snotelr

a snow data network (SNOTEL) R package

https://github.com/bluegreen-labs/snotelr

Science Score: 59.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
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  • .zenodo.json file
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  • DOI references
    Found 7 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
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    1 of 5 committers (20.0%) from academic institutions
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    Low similarity (16.3%) to scientific vocabulary

Keywords

climate-data data-retrieval precipitation-data r-package rstats snotel snow
Last synced: 6 months ago · JSON representation

Repository

a snow data network (SNOTEL) R package

Basic Info
Statistics
  • Stars: 17
  • Watchers: 4
  • Forks: 10
  • Open Issues: 3
  • Releases: 5
Topics
climate-data data-retrieval precipitation-data r-package rstats snotel snow
Created about 9 years ago · Last pushed about 1 year ago
Metadata Files
Readme Changelog License

README.md

snotelr

R-CMD-check codecov CRAN\_Status\_Badge DOI

snotelr is an R toolbox to facilitate easy SNOTEL data exploration and downloads through a convenient R shiny based GUI. In addition it provides a routine to extract basic snow phenology metrics.

How to cite this package in your article

You can cite this package like this "we obtained data from SNOTEL using the snotelr R package (Hufkens 2022)". Here is the full bibliographic reference to include in your reference list:

Hufkens, K. (2022). snotelr: a toolbox to facilitate easy SNOTEL data exploration and downloads in R. Zenodo. https://doi.org/10.5281/zenodo.7012728.

Installation

stable release

To install the current stable release use a CRAN repository:

r install.packages("snotelr") library("snotelr")

The use of the GUI requires the installation of additional packages, which are side loaded.

r install.packages(c("DT","shinydashboard", "plotly", "leaflet"))

development release

To install the development releases of the package run the following commands:

r if(!require(remotes)){install.packages("remotes")} remotes::install_github("bluegreen-labs/snotelr") library("snotelr")

Vignettes are not rendered by default, if you want to include additional documentation please use:

r if(!require(remotes)){install.packages("remotes")} remotes::install_github("bluegreen-labs/snotelr", build_vignettes = TRUE) library("snotelr")

Use

Most people will prefer the GUI to explore data on the fly. To envoke the GUI use the following command:

r library(snotelr) snotel_explorer()

This will start a shiny application with an R backend in your default browser. The first window will display all site locations, and allows for subsetting of the data based upon state or a bounding box. The bounding box can be selected by clicking top-left and bottom-right.

map

The plot data tab allows for interactive viewing of the soil water equivalent (SWE) data together with a covariate (temperature, precipitation). The SWE time series will also mark snow phenology statistics, mainly the day of:

  • first snow melt
  • a continuous snow free season (last snow melt)
  • first snow accumulation (first snow deposited)
  • continuous snow accumulation (permanent snow cover)
  • seasonal maximum SWE (and its amount)

All values are provided as relative to January first of the year mentioned (spring), and absolute dates.

time_series

To access the full list of SNOTEL sites and associated meta-data use the snotel_info() function.

```r

returns the site info as snotel_metadata.txt in the current working directory

snotel_info(path = ".")

export to data frame

meta-data <- snotel_info(path = NULL)

show some lines of the data frame

head(meta-data) ```

To query data for e.g. site 924 as shown in the image above use:

r snotel_download(site_id = 924)

For in depth analysis the statistics in the GUI can be retrieved using the snotel_phenology() function

```r

with df a SNOTEL file or data frame in your R workspace

snotel_phenology(df) ```

Data (units)

By default all data is converted to metric. Depths of snow and snow water equivalent are reported in mm, although it must be noted that when stations measure snow depth (in metric) they round values to the nearest inch or cm. You can use the metric parameter to download the raw data. Note that batch downloads might fail in this instance as column names might not match due to the dual use of metric and imperial units across stations. This is for niche and debugging use mostly.

References

Hufkens, K. (2022). snotelr: a toolbox to facilitate easy SNOTEL data exploration and downloads in R. Zenodo. https://doi.org/10.5281/zenodo.7012728.

Acknowledgements

This project was in part supported by the National Science Foundation’s Macro-system Biology Program (award EF-1065029) and the Marie Skłodowska-Curie Action (H2020 grant 797668). Logo design elements are taken from the FontAwesome library according to these terms, where the globe element was inverted and intersected.

Owner

  • Name: BlueGreen Labs
  • Login: bluegreen-labs
  • Kind: organization
  • Email: info@bluegreenlabs.org
  • Location: Melsele, Belgium

BlueGreen open science labs & consulting, providing environmental research infrastructure and editorial solutions.

GitHub Events

Total
  • Create event: 1
  • Issues event: 3
  • Release event: 1
  • Watch event: 2
  • Delete event: 1
  • Push event: 1
Last Year
  • Create event: 1
  • Issues event: 3
  • Release event: 1
  • Watch event: 2
  • Delete event: 1
  • Push event: 1

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 198
  • Total Committers: 5
  • Avg Commits per committer: 39.6
  • Development Distribution Score (DDS): 0.066
Past Year
  • Commits: 20
  • Committers: 2
  • Avg Commits per committer: 10.0
  • Development Distribution Score (DDS): 0.05
Top Committers
Name Email Commits
khufkens k****s@g****m 185
Koen Hufkens k****s@P****l 10
David Hill d****h@o****u 1
Dominik Schneider d****h 1
Nicholas Potter p****t 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 30
  • Total pull requests: 9
  • Average time to close issues: 6 months
  • Average time to close pull requests: about 3 hours
  • Total issue authors: 10
  • Total pull request authors: 4
  • Average comments per issue: 1.73
  • Average comments per pull request: 0.33
  • Merged pull requests: 9
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 8
  • Pull requests: 2
  • Average time to close issues: 15 days
  • Average time to close pull requests: 24 minutes
  • Issue authors: 2
  • Pull request authors: 1
  • Average comments per issue: 0.75
  • Average comments per pull request: 0.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • khufkens (18)
  • realmiketalbot (2)
  • jeffmarti (2)
  • potterzot (2)
  • JepsonNomad (1)
  • dschneiderch (1)
  • tungttnguyen (1)
  • dfosterhill (1)
  • Roctober92 (1)
  • MNewcomer (1)
Pull Request Authors
  • khufkens (8)
  • dfosterhill (2)
  • dschneiderch (1)
  • potterzot (1)
Top Labels
Issue Labels
enhancement (3)
Pull Request Labels

Packages

  • Total packages: 2
  • Total downloads:
    • cran 427 last-month
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 1
    (may contain duplicates)
  • Total versions: 10
  • Total maintainers: 1
proxy.golang.org: github.com/bluegreen-labs/snotelr
  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 6 months ago
cran.r-project.org: snotelr

Calculate and Visualize 'SNOTEL' Snow Data and Seasonality

  • Versions: 8
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 427 Last month
Rankings
Forks count: 8.8%
Stargazers count: 15.1%
Average: 20.0%
Downloads: 24.0%
Dependent repos count: 24.3%
Dependent packages count: 27.9%
Maintainers (1)
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.6 depends
  • httr * imports
  • magrittr * imports
  • memoise * imports
  • rvest * imports
  • shiny * imports
  • stats * imports
  • utils * imports
  • DT * suggests
  • covr * suggests
  • knitr * suggests
  • leaflet * suggests
  • plotly * suggests
  • rmarkdown * suggests
  • shinydashboard * suggests
  • testthat * suggests
.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v3 composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/deploy_docs.yaml actions
  • JamesIves/github-pages-deploy-action v4.4.1 composite
  • actions/checkout v3 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/test-coverage.yaml actions
  • actions/cache v2 composite
  • actions/checkout v2 composite
  • r-lib/actions/setup-pandoc v1 composite
  • r-lib/actions/setup-r v1 composite