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LANDFIRE Remap Prototype Mapping Effort: Developing a New Framework for Mapping Vegetation Classification, Change, and Structure

1
ASRC Federal Data Solutions, Contractor to the U.S. Geological Survey (USGS), Earth Resources Observation and Science (EROS) Center, 47914 252nd Street, Sioux Falls, SD 57198, USA
2
KBR, Contractor to the USGS EROS Center, Sioux Falls, SD 57198, USA
3
USGS/Boise State University, National Gap Analysis Project, Boise, ID 83725, USA
4
USGS EROS, Sioux Falls, SD 57198, USA
*
Author to whom correspondence should be addressed.
Received: 22 May 2019 / Revised: 14 June 2019 / Accepted: 16 June 2019 / Published: 20 June 2019
LANDFIRE (LF) National (2001) was the original product suite of the LANDFIRE program, which included Existing Vegetation Cover (EVC), Height (EVH), and Type (EVT). Subsequent refinements after feedback from data users resulted in updated products, referred to as LF 2001, that now served as LANDFIRE’s baseline datasets and are the basis for all subsequent LANDFIRE updates. These updates account for disturbances and vegetation transition changes that may not represent current vegetation conditions. Therefore, in 2016 LANDFIRE initiated the Remap prototype to determine how to undertake a national-scale remap of the LANDFIRE primary vegetation datasets. EVC, EVH, and EVT were produced (circa 2015) via modeling for ecologically variable prototyping areas in the Pacific Northwest (NW) and Grand Canyon (GC). An error analysis within the GC suggested an overall accuracy of 52% (N = 800) for EVT, and a goodness of fit of 51% (N = 38) for percent cover (continuous EVC) and 53% (N = 38) for height (continuous EVH). The prototyping effort included a new 81-class map using the National Vegetation Classification (NVC) within the NW. This paper presents a narrative of the innovative methodologies in image processing and mapping used to create the new LANDFIRE vegetation products. View Full-Text
Keywords: decision tree classification; Landsat; lidar; regression tree classification; vegetation mapping; vegetation structure decision tree classification; Landsat; lidar; regression tree classification; vegetation mapping; vegetation structure
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MDPI and ACS Style

Picotte, J.J.; Dockter, D.; Long, J.; Tolk, B.; Davidson, A.; Peterson, B. LANDFIRE Remap Prototype Mapping Effort: Developing a New Framework for Mapping Vegetation Classification, Change, and Structure. Fire 2019, 2, 35. https://doi.org/10.3390/fire2020035

AMA Style

Picotte JJ, Dockter D, Long J, Tolk B, Davidson A, Peterson B. LANDFIRE Remap Prototype Mapping Effort: Developing a New Framework for Mapping Vegetation Classification, Change, and Structure. Fire. 2019; 2(2):35. https://doi.org/10.3390/fire2020035

Chicago/Turabian Style

Picotte, Joshua J.; Dockter, Daryn; Long, Jordan; Tolk, Brian; Davidson, Anne; Peterson, Birgit. 2019. "LANDFIRE Remap Prototype Mapping Effort: Developing a New Framework for Mapping Vegetation Classification, Change, and Structure" Fire 2, no. 2: 35. https://doi.org/10.3390/fire2020035

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