Spatial fuel data products of the LANDFIRE Project

Abstract

The Landscape Fire and Resource Management Planning Tools (LANDFIRE) Project is mapping wildland fuels, vegetation, and fire regime characteristics across the United States. The LANDFIRE project is unique because of its national scope, creating an integrated product suite at 30-m spatial resolution and complete spatial coverage of all lands within the 50 states. Here we describe development of the LANDFIRE wildland fuels data layers for the conterminous 48 states: surface fire behavior fuel models, canopy bulk density, canopy base height, canopy cover, and canopy height. Surface fire behavior fuel models are mapped by developing crosswalks to vegetation structure and composition created by LANDFIRE. Canopy fuels are mapped using regression trees relating field-referenced estimates of canopy base height and canopy bulk density to satellite imagery, biophysical gradients and vegetation structure and composition data. Here we focus on the methods and data used to create the fuel data products, discuss problems encountered with the data, provide an accuracy assessment, demonstrate recent use of the data during the 2007 fire season, and discuss ideas for updating, maintaining and improving LANDFIRE fuel data products.

Evaluating Unmanned Aerial Vehicle Images for Estimating Forest Canopy Fuels in a Ponderosa Pine Stand

“…Canopy height describes the average height of the forest canopy within a 30 m grid cell [26]. Crown bulk density is the mass of canopy fuel per canopy volume that would burn in a crown fire [51][52][53].…”

“…Crown bulk density is the mass of canopy fuel per canopy volume that would burn in a crown fire [51][52][53]. Crown base height is the lowest point at which sufficient canopy fuel exists for ignition (≥0.012 kg/m 3 ) [23]. The fire behavior fuel models refer to the 13 Anderson Fire Behavior Fuel Models [54] and the 40 Scott and Burgan Fire Behavior Fuel Models [55], which describe surface fuel composition and associated fire behavior [56].…”

Integrating Satellite Imagery with Simulation Modeling to Improve Burn Severity Mapping

“…However, FIRE-HARM is a research tool currently under assessment for management applicability, and it does have some limitations: (1) FIREHARM always simulates a ''head'' fire (a fire that spreads with the wind) which may lead to overestimation of fire intensity in situations where flanking or backing fires are more likely, (2) it does not address spatial relations (what happens in one pixel is independent of what happened in surrounding pixels), (3) input parameters may not match the scale of analysis (e.g., fuel moisture content is specified for broad areas, but moistures are highly variable locally). Lastly, and perhaps most importantly, FIREHARM performance ultimately depends on accurate spatial inputs, and it appears LANDFIRE mapping products likely contain a high level of uncertainty (Keane et al 2013(Keane et al , 2006Krasnow et al 2009;Reeves et al 2009); fuel loadings from the LAND-FIRE FLM map are inaccurate because (1) surface fuel characteristics vary at finer scales than the FLM map (Keane et al 2012) (2) FLMs were created from a limited dataset ), (3) FLM mapping involved assigning an FLM to a vegetation type, but fuels are rarely correlated to vegetation conditions (Keane et al 2013), and the vegetation type categories were too broad for consistent and accurate FLM assignment (Keane et al 2006). The accuracy of the LANDFIRE Tree List product is questionable for similar reasons: (1) scale of variation in Forest Inventory Analysis (FIA) tree data did not match the resolution of vegetation type categories and LANDFIRE maps, (2) assignment of FIA plots to vegetation types was incomplete, because there was not a tree list for every vegetation type category, and (3) the tree data was not rectified with the FLM fuels data (Drury and Herynk 2011).…”

Mapping Forest Height in Alaska Using GLAS, Landsat Composites, and Airborne LiDAR

“…The forest canopy height (CH) is a canopy fuel layer that is derived directly from the EVH for forested pixels, and masked for non-forested pixels. The EVH layer is also used for mapping canopy base height and canopy bulk density layers [28]. Therefore, the increased thematic resolution of the re-mapped FHC directly affects the assignments of surface fuel models and the mapping of canopy fuels, which has tangible effects on strategic and tactical fire behavior modeling, for which these layers are utilized.…”

“…Most notably, the surface and canopy fuel layers are driven in part by the EVH layer. Surface fuel models are assigned using rulesets based on the EVT, EVH, existing vegetation cover, and potential vegetation [28]. The forest canopy height (CH) is a canopy fuel layer that is derived directly from the EVH for forested pixels, and masked for non-forested pixels.…”