---
title: "Swath Profiles"
author: "Tobias Stephan"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Swath Profiles}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
editor_options: 
  markdown: 
    wrap: 72
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

This tutorial demonstrates how to create **swath profiles**, which are a 
popular method for examining the topography of an
area. These profiles represent generalized elevation profiles of a
landscape section.

`{geoprofiler}` calculates the elevation profile along a straight line
(profile line) and provides statistical parameters (e.g. mean, standard
deviation, ...) for the elevation in the nearby area.

```{r setup, message=FALSE,warning=FALSE}
# Load packages required for this tutorial:
library(geoprofiler)
library(ggplot2)
library(units)
library(sf)
library(terra)
library(tidyterra)

theme_set(theme_bw())
options(ggplot2.continuous.colour = "viridis")
options(ggplot2.continuous.fill = "viridis")
```

## Load example data

You can use any spatial data that can be converted into a `SpatRast`
object. If you have a GeoTiff for example, simply import it into R using
the function

```{r read, eval=FALSE, include=TRUE}
my_raster <- terra::rast("path/to/my/file.tif")
```

For this tutorial we use an example data set that is an snippet of the
ETOPO dataset.

```{r load_data}
data("raster_example")
crs <- "EPSG:26915" # coordinate reference system for projection

my_raster <- terra::rast(raster_example, type = "xyz", crs = "WGS84") |>
  terra::project(crs)

elevation_map <- ggplot() +
  tidyterra::geom_spatraster(data = my_raster)

elevation_map
```

## Define a profile

We can define the profile by the direction and distance from one point:

```{r azimuth, warning=FALSE, message=FALSE}
my_profile <- data.frame(lon = -90.75, lat = 48.61) |>
  sf::st_as_sf(coords = c("lon", "lat"), crs = "WGS84") |>
  profile_points(
    profile.azimuth = 135,
    profile.length = units::set_units(16, "km"),
    crs = sf::st_crs(crs)
  ) |>
  profile_line()

elevation_map +
  geom_sf(data = my_profile, lwd = 1)
```

## Extract elevation along swath profile

To calculate the elevation along the swath profiles, we need to do two
steps:

1.  Extract the elevation values along an array of straight lines
    parallel to our profile line using `swath_profile()`.
2.  Calculate some statistics within the swath using `swath_stats()`.


The function `swath_profile()` requires the profile line, the raster file, and 
amount of equally-spaced, parallel lines on either side of the profile line 
(argument `k`) and the distance between these lines (`dist` distance (same 
units as the coordinate reference system). 

Here, we want to have `k=10` lines on both sides of the profile, spaced by 
`dist=300` meters:

```{r swath1, warning=FALSE, message=FALSE}
swath <- swath_profile(my_profile, raster = my_raster, k = 5, dist = 1000)
```

The output is a list that contains the extracted elevation data and also the 
generated swath lines:

```{r swath_map, warning=FALSE, message=FALSE}
elevation_map +
  geom_sf(data = swath$lines, lwd = .1)
```
 > Note that the width of the swath profile is $2k \times \text{dist}$. 
 In our example, the width is 10.000 (m).


Next, we calculate some summary statistics of the elevation across the swath, 
such as 
min/max, mean and standard deviation using the function `swath_stats()`. We 
can plug in the length of the profile by specifying the parameter
`profile.length` by calculating the length using the function 
`profile_length()`.

```{r swath2, warning=FALSE, message=FALSE}
my_swath_profile <- swath_stats(swath, profile.length = profile_length(my_profile))
```

## Plot the swath profile

Finally, we can plot the elevation along the profile and add some of the 
calculated statistics:

```{r plot, warning=FALSE, message=FALSE}
ggplot(my_swath_profile, aes(distance, elevation)) +
  geom_ribbon(aes(ymin = min, ymax = max), fill = "grey90") +
  geom_ribbon(aes(ymin = quantile25, ymax = quantile75), fill = "grey80") +
  # geom_ribbon(aes(ymin = mean - sd, ymax = mean + sd), fill = "grey60") +
  geom_line(aes(y = median), color = "darkred", lwd = 1) +
  # geom_line(aes(y = mean), color = "dodgerblue", lwd = 1) +
  geom_line(lty = 2)
```
