knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", message = FALSE, warning = FALSE, error = FALSE, tidy = TRUE )
Development of the SNAPverse R package ecosystem has been frozen indefinitely. This project was never directly funded. I began it out of personal interest, but no longer work for SNAP. It will remain archived here for historical reference.
The snapfire
package provides access to curated collections of public wildfire data sets
offered by Scenarios Network for Alaska and Arctic Planning (SNAP) at the University of Alaska Fairbanks.
snapfire
interfaces with SNAP's Amazon Web Services cloud storage to retrieve specific fire data.
Available data includes historical observational fire data and historical and projected climate model-driven fire simulation outputs.
Available fire variables include fire frequency, fire size and total burn area.
Auxiliary variables include modeled vegetation cover area and stand age, which are also part of SNAP fire simulation outputs.
Simulations driven by climate model inputs are done using SNAP's ALFRESCO wildfire and landscape transition model.
Regional fire summaries and fire data at point locations are available, stretching over Alaska and western Canada. Regions include the state of Alaska and several Canadian provinces, ecological regions, fire management zones, terrestrial protected areas under jurisdiction and management of various governmental agencies and more. Point locations include cities, towns, villages and other municipal units and locations of interest.
Annual and decadal are available data for 86 regions and 3,967 point locations across Alaska and western Canada.
Most of the collections accessed with snapfire
are based on simulated 1-km outputs from SNAP's ALFRESCO wildfire and landscape transition model.
snapfire
is a member package in the data sector of the SNAPverse collection of R packages.
Data packages typically include raw data sets in support of other R packages.
snapfire
is technically more like a typical R package. Instead of storing local copies of data sets,
it contains functions for accessing external data sets that would be too large to store conveniently even in an
explicit data package, especially considering that any given user session would likely utilize
only a small fraction of the total available data. However, snapfire
does not offer functionality
beyond accessing data and is therefore still best conceptualized as a data package.
Functions for statistical analysis and modeling of SNAP data are already encompassed in packages like snapstat
.
You can install snapfire from github with:
# install.packages("devtools") devtools::install_github("leonawicz/snapfire")
is_md <- knitr::opts_knit$get("rmarkdown.pandoc.to") == "markdown_github-ascii_identifiers"
cat('## Reference\n\n[Complete package reference and function documentation](https://leonawicz.github.io/snapfire/)')
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