{fifo}: ‘Fly in, fly out’ to extract the valuable data you need from your georeferenced datasets for Australia
About {fifo}
{fifo} is a re-imagined fork of {extractOz} that is under active development providing a unified interface to extract data from georeferenced Australian data sets using GPS points, i.e., latitude and longitude coordinates, that include all the data that the original {extractOz} supports and more:
- Australian Agricultural and Grazing Industries Survey (AAGIS) regions via {read.abares};
- Australian topsoil layer 1 thickness via {read.abares};
- Grains Research and Development Corporation (GRDC) Agroecoregions via this package;
- Australia’s Terrestrial Ecosystem Research Network (TERN) data including:
- Digital Atlas of Australian Soils via this package;
- Queensland’s Scientific Information for Land Owners (SILO) weather data including:
- SILO’s Data Drill 5km x 5km gridded weather data via {weatherOz};
- SILO’s Patched Point station-based weather data via {weatherOz};
- NASA POWER weather data via {nasapower}; or
- Your own geospatial data layer.
{fifo} is named after a work arrangement commonly used in Australian mining where an employer will temporarily transport employees to a work location or site of work, typically a mine, and transport them back for a period of rest.
Differences With {extractOz}
{fifo}
- uses
xyrather thanxas the primary function argument to provide the geo-locations of interest; - uses
locationsrather thannamesto denote the named geo-locations of the paired lon lat values to avoid confusion with base R functionality; - provides access to TERN data ({extractOz} does not);
- provides access to ABARES data ({extractOz} does not); and
- allows direct use of
data.frameobjects for extraction rather than requiring alistof lon and lat values; - has stricter checks of user-inputs that use {cli} and {rlang} for clearer and more informative messages for users about what went wrong;
- removes the ability to crop DAAS soil order by the GRDC Agroecozones; and
- has comprehensive test coverage, >98% of the package is covered.
Quick Start
Installation
The preferred method is to install through R-Universe like so:
# Enable this universe
options(repos = c(
adamhsparks = "https://maelle.r-universe.dev",
CRAN = "https://cloud.r-project.org"))
# Install
install.packages("fifo")Load the packages necessary to execute the examples that follow.
##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionUsing {fifo}
Extract the GRDC AgroEcological Zones
See the help for extract_ae_zone for more help on how to use this function.
z <- extract_ae_zone(xy = locs)Extract the Soil Order
See the help for extract_soil_order for more help on how to use this function.
s <- extract_daas_soil_order(xy = 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 example uses a locally-stored API key found in the .Renviron file. See the help for extract_patched_point for more help on how to use this function.
three_sites <-
extract_patched_point(
xy = locs,
start_date = "20200101",
end_date = "20201231",
api_key = Sys.getenv("SILO_API_KEY")
)## You have requested station observation data but some rows in this
## dataset have data codes for interpolated data.
## Check the 'data_source' columns and `get_patched_point()` or
## `get_data_drill()` documentation for further details on codes and
## references.
##
## You have requested station observation data but some rows in this
## dataset have data codes for interpolated data.
## Check the 'data_source' columns and `get_patched_point()` or
## `get_data_drill()` documentation for further details on codes and
## references.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.
## Joining with `by = join_by(location, x, y)`## Key: <location>
## location x y ae_zone station_code distance
## <char> <num> <num> <char> <char> <num>
## 1: Corrigin 117.87 -32.33 WA Central 010536 0.3
## 2: Corrigin 117.87 -32.33 WA Central 010536 0.3
## 3: Corrigin 117.87 -32.33 WA Central 010536 0.3
## 4: Corrigin 117.87 -32.33 WA Central 010536 0.3
## 5: Corrigin 117.87 -32.33 WA Central 010536 0.3
## ---
## 1094: Tamworth 150.84 -31.07 NSW NE/Qld SE 055325 0.6
## 1095: Tamworth 150.84 -31.07 NSW NE/Qld SE 055325 0.6
## 1096: Tamworth 150.84 -31.07 NSW NE/Qld SE 055325 0.6
## 1097: Tamworth 150.84 -31.07 NSW NE/Qld SE 055325 0.6
## 1098: Tamworth 150.84 -31.07 NSW NE/Qld SE 055325 0.6
## station_name year day date air_tmax air_tmax_source
## <char> <num> <int> <Date> <num> <int>
## 1: Corrigin 2020 1 2020-01-01 37.4 25
## 2: Corrigin 2020 2 2020-01-02 23.0 0
## 3: Corrigin 2020 3 2020-01-03 26.0 0
## 4: Corrigin 2020 4 2020-01-04 34.0 0
## 5: Corrigin 2020 5 2020-01-05 38.0 0
## ---
## 1094: Tamworth Airport AWS 2020 27 2020-12-27 29.8 0
## 1095: Tamworth Airport AWS 2020 28 2020-12-28 26.8 0
## 1096: Tamworth Airport AWS 2020 29 2020-12-29 28.9 0
## 1097: Tamworth Airport AWS 2020 30 2020-12-30 29.4 0
## 1098: Tamworth Airport AWS 2020 31 2020-12-31 30.0 0
## air_tmin air_tmin_source elev_m et_morton_actual et_morton_actual_source
## <num> <int> <char> <num> <int>
## 1: 15.3 25 295.0 m 3.3 26
## 2: 16.0 25 295.0 m 6.4 26
## 3: 12.5 0 295.0 m 3.4 26
## 4: 8.0 0 295.0 m 4.6 26
## 5: 12.0 0 295.0 m 7.4 26
## ---
## 1094: 15.0 0 394.9 m 5.5 26
## 1095: 18.3 0 394.9 m 4.1 26
## 1096: 17.5 0 394.9 m 2.6 26
## 1097: 14.9 0 394.9 m 6.6 26
## 1098: 16.1 0 394.9 m 6.2 26
## et_morton_potential et_morton_potential_source et_morton_wet
## <num> <int> <num>
## 1: 11.0 26 7.2
## 2: 6.4 26 6.4
## 3: 7.3 26 5.4
## 4: 8.4 26 6.5
## 5: 8.8 26 8.1
## ---
## 1094: 6.9 26 6.2
## 1095: 4.9 26 4.5
## 1096: 5.3 26 3.9
## 1097: 6.6 26 6.6
## 1098: 8.1 26 7.1
## et_morton_wet_source et_short_crop et_short_crop_source et_tall_crop
## <int> <num> <int> <num>
## 1: 26 8.0 26 10.4
## 2: 26 4.4 26 4.7
## 3: 26 5.4 26 6.7
## 4: 26 7.0 26 8.9
## 5: 26 7.3 26 9.0
## ---
## 1094: 26 5.3 26 6.3
## 1095: 26 3.5 26 4.2
## 1096: 26 3.8 26 4.8
## 1097: 26 5.2 26 5.9
## 1098: 26 6.0 26 7.1
## et_tall_crop_source evap_comb evap_comb_source evap_morton_lake
## <int> <num> <int> <num>
## 1: 26 9.5 25 8.1
## 2: 26 10.4 0 6.6
## 3: 26 8.0 0 6.2
## 4: 26 8.0 0 7.5
## 5: 26 10.6 0 8.4
## ---
## 1094: 26 5.5 25 6.3
## 1095: 26 3.6 25 4.5
## 1096: 26 2.6 25 4.0
## 1097: 26 4.3 25 6.8
## 1098: 26 5.0 25 7.3
## evap_morton_lake_source evap_pan evap_pan_source evap_syn evap_syn_source
## <int> <num> <int> <num> <int>
## 1: 26 9.5 25 11.1 26
## 2: 26 10.4 0 7.2 26
## 3: 26 8.0 0 8.3 26
## 4: 26 8.0 0 10.1 26
## 5: 26 10.6 0 10.4 26
## ---
## 1094: 26 5.5 25 6.7 26
## 1095: 26 3.6 25 4.5 26
## 1096: 26 2.6 25 5.1 26
## 1097: 26 4.3 25 6.5 26
## 1098: 26 5.0 25 7.5 26
## extracted station_latitude station_longitude mslp mslp_source
## <Date> <num> <num> <num> <int>
## 1: 2025-07-17 -32.3292 117.8733 1012.7 25
## 2: 2025-07-17 -32.3292 117.8733 1010.8 0
## 3: 2025-07-17 -32.3292 117.8733 1017.2 0
## 4: 2025-07-17 -32.3292 117.8733 1020.9 0
## 5: 2025-07-17 -32.3292 117.8733 1015.9 0
## ---
## 1094: 2025-07-17 -31.0742 150.8362 1015.7 0
## 1095: 2025-07-17 -31.0742 150.8362 1012.7 0
## 1096: 2025-07-17 -31.0742 150.8362 1011.4 0
## 1097: 2025-07-17 -31.0742 150.8362 1014.2 0
## 1098: 2025-07-17 -31.0742 150.8362 1015.8 0
## radiation radiation_source rainfall rainfall_source rh_tmax
## <num> <int> <num> <int> <num>
## 1: 31.0 42 0.0 0 22.6
## 2: 27.1 42 0.0 0 71.2
## 3: 26.8 42 0.0 0 37.5
## 4: 30.9 42 0.0 0 26.3
## 5: 30.8 42 0.0 0 33.4
## ---
## 1094: 24.9 42 2.0 0 46.5
## 1095: 15.7 42 10.2 0 61.9
## 1096: 14.0 42 1.0 0 50.0
## 1097: 26.4 42 18.8 0 52.7
## 1098: 28.7 42 0.0 0 44.5
## rh_tmax_source rh_tmin rh_tmin_source vp vp_deficit vp_deficit_source
## <int> <num> <int> <num> <num> <int>
## 1: 26 83.5 26 14.5 32.7 26
## 2: 26 100.0 26 20.0 5.2 26
## 3: 26 87.0 26 12.6 14.9 26
## 4: 26 100.0 26 14.0 22.7 26
## 5: 26 100.0 26 22.1 24.1 26
## ---
## 1094: 26 100.0 26 19.5 14.3 26
## 1095: 26 100.0 26 21.8 9.3 26
## 1096: 26 99.6 26 19.9 13.8 26
## 1097: 26 100.0 26 21.6 11.6 26
## 1098: 26 100.0 26 18.9 15.8 26
## vp_source daas_soil_order
## <int> <char>
## 1: 25 Sodosol
## 2: 0 Sodosol
## 3: 0 Sodosol
## 4: 0 Sodosol
## 5: 0 Sodosol
## ---
## 1094: 0 Dermosol
## 1095: 0 Dermosol
## 1096: 0 Dermosol
## 1097: 0 Dermosol
## 1098: 0 DermosolA Note on API Keys
The examples in this README assume that you have stored your API key(s) in your .Renviron file. See Chapter 8 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.
Note for Linux Installers
If you are using Linux, you will likely need to install several system-level libraries. For Nectar with a fresh Ubuntu image, you can use the following command to install system libraries to install {pak} and then install {fifo}. In your Linux terminal (not your R console, the “terminal” tab in RStudio should do here in most cases) type:
Meta
Code of Conduct
Please note that the {fifo} project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
Contributing
Please note that the {fifo} project has a Contributing guide, please refer to it before contributing to this project.