--- title: "amadeus workflow" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{amadeus workflow} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} date: "2024-07-29" author: "Mitchell Manware" --- ```{r setup, include = FALSE} # packages knitr::opts_chunk$set( collapse = TRUE, comment = "" ) library(amadeus) ``` The following vignette will demonstrate how to download, process, and calculate covariates using `amadeus` functions. The examples will utilize air temperature at 2m height ("air.2m") data from the NOAA North American Regional Reanalysis (NARR) dataset.\insertRef{web_NARRabout} ## Download Download data for years 2021 and 2022 with `download_data`. ```{r, eval = FALSE} dir <- tempdir() download_data( dataset_name = "narr", variable = "air.2m", year = c(2021, 2022), directory_to_save = dir, acknowledgement = TRUE, download = TRUE, remove_command = TRUE ) ``` Check for the downloaded files. ```{r, eval = FALSE} list.files(paste0(dir, "/air.2m")) ``` ```{r, echo = FALSE} cat('[1] "air.2m.2021.nc" "air.2m.2022.nc"\n') ``` ## Process Process data for all dates from December 28, 2021 to January 3, 2022 with `process_covariates`. ```{r, eval = FALSE} temp_process <- process_covariates( covariate = "narr", variable = "air.2m", date = c("2021-12-28", "2022-01-03"), path = paste0(dir, "/air.2m") ) ``` Check the processed `SpatRaster` object. ```{r, eval = FALSE} temp_process ``` ```{r, echo = FALSE} cat( "class : SpatRaster dimensions : 277, 349, 7 (nrow, ncol, nlyr) resolution : 32462.99, 32463 (x, y) extent : -16231.49, 11313351, -16231.5, 8976020 (xmin, xmax, ymin, ymax) coord. ref. : +proj=lcc +lat_0=50 +lon_0=-107 +lat_1=50 +lat_2=50 +x_0=5632642.22547 +y_0=4612545.65137 +datum=WGS84 +units=m +no_defs sources : air.2m.2021.nc:air (4 layers) air.2m.2022.nc:air (3 layers) varnames : air (Daily Air Temperature at 2 m) air (Daily Air Temperature at 2 m) names : air.2~11228, air.2~11229, air.2~11230, air.2~11231, air.2~20101, air.2~20102, ... unit : K, K, K, K, K, K, ... time : 2021-12-28 to 2022-01-03 UTC\n" ) ``` ## Calculate covariates Calculate covariates for North Carolina county boundaries with `calc_covariates`. County boundaries are accessed with the `tigris::counties` function.\insertRef{package_tigris} `geom = TRUE` will return the covariates as a `SpatVector` object. ```{r, eval = FALSE} library(tigris) temp_covar <- calc_covariates( covariate = "narr", from = temp_process, locs = tigris::counties("NC", year = 2021), locs_id = "NAME", radius = 0, geom = TRUE ) ``` Check the calculated covariates `SpatVector` object. ```{r, eval = FALSE} temp_covar ``` ```{r, echo = FALSE} cat( "class : SpatVector geometry : polygons dimensions : 700, 3 (geometries, attributes) extent : 7731783, 8506154, 3248490, 3694532 (xmin, xmax, ymin, ymax) coord. ref. : +proj=lcc +lat_0=50 +lon_0=-107 +lat_1=50 +lat_2=50 +x_0=5632642.22547 +y_0=4612545.65137 +datum=WGS84 +units=m +no_defs names : NAME time air.2m_0 type : values : Chatham 2021-12-28 289.3 Alamance 2021-12-28 288.8 Davidson 2021-12-28 289.1\n") ```