in 1:nlyr(oxygenSmooth)){ oxygenSmooth[[i]] <- smoothRaster(oxygenSmooth[[i]], lon.lat = T) #Thin plate spline interpolation oxygenSmooth[[i]] <- crop(mask(x = oxygenSmooth[[i]], mask = temperature[[i]]), temperature[[i]]) } # Change names to match tempT and save names(oxygenSmooth) <- names(oxygen) oxygenSmooth <- oxygenSmooth par(mfrow=c(1,2)) p3 <- oneRasterPlot(oxygen[[1]], land = land, landCol = "black", title= "Surface Apparent Oxygen Utilization\n(µmol/kg), interpolated") p4 <- oneRasterPlot(oxygenSmooth[[1]], land = land, landCol = "black", title = "Surface Apparent Oxygen Utilization\n(µmol/kg), interpolated and smoothed") ## ----cleanup temporary directory---------------------------------------------- unlink(td, recursive = T)