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https://github.com/DPIRD-FSI/extractOz
{extractOz}: Get local attribute information from GPS points for Australian agricultural research
https://github.com/DPIRD-FSI/extractOz
agriculture agriculture-data agriculture-research agroecology australia r-package soils soils-data weather weather-data
Last synced: about 1 month ago
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{extractOz}: Get local attribute information from GPS points for Australian agricultural research
- Host: GitHub
- URL: https://github.com/DPIRD-FSI/extractOz
- Owner: DPIRD-FSI
- License: gpl-3.0
- Created: 2022-05-27T08:18:42.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-12-05T04:23:13.000Z (about 1 year ago)
- Last Synced: 2024-03-28T08:01:16.173Z (9 months ago)
- Topics: agriculture, agriculture-data, agriculture-research, agroecology, australia, r-package, soils, soils-data, weather, weather-data
- Language: R
- Homepage: https://dpird-fsi.github.io/extractOz/
- Size: 38.9 MB
- Stars: 5
- Watchers: 4
- Forks: 2
- Open Issues: 3
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE.md
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
- open-sustainable-technology - extractOz - Extract the Global Runoff Data Centre agroecological zone, major soil order and weather data from your GPS sampling points. (Consumption / Agriculture and Nutrition)
README
---
title: ""
output: github_document
---# {extractOz}: A Unified Approach to Extracting Data About Australian Locations Using GPS Points
[![codecov](https://codecov.io/gh/DPIRD-FSI/extractOz/branch/main/graph/badge.svg?token=PBtL3rNIYb)](https://codecov.io/gh/DPIRD-FSI/extractOz)
[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
[![R-CMD-check](https://github.com/DPIRD-FSI/extractOz/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/DPIRD-FSI/extractOz/actions/workflows/R-CMD-check.yaml)Extract the GRDC agroecological zone, major soil order and weather data from your GPS sampling points.
Datasets for the GRDC agroecological zones and functions that automatically download modified data from the Digital Atlas of Australian Soils are included in this package for ease of use.
You may also use your own geospatial vector format file to extract similar information using the generic function, `extract_area()`.## Quick Start
You can install {extractOz} like so.
```{r setup, eval=FALSE}
if (!require("remotes")) {
install.packages("remotes")
}remotes::install_github("DPIRD-FSI/extractOz", build_vignettes = TRUE)
```Load the packages necessary to execute the examples that follow.
```{r load-libs}
library(extractOz)
library(dplyr)
```## Create Locations in WA and NSW
```{r create-locs}
locs <- list(
"Merredin" = c(x = 118.28, y = -31.48),
"Corrigin" = c(x = 117.87, y = -32.33),
"Tamworth" = c(x = 150.84, y = -31.07)
)
```## Extract the GRDC AgroEcological Zones
See `?extract_ae_zone()` for more help on how to use this function.
```{r az-zone}
z <- extract_ae_zone(x = locs)
```## Extract the Soil Order
See `?extract_soil_order()` for more help on how to use this function.
```{r soil-order}
s <- extract_daas_soil_order(x = locs)
```## Get Weather Data for These Locations in 2020
Using the previously used list of GPS points, fetch weather data from SILO for 2020.
This is just a non-working example, replace `your_api_key` with your email address below.
See `?extract_patched_point()` for more help on how to use this function.### A Note on API Keys
The examples in this README assume that you have stored your API key in your .Renviron file.
See [Chapter 8](https://rstats.wtf/r-startup.html#renviron) in "What They Forgot to Teach You About R" by Bryan _et al._ for more on storing details in your .Renviron if you are unfamiliar.```{r ppd}
three_sites <-
extract_patched_point(
x = locs,
start_date = "20200101",
end_date = "20201231",
api_key = Sys.getenv("SILO_API_KEY")
)
```## Join the Weather Data with AE Zone, Soil Order and Site Information
Now using `dplyr::left_join()`, create a single `data.frame()` of the location, GPS coordinates, agroecological zone and weather data.
```{r join-all}
left_join(z, three_sites, by = c(
"location" = "location",
"x" = "x",
"y" = "y"
)) %>%
left_join(s)
```## Code of Conduct
Please note that the {extractOz} project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html).
By contributing to this project, you agree to abide by its terms.