fireR

Fast access to MTBS (Monitoring Trends in Burn Severity) fire perimeter data, SE FireMap burn severity mosaics, USFS Wildland-Urban Interface (WUI) data, and EPA/CEC ecoregion boundaries straight from the source.

Overview

fireR provides convenient access to USGS fire datasets and EPA/CEC ecoregion boundaries:

get_mtbs() downloads the MTBS ZIP to a directory
read_mtbs() reads, filters, and returns data from that ZIP as sf, terra::SpatVector, or data.frame
get_sefire() downloads SE FireMap Annual Burn Severity Mosaic ZIP(s) for one or more years (2000–2022)
get_nal1eco() / get_nal2eco() / get_nal3eco() — download and load CEC North America ecoregions at Levels 1–3
get_usl3eco() / get_usl4eco() — download and load US EPA ecoregions at Levels 3–4 (with optional state boundaries)
get_nifc() — download NIFC (National Interagency Fire Center) wildfire perimeters dataset from figshare
get_fod() — download the USFS Fire Occurrence Database (FPA-FOD) GeoPackage ZIP from the Forest Service Research Data Archive
get_wui() — download the USFS Wildland-Urban Interface (WUI) dataset from the USFS public Box archive (4.65 GB — slow, run in the background)

Key features:

⚡ Fast downloads — uses curl’s HTTP/2 persistent connection
🗓️ Flexible year filtering — single year (2020), range (2010:2020), or specific years (c(2000, 2010, 2020))
🗺️ Flexible output — sf, terra, or plain data.frame
💾 Optional caching — skip the download on repeat calls

Installation

# Install from GitHub (once published)
# install.packages("pak")
pak::pak("noahweidig/fireR")

Usage

All fires, return as `sf`

library(fireR)

fires <- read_mtbs(output = "sf")
plot(fires["BurnBndAc"])

Filter to a year range

fires_recent <- read_mtbs(years = 2010:2023, output = "sf")

Single year

fires_2020 <- read_mtbs(years = 2020, output = "sf")

Specific years only

fires_sel <- read_mtbs(years = c(2000, 2010, 2020), output = "sf")

Return as `terra::SpatVector`

fires_vect <- read_mtbs(years = 2015:2023, output = "vect")

Attribute table only (no geometry)

tbl <- read_mtbs(geometry = FALSE)

Cache the download for future sessions

# Cache in the default user directory
fires <- read_mtbs(cache = TRUE)

# Or supply your own cache path
fires <- read_mtbs(cache = "~/data/mtbs_cache")

SE FireMap

Download burn severity mosaics for one or more years:

# Single year
zip_path <- get_sefire(2020)

# Contiguous range
zip_paths <- get_sefire(2015:2020, directory = "data/sefire")

# Specific years
zip_paths <- get_sefire(c(2000, 2010, 2020))

NIFC Wildfire Perimeters

Download the NIFC wildfire perimeters dataset from figshare:

# Download to current directory
zip_path <- get_nifc()

# Download to a specific directory
zip_path <- get_nifc(directory = "data/nifc")

USFS Fire Occurrence Database (FOD)

Download the FPA-FOD GeoPackage ZIP from the Forest Service Research Data Archive:

# Download to current directory
zip_path <- get_fod()

# Download to a specific directory
zip_path <- get_fod(directory = "data/fod")

USFS Wildland-Urban Interface (WUI)

Warning: The WUI ZIP is approximately 4.65 GB and will be slow to download. It is strongly recommended to run get_wui() in a background R session so your interactive session remains responsive.

# Recommended: run in a background session
bg <- callr::r_bg(function() fireR::get_wui(directory = "data/wui"))
bg$wait()

# Or download to the current directory (blocks the session)
zip_path <- get_wui()

# Download to a specific directory
zip_path <- get_wui(directory = "data/wui")

Ecoregions

North America (CEC Levels 1–3)

# Level 1 — broadest continental divisions
na_l1 <- get_nal1eco()

# Level 2 — finer continental subdivisions
na_l2 <- get_nal2eco()

# Level 3 — finest continental scale (= US EPA Level III)
na_l3 <- get_nal3eco(output = "vect")

US EPA (Levels 3–4, with optional state boundaries)

# Level 3 — without state boundaries (default)
us_l3 <- get_usl3eco()

# Level 3 — with state boundaries
us_l3_states <- get_usl3eco(state = TRUE)

# Level 4 — finest US subdivisions
us_l4 <- get_usl4eco()
us_l4_states <- get_usl4eco(state = TRUE)

All ecoregion functions accept output = "sf" (default) or output = "vect" and a cache argument to persist downloads between sessions.

`read_mtbs()` Arguments

Argument	Type	Default	Description
`years`	`integer`	`NULL`	Single year, range (`2010:2020`), or specific years (`c(2000, 2010)`). `NULL` = no filter
`type`	`character`	`NULL`	Incident type(s). `NULL` = all types
`geometry`	`logical`	`TRUE`	Return a spatial object. `FALSE` → `data.frame`
`output`	`character`	`"vect"`	`"sf"` or `"vect"` / `"terra"`
`cache`	`logical`/`character`	`FALSE`	Directory containing the downloaded ZIP
`verbose`	`logical`	`TRUE`	Print progress messages

Download data to disk first with get_mtbs():

mtbs_dir <- get_mtbs()

About MTBS

Monitoring Trends in Burn Severity (MTBS) is a multi-agency programme (USGS, USFS) that maps the location, extent, and burn severity of all large wildfires across the conterminous USA, Alaska, Hawaii, and Puerto Rico from 1984 to the present.