Tools for geo-web processing of gridded data via the Geo Data Portal. geoknife slices up gridded data according to overlap with irregular features, such as watersheds, lakes, points, etc. The result is subsetted data in plain text, NetCDF, geotiff or other formats.

To install the geoknife from CRAN:

install.packages("geoknife")

Or to install the current development version of the package:

install.packages("remotes")
remotes::install_github('DOI-USGS/geoknife')

Please consider reporting bugs and asking questions on the Issues page: https://github.com/DOI-USGS/geoknife/issues

We want to encourage a warm, welcoming, and safe environment for contributing to this project. See the code of conduct for more information.

The Water Mission Area of the USGS supports the development and maintenance of geoknife through September 2018, and most likely further into the future. Resources are available primarily for maintenance and responding to user questions. Priorities on the development of new features are determined by the geoknife development team.

The geoknife package was created to support web-based geoprocessing of large gridded datasets according to their overlap with landscape (or aquatic/ocean) features that are often irregularly shaped. geoknife creates data access and subsequent geoprocessing requests for the USGS’s Geo Data Portal to carry out on a web server. The results of these requests are available for download after the processes have been completed. This type of workflow has three main advantages: 1) it allows the user to avoid downloading large datasets, 2) it avoids reinventing the wheel for the creation and optimization of complex geoprocessing algorithms, and 3) computing resources are dedicated elsewhere, so geoknife operations do not have much of an impact on a local computer.

geoknife interacts with a remote server to figure out what types of processing capabilities are available, in addition to seeing what types of geospatial features are already available to be used as an area of interest (commonly, these are user-uploaded shapefiles). Because communication with web resources are central to geoknife operations, users must have an active internet connection.

The main elements of setting up and carrying out a geoknife ‘job’ (geojob) include defining the feature of interest (the stencil argument in the geoknife function), the gridded web dataset to be processed (the fabric argument in the geoknife function), and the the processing algorithm parameters (the knife argument in the geoknife function). The status of the geojob can be checked with check, and output can be loaded into a data.frame with result.

library(geoknife)
# from a single point
stencil <- simplegeom(c(-89, 46.23))
   # -- or --
# from a collection of named points
stencil <- simplegeom(data.frame(
              'point1' = c(-89, 46), 
              'point2' = c(-88.6, 45.2)))
   # -- or --
#for a state from a web available dataset
stencil <- webgeom('state::New Hampshire')
stencil <- webgeom('state::New Hampshire,Wisconsin,Alabama')
   # -- or --
#for HUC8s from a web available dataset
stencil <- webgeom('HUC8::09020306,14060009')

# from the prism dataset:
fabric <- webdata('prism')
   # -- or --
# explicitly define webdata from a list:
fabric <- webdata(list(
            times = as.POSIXct(c('1895-01-01','1899-01-01')),
            url = 'https://cida.usgs.gov/thredds/dodsC/prism_v2',
            variables = 'ppt'))
# modify the times field:
times(fabric) <- as.POSIXct(c('2003-01-01','2005-01-01'))

job <- geoknife(stencil, fabric, wait = TRUE)

# use existing convienence functions to check on the job:
check(job)

## $status
## [1] "Process successful"
## 
## $URL
## [1] "https://labs.waterdata.usgs.gov:443/gdp-process-wps/RetrieveResultServlet?id=3362d55f-6d35-4e21-baf6-51a2583bc8bdOUTPUT"
## 
## $statusType
## [1] "ProcessSucceeded"
## 
## $percentComplete
## [1] "100"

see also:

running(job)
error(job)
successful(job)

data <- result(job)
plot(data[,1:2], ylab = variables(fabric))

job <- geoknife(webgeom('state::New Hampshire'), fabric = 'prism', email = 'fake.email@gmail.com')

This version requires httr, sp, and XML. All of these packages are available on CRAN, and will be installed automatically when using the install.packages() instructions above.

In addition to typical R package checking, a Dockerfile is included in this repository. Once built, it can be run with the following command.

docker build -t geoknife_test .

docker run --rm -it -v %cd%:/src geoknife_test /bin/bash -c "cp -r /src/* /check/ && cp /src/.Rbuildignore /check/ && cd /check && Rscript -e 'devtools::build()' && R CMD check --as-cran ../geoknife_*"

For release of the sbtools package, a number of steps are required.

1. Ensure all checks pass and code coverage is adequate.
2. Ensure NEWS.md reflects updates in version.
3. Update DESCRIPTION to reflect release version.
4. Convert DISCLAIMER.md to approved language and rebuild README.Rmd.
5. Create release candidate branch and commit release candidate.
6. Build source package and upload to CRAN.
7. Once accepted to CRAN, tag release candidate branch an push to repositories.
8. Change DISCLAIMER.md back to development mode and increment description version.
9. Merge release candidate and commit.
10. Open PR/MR in development state.

This software is preliminary or provisional and is subject to revision. It is being provided to meet the need for timely best science. The software has not received final approval by the U.S. Geological Survey (USGS). No warranty, expressed or implied, is made by the USGS or the U.S. Government as to the functionality of the software and related material nor shall the fact of release constitute any such warranty. The software is provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the software.