This lidar dataset was collected as part of an NCALM Seed grant for Brooke Hunter at the University of Oregon. This study used airborne lidar to detect Post-Fire Debris Flow Detection and Erosion from the Douglas Fire near Grants Pass, Oregon. The study area covers approximately 60 km2.

This lidar dataset was collected by NCALM for Sally Thompson at the University of California, Berkeley. This study aims to assess the occurrence and characteristics of post-fire erosion gullies caused by the Empire Fire in Illilouette Creek Basin, California. The study area covers approximately 74 km2 in Yosemite National Park, California.

This U.S. Geological Survey (USGS) data release contains the results from the 2017 geomorphic survey of North Fork Eagle Creek, New Mexico. The 2017 geomorphic survey was conducted by the USGS, in cooperation with the Village of Ruidoso, New Mexico, and is the first in a planned series of five annual geomorphic surveys of the stream reach located between the North Fork Eagle Creek near Alto, New Mexico, streamflow-gaging station (USGS site 08387550) and the Eagle Creek below South Fork near Alto, New Mexico, streamflow-gaging station (USGS site 08387600). Specifically, this data release contains the results from 14 cross-section surveys (to include x-y-z coordinates of all cross-section points), the locations of all woody debris identified in the reach and their corresponding debris jam classifications, and the locations of all pools identified in the reach. All x-y-z coordinates included in this data release were collected by using survey-grade real-time kinematic global navigation satellite systems (RTK GNSS). This data release supports the following publication: Graziano, A.P., 2019, Geomorphic survey of North Fork Eagle Creek, New Mexico, 2017: U.S. Geological Survey Open-File Report 2018-1187, 28 p., https://doi.org/10.3133/ofr20181187.

This dataset represents percent area burned in each burn severity class for wildfires within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies for each year for 1984-2018.The Monitoring Trends in Burn Severity MTBS project assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico from the beginning of the Landsat Thematic Mapper archive to the present. See: https://catalog.data.gov/dataset/monitoring-trends-in-burn-severity-burned-area-boundaries-feature-layer-27201 and https://www.mtbs.gov/product-descriptions

This dataset represents percent area burned in each burn severity class for wildfires within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies for each year for 1984-2018.The Monitoring Trends in Burn Severity MTBS project assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico from the beginning of the Landsat Thematic Mapper archive to the present. See: https://catalog.data.gov/dataset/monitoring-trends-in-burn-severity-burned-area-boundaries-feature-layer-27201 and https://www.mtbs.gov/product-descriptions

This dataset represents the historical fire perimeters within individual local NHDPlusV2 catchments and upstream, contributing watersheds based on the GeoMAC (Geospatial Multi-Agency Coordination) mapping tool. Fire perimeters contain data as they are submitted by field offices to GeoMAC (Geospatial Multi-Agency Coordination) in a polygon format. Fire perimeter data is based on input from incident intelligence sources, GPS data, infrared (IR) imagery from fixed wing and satellite platforms. Polygons are selected by year and then converted into a binary raster format where values of 1 represent fire perimeters of the given year and 0 describes the remaining areas across the CONUS, leaving No Data to be anything outside the CONUS border. The wildland fire characteristics (% forest loss to fire) were summarized by year to produce local catchment-level and watershed-level metrics as a continuous data type.

LANDFIRE's 2023 Update (LF 2023) Forest Canopy Cover (CC) describes the percent cover of the tree canopy in a stand. CC is a vertical projection of the tree canopy cover onto an imaginary horizontal plane. In fire behavior models, CC supplies information to determine the probability of crown fire initiation, provides input in the spotting model, and aids in calculating wind reductions and fuel moisture conditioning. To create CC, LANDFIRE's Existing Vegetation Cover (EVC) product must be produced first. EVC is a continuous scaled product which assigns cover to all life forms in the LF data. CC is then derived from EVC by assigning bins of 10% for fuel production and use in fire behavior software. CC is used in the calculation of Forest Canopy Bulk Density (CBD) and Base Height (CBH). To designate disturbed areas where CC is modified, the aggregated Annual Disturbance products from 2014 to 2023 in the LF Fuel Disturbance (FDist) product are used. All existing disturbances between 2014-2023 are represented in LF 2023, and the products are intended to be used in 2024 (the year of release). When using any product from the LF 2023 fuel product suite, users should consider adjusting fuel layers for disturbances that occurred after the end of the 2023 fiscal year (after October 1st, 2023). Disturbances that occurred after the end of the 2023 fiscal year are not accounted for within LF 2023 fuel products. Learn more about LF 2023 at https://landfire.gov/data/lf2023.

This dataset represents mean percent are burned from wildfires within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies for each year for 1984-2018. The Monitoring Trends in Burn Severity MTBS project assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico from the beginning of the Landsat Thematic Mapper archive to the present. See: https://catalog.data.gov/dataset/monitoring-trends-in-burn-severity-burned-area-boundaries-feature-layer-27201 and https://www.mtbs.gov/product-descriptions

Geotiff Images of fire affected areas in Litchfield National Park for the year 2014 based on the NASA Moderate Resolution Imaging Spectroradiometer (MODIS). These Images are clipped from geotiff images of fire affected areas in far northern Australia available from North Australian Fire Information (NAFI) website. The images have a resolution of 250 m (pixel size) and each burnt pixel is tagged with the month that covers the largest part of the date interval in which the burnt pixel was detected. These data cover Kakadu National Park, but are part of a larger data set that extends across far northern WA down to 21 degrees S, across the entire NT (down to 26 degrees S) and all of Qld (down to 29 degrees S). The NAFI mapping covers the years 2000 to present and since 2012, the mapping also includes northern SA down to 29 degrees S. Mapping landscapes north of 20 degrees S in WA, NT and Qld has been validated by aerial and on-ground transects across northern Australia.

A Fire Disturbance Area represents the mapped exterior perimeter of a forest fire. Mapping is derived from a variety of sources, such as GPS points and digitized paper maps. Prior to 1998, only fires greater than 200 hectares were mapped. Since 1998, fires greater than 40 hectares have been mapped. If adequate mapping exists for fires less than 40 hectares in size, they will be included in this data class. The [Forest Fire Info Map](https://www.lioapplications.lrc.gov.on.ca/ForestFireInformationMap/index.html?viewer=FFIM.FFIM) shows active fires, current fire danger and restricted fire zones in place due to high fire danger.