Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content

LANDFIRE Remap Forest Canopy Cover (CC) CONUS

Metadata Updated: July 6, 2024

LANDFIRE's (LF) Remap 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 disturbed locations CC is calculated from linear regression equations derived from Forest Vegetation Simulator (FVS) plot data output, but at non-disturbed locations it is assigned the midpoint of Fuel Vegetation Cover (FVC) forested classes. In some instances, LF Remap assumes the potential burnable biomass in the tree canopy has been accounted for in the surface fuel model. For example, young or short conifer stands where the trees are represented by a shrub type fuel model will not have canopy characteristics. LF Remap Annual Disturbance products are incorporated into CC to provide informed changes by disturbance type, severity, and time since disturbance (TSD). Annual Disturbance products provide a pre-disturbance scenario represented by LF Remap existing vegetation products. Reporting of the pre-disturbance scenario helps to calculate CC, by providing information about vegetation impacted by a disturbance. Then, vegetation adjustments are modeled in disturbance areas based on disturbance type and severity. CC is then used in the calculation of Canopy Bulk Density (CBD) and Canopy Base Height (CBH). CC supplies information to fire behavior models in order to; determine the probability of crown fire initiation, provide input in the spotting model, calculate wind reductions, and to calculate fuel moisture conditioning. CC also has capable fuels functionality. Capable fuels calculates TSD assignments for disturbed areas using an effective year. For example, year 2019 fuels may be calculated for the year 2019. This new process considers all the existing disturbances included in LF Remap and adjusts the TSD for these to the effective year (2019 in this example), making the products "2019 capable fuels." More information about capable fuels can be found at https://www.landfire.gov/lf_remap.php.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

Downloads & Resources

Dates

Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024

Metadata Source

Harvested from DOI EDI

Additional Metadata

Resource Type Dataset
Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024
Publisher U.S. Geological Survey
Maintainer
@Id http://datainventory.doi.gov/id/dataset/43913815a260ea8e7b7f6845dea49513
Identifier USGS:f5dba5b9-6992-436b-9665-bab5fec41214
Data Last Modified 20230111
Category geospatial
Public Access Level public
Bureau Code 010:12
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://datainventory.doi.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id 27fe92a8-5431-4734-8e35-393d22069180
Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
Old Spatial -127.98775263969655,22.765446426860603,-65.25444546636928,51.64968101623376
Publisher Hierarchy White House > U.S. Department of the Interior > U.S. Geological Survey
Source Datajson Identifier True
Source Hash bdba1b7c8f90f0f57bcba49621047a2ed0f4bcdaef3dfe3bec96f5758976351b
Source Schema Version 1.1
Spatial {"type": "Polygon", "coordinates": -127.98775263969655, 22.765446426860603, -127.98775263969655, 51.64968101623376, -65.25444546636928, 51.64968101623376, -65.25444546636928, 22.765446426860603, -127.98775263969655, 22.765446426860603}

Didn't find what you're looking for? Suggest a dataset here.