FuelMap 2014: Imputed map of carbon stored in litter, duff, fine woody debris, and coarse woody debris for CONUS forests circa 2014

Metadata:
Identification_Information:
Citation:
Citation_Information:
Originator: Riley, Karin L.
Originator: Grenfell, Isaac C.
Originator: Shaw, John D.
Publication_Date: 2023
Title:
FuelMap 2014: Imputed map of carbon stored in litter, duff, fine woody debris, and coarse woody debris for CONUS forests circa 2014
Geospatial_Data_Presentation_Form: raster digital data
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: Forest Service Research Data Archive
Other_Citation_Details:
Updated 30 August 2024
Online_Linkage: https://doi.org/10.2737/RDS-2023-0042
Description:
Abstract:
FuelMap 2014 is an imputed map of litter, duff, fine woody debris, and coarse woody debris loadings for the forests of the conterminous United States (CONUS) circa 2014. In fire science, these strata are often referred to as “fuel” for a wildland fire. FuelMap 2014 is largely derived from the TreeMap 2014, which provides a tree-level model of CONUS forests. To create TreeMap, we assigned forest plot data measured by Forest Inventory and Analysis (FIA) to a 30x30 meter (m) grid. Specifically, we used a random forests machine-learning algorithm to impute the forest plot data to a set of target rasters provided by Landscape Fire and Resource Management Planning Tools (LANDFIRE: https://landfire.gov). Predictor variables for both the forest plots (reference data) and LANDFIRE rasters (target data) consisted of percent forest cover, forest height, and vegetation type, as well as topography (slope, elevation, and aspect), location (latitude and longitude), biophysical variables (photosynthetically active radiation, precipitation, maximum temperature, minimum temperature, relative humidity, and vapor pressure deficit), and disturbance history (time since disturbance and disturbance type) for the landscape circa 2014. FIA records down woody material (DWM) at some but not all of their forest plots. Thus, many of the FIA plots imputed (assigned) in the TreeMap carried DWM information with them. For pixels in TreeMap 2014 where the assigned FIA plot recorded DWM, we used the FIA plot assigned in TreeMap 2014 in the FuelMap 2014. For pixels where FIA plots were assigned that did not have DWM measured, we identified the most similar plot that had DWM measured from the list of FIA plots available for imputation in TreeMap 2014, and then we assigned that plot in the FuelMap 2014.

The main outputs of this project are rasters at 30x30 m spatial resolution for the imputed FIA plot identifier. The plot identifier corresponds to a unique visit to a plot by FIA’s field crew, and is also referred to as the plot control number [CN]. Using the CN, we looked up the loading in each of the carbon pools (in pounds per acre) and include a raster for each: 1) litter, 2) duff, 3) fine woody debris in the 1-hour (hr) size class, 4) fine woody debris in the 10-hr size class, 5) fine woody debris in the 100-hr size class, 6) coarse woody debris in the 1000-hr size class, and 7) “total carbon” in the DWM strata produced by adding these six strata together. We present these data in geodatabase and GeoTIFF formats. The spatial extent is CONUS for landscape conditions circa 2014. The carbon loadings for DWM are drawn from the FIA COND_DWM_CALC tables for the assigned plot CN for litter, duff, fine woody debris and coarse woody debris.
Purpose:
The FuelMap provides spatial estimates of forest floor carbon at fine resolution (30x30 m). These spatially contiguous estimates are needed for landscape-level analyses of forest biomass and carbon, as well as estimates of emissions from wildland fire. The FuelMap can be used in combination with the TreeMap to provide estimates of forest carbon that include both the trees and forest floor. The FuelMap is the first imputed dataset to partition forest floor carbon into different strata of which we are aware. FuelMap does not provide estimates of soil carbon or carbon stored in roots of trees, nor of carbon stored in understory shrubs or grasses.
Supplemental_Information:
See the Entity and Attributes section for details regarding the relationship between the data files included in this publication and the FIA DataMart (https://doi.org/10.2737/RDS-2001-FIADB). For additional information regarding TreeMap 2014, see Riley et al. (2019, https://doi.org/10.2737/RDS-2019-0026).

These data were published on 07/26/2023. On 02/07/2024, a lookup table containing the predicted FIA plot CN was added to the package and a few minor metadata updates were made. On 08/12/2024, a corrected lookup table was added to the package and a few publication URLs were updated. On 08/30/2024, FIA documentation URLs were updated.
Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2014
Currentness_Reference:
Ground condition
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None planned
Spatial_Domain:
Description_of_Geographic_Extent:
Data are provided for forested areas in the conterminous United States.
Bounding_Coordinates:
West_Bounding_Coordinate: -127.97722
East_Bounding_Coordinate: -65.25445
North_Bounding_Coordinate: 51.64968
South_Bounding_Coordinate: 22.76862
Keywords:
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: biota
Theme_Keyword: environment
Theme:
Theme_Keyword_Thesaurus: National Research & Development Taxonomy
Theme_Keyword: Climate change
Theme_Keyword: Carbon
Theme_Keyword: Ecology, Ecosystems, & Environment
Theme_Keyword: Inventory, Monitoring, & Analysis
Theme_Keyword: Natural Resource Management & Use
Theme_Keyword: Conservation
Theme_Keyword: Ecosystem services
Theme_Keyword: Forest management
Theme_Keyword: Wilderness
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: Forest Inventory and Analysis
Theme_Keyword: imputation
Theme_Keyword: LANDFIRE
Theme_Keyword: random forests
Theme_Keyword: fuel data
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: conterminous United States
Place_Keyword: CONUS
Access_Constraints: None
Use_Constraints:
These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the following citation:

Riley, Karin L.; Grenfell, Isaac C.; Shaw, John D. 2023. FuelMap 2014: Imputed map of carbon stored in litter, duff, fine woody debris, and coarse woody debris for CONUS forests circa 2014. Updated 30 August 2024. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2023-0042
Point_of_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA Forest Service, Rocky Mountain Research Station
Contact_Person: Karin Riley
Contact_Position: Research Ecologist
Contact_Address:
Address_Type: mailing and physical
Address: 5775 W. Broadway
City: Missoula
State_or_Province: MT
Postal_Code: 59808
Country: USA
Contact_Voice_Telephone: 406-533-5820
Contact_Electronic_Mail_Address: karin.l.riley@usda.gov
Contact Instructions: This contact information was current as of original publication date. For current information see Contact Us page on: https://doi.org/10.2737/RDS.
Data_Set_Credit:
Funding for this project provided by USDA Forest Service, Rocky Mountain Research Station.


Author Information:

Karin L. Riley
USDA Forest Service, Rocky Mountain Research Station
https://orcid.org/0000-0001-6593-5657

Isaac C. Grenfell
USDA Forest Service, Rocky Mountain Research Station
https://orcid.org/0000-0002-3779-1681

John D. Shaw
USDA Forest Service, Rocky Mountain Research Station
https://orcid.org/0000-0002-5797-1006
Cross_Reference:
Citation_Information:
Originator: Riley, Karin L.
Originator: Grenfell, Isaac C.
Originator: Finney, Mark A.
Publication_Date: 2022
Title:
TreeMap 2016 dataset generates CONUS-wide maps of forest characteristics including live basal area, aboveground carbon, and number of trees per acre
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Journal of Forestry
Issue_Identification: 2022: 607-632
Online_Linkage: https://doi.org/10.1093/jofore/fvac022
Online_Linkage: https://research.fs.usda.gov/treesearch/65597
Cross_Reference:
Citation_Information:
Originator: Riley, Karin L.
Originator: Grenfell, Isaac C.
Originator: Finney, Mark A.
Originator: Shaw, John D.
Publication_Date: 2021
Title:
TreeMap 2016: A tree-level model of the forests of the conterminous United States circa 2016
Geospatial_Data_Presentation_Form: raster and tabular digital data
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: Forest Service Research Data Archive
Online_Linkage: https://doi.org/10.2737/RDS-2021-0074
Cross_Reference:
Citation_Information:
Originator: Riley, Karin L.
Originator: Grenfell, Isaac C.
Originator: Finney, Mark A.
Originator: Wiener, Jason M.
Publication_Date: 2021
Title:
TreeMap, a tree-level model of conterminous US forests circa 2014 produced by imputation of FIA plot data
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Scientific Data
Issue_Identification: 8: 11
Online_Linkage: https://doi.org/10.1038/s41597-020-00782-x
Online_Linkage: https://research.fs.usda.gov/treesearch/61840
Cross_Reference:
Citation_Information:
Originator: Riley, Karin L.
Originator: Grenfell, Isaac C.
Originator: Finney, Mark A.
Originator: Wiener, Jason M.
Originator: Houtman, Rachel M.
Publication_Date: 2019
Title:
Fire Lab tree list: A tree-level model of the conterminous United States landscape circa 2014
Geospatial_Data_Presentation_Form: raster and tabular digital data
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: Forest Service Research Data Archive
Online_Linkage: https://doi.org/10.2737/RDS-2019-0026
Cross_Reference:
Citation_Information:
Originator: Riley, Karin L.
Originator: Grenfell, Isaac C.
Originator: Finney, Mark A.
Originator: Wiener, Jason M.
Publication_Date: 2018
Title:
Fire Lab tree list: A tree-level model of the western US circa 2009 v1
Geospatial_Data_Presentation_Form: raster and tabular digital data
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: Forest Service Research Data Archive
Online_Linkage: https://doi.org/10.2737/RDS-2018-0003
Cross_Reference:
Citation_Information:
Originator: Riley, Karin L.
Originator: Grenfell, Isaac C.
Originator: Finney, Mark A.
Publication_Date: 2016
Title:
Mapping forest vegetation for the western United States using modified random forests imputation of FIA forest plots
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Ecosphere
Issue_Identification: 7(10): e01472
Online_Linkage: https://doi.org/10.1002/ecs2.1472
Online_Linkage: https://research.fs.usda.gov/treesearch/53114
Analytical_Tool:
Analytical_Tool_Description:
The Forest Vegetation Simulator (FVS) is a forest growth simulation model (Dixon 2022). It simulates forest vegetation change in response to natural succession, disturbances, and management. The TreeMap database is designed to be used in FVS via the plot CN, which can be linked to the FIA databases, which contain parameters needed for FVS. For additional information about using FVS to estimate canopy cover and height, as we did to calculate these variables for the FIA plots, see Crookston and Stage (1999).


Crookston Nicholas L.; Stage Albert R. 1999. Percent canopy cover and stand structure statistics from the Forest Vegetation Simulator. General Technical Report. RMRS-GTR-24. Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 11 p. https://doi.org/10.2737/RMRS-GTR-24

Dixon, Gary E. 2022. Essential FVS: A User’s Guide to the Forest Vegetation Simulator. Internal Rep. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Forest Management Service Center. 226p.
Tool_Access_Information:
Online_Linkage: https://www.fs.usda.gov/fvs/
Tool_Access_Instructions:
see website for details
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Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
The methods used to generate FuelMap were similar to those described in Riley et al. (2022) except that the methods were used to identify the most similar plot visit (CN) with DWM measured where plots imputed in TreeMap 2014 did not have DWM measured. Of 31,278 single-condition FIA plot visits (CNs) with DWM measured that were available to the random forests model, 28,319 of these (90.5%) were utilized at least once in imputation to 2,841,601,981 forested pixels. Accuracy is difficult to assess due to the scale at which fuel loading varies and sparsity of validation plots. Accuracy varies from ecoregion to ecoregion and among carbon pools. These data have been validated for applications related to carbon loading of litter, duff, fine woody debris, and coarse woody debris. Validation was performed by comparing the empirical cumulative distribution function of the carbon loading of FIA plots located in an ecoregion to the loadings of the imputed plots. Detailed assessment of the error will be presented in an upcoming publication. Users are recommended to review this publication and assess the suitability of the dataset based on their tolerance of error for various applications, or the authors of this data pub may be contacted for additional information.

Riley, Karin L.; Grenfell, Isaac C.; Shaw, John D.; Finney, Mark A. 2022. TreeMap 2016 dataset generates CONUS-wide maps of forest characteristics including live basal area, aboveground carbon, and number of trees per acre. Journal of Forestry. 2022: 607-632. https://doi.org/10.1093/jofore/fvac022 and https://research.fs.usda.gov/treesearch/65597
Logical_Consistency_Report:
The data are logically consistent. The consistency was verified as part of the quality assurance that occurred during data analysis.
Completeness_Report:
Forest plot visits (CNs) available for imputation were those that met the following criteria: 1) physically located in CONUS, 2) single-condition, 100% forested FIA Phase 2 plots, 3) inventory year between 2004 and 2017 inclusive, and 4) DWM measured on the plot. There were 31,278 plot visits that met these criteria and were available for imputation; of these, 28,319 (90.5%) were chosen for imputation at least once.
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Originator: USDA Forest Service
Publication_Date: 2017
Title:
Forest Inventory and Analysis database
Geospatial_Data_Presentation_Form: tabular digital data
Publication_Information:
Publication_Place: St, Paul, MN
Publisher: USDA Forest Service, Northern Research Station
Other_Citation_Details:
Retrieved 20 September 2017
Online_Linkage: https://doi.org/10.2737/RDS-2001-FIADB
Type_of_Source_Media: Online
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 2004
Ending_Date: 2017
Source_Currentness_Reference:
Ground Condition
Source_Citation_Abbreviation:
FIA DataMart
Source_Contribution:
Estimates of carbon loadings were obtained from the USDA Forest Service's Forest Inventory and Analysis (FIA). Version 1.7.1 and 1.9 data were downloaded from the FIA DataMart. We restricted the plot data to single-condition forested plots only; conditions are defined by changes in vegetation or land use, and some plots have more than one condition because of harvesting or fire. Because we wanted the plots used in the imputation to be more or less homogeneous, we used single-condition plots only. Plot locations in the FIA DataMart are fuzzed to protect plot integrity and true coordinates are not available to the public; for the purposes of this study, we obtained true locations from FIA via a Memorandum of Cooperation. FIA records the number and size of downed woody material pieces along one transect per subplot (FIA 2019). FIA measures the depth of litter and duff at two locations in each of the four subplots, for a total of eight measurements per plot (FIA 2019). From these measurements, FIA estimates the loading in pounds per acre in the litter, duff, and four size classes of woody debris (1-hr, 10-hr, 100-hr, and 1000-hr); these estimates are reported in the COND_DWM_CALC table of their databases (Burrill et al. 2021).

Burrill, Elizabeth A.; DiTommaso, Andrew; Turner, Jeffrey A.; Pugh, Scott A.; Christiansen, Glenn; Perry, Carol J.; Conkling, Barbara L. 2021. The Forest Inventory and Analysis Database: database description and user guide for Phase 2 (version 9.0.1). U.S. Department of Agriculture, Forest Service. https://research.fs.usda.gov/understory/forest-inventory-and-analysis-database-user-guide-nfi

Forest Inventory and Analysis. 2019. National Core Field Guide, Volume 1: Field Data Collection Procedures for Phase 2 Plots (Version 9.0). https://research.fs.usda.gov/understory/nationwide-forest-inventory-field-guide
Source_Information:
Source_Citation:
Citation_Information:
Originator: U.S. Department of Interior, Geological Survey
Publication_Date: Unknown
Title:
LANDFIRE: Landscape Fire and Resource Management Planning Tools
Geospatial_Data_Presentation_Form: raster digital data
Publication_Information:
Publisher: U.S. Department of Interior, Geological Survey
Online_Linkage: https://landfire.gov/version_download.php
Type_of_Source_Media: Online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2014
Source_Currentness_Reference:
Publication Date
Source_Citation_Abbreviation:
LANDFIRE
Source_Contribution:
LANDFIRE provides a suite of topographic, biophysical, and vegetation data at 30x30-m grid resolution for the continental United States that served as the target data for this project.
Process_Step:
Process_Description:
A suite of rasters mapping vegetation and disturbance for the landscape circa 2014 were obtained from the LANDFIRE project’s website (https://landfire.gov/version_download.php), and rasters mapping biophysical characteristics were obtained via a shared server at the Missoula Fire Sciences Lab (these have been made publicly available at https://doi.org/10.6084/m9.figshare.c.5142572). These rasters include: slope, aspect, elevation, Existing Vegetation Cover (EVC), Existing Vegetation Height (EVH), Existing Vegetation Type (EVT), Vegetation Disturbance, average photosynthetically active radiation, average precipitation, average relative humidity, average maximum temperature, average minimum temperature, and average vapor pressure deficit. We used these rasters as target data for the random forests model (see Riley et al. 2016, Riley et al. 2021, and Riley et al. 2022 for more details on methodology). Imputation was made only to pixels that were identified as having forest cover of 10% or greater in the EVC raster, and that had a forested EVT.

Tabular information regarding FIA plots was obtained from the FIA DataMart. True plot locations are not available in the DataMart and were obtained directly from FIA via a Memorandum of Cooperation. We obtained information directly from the FIA DataMart regarding plot elevation, slope, and aspect, as well as tree-level information for each plot. We calculated plot-level tree cover and height using the StrClass keyword in the Forest Vegetation Simulator (Crookston and Stage 1999). Existing Vegetation Type was assigned to each plot using a series of scripts we obtained from LANDFIRE; this information is not publicly available and was obtained via a Memorandum of Cooperation. We assigned biophysical predictors to each plot via spatial overlay of the plot locations with the LANDFIRE rasters in ArcGIS. This plot-level information was used as reference data in the random forests model.

We then used a modified random forests approach with the LANDFIRE vegetation, disturbance, and biophysical predictors as the predictor variables. The model was built using the plots with DWM recorded, and then each plot missing DWM was fed through the model to identify the most similar plot with DWM. Response variables included EVH, EVT, EVC, and disturbance type. The plot CN that most frequently appeared in the terminal bucket with the target plot is the one that was selected for assignment/imputation to all pixels with that reference plot. These relationships were then used to create a spatial map of DWM where each pixel had values for these strata. The resulting map is the FuelMap dataset.


Crookston Nicholas L.; Stage Albert R. 1999. Percent canopy cover and stand structure statistics from the Forest Vegetation Simulator. General Technical Report. RMRS-GTR-24. Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 11 p. https://doi.org/10.2737/RMRS-GTR-24

Riley, Karin L.; Grenfell, Isaac C.; Finney, Mark A. 2016. Mapping forest vegetation for the western United States using modified random forests imputation of FIA forest plots. Ecosphere. 7(10): e01472. https://doi.org/10.1002/ecs2.1472 and https://research.fs.usda.gov/treesearch/53114

Riley, Karin L.; Grenfell, Isaac C.; Finney, Mark A.; Wiener, Jason M. 2021. TreeMap, a tree-level model of conterminous US forests circa 2014 produced by imputation of FIA plot data. Scientific Data. 8: 11. https://doi.org/10.1038/s41597-020-00782-x and https://research.fs.usda.gov/treesearch/61840

Riley, Karin L.; Grenfell, Isaac C.; Shaw, John D.; Finney, Mark A. 2022. TreeMap 2016 dataset generates CONUS-wide maps of forest characteristics including live basal area, aboveground carbon, and number of trees per acre. Journal of Forestry. 2022: 607-632. https://doi.org/10.1093/jofore/fvac022 and https://research.fs.usda.gov/treesearch/65597
Source_Used_Citation_Abbreviation:
1. FIA DATAMART
2. LANDFIRE
3. TreeMap 2014: Riley, Karin L.; Grenfell, Isaac C.; Finney, Mark A.; Wiener, Jason M.; Houtman, Rachel M. 2019. Fire Lab tree list: A tree-level model of the conterminous United States landscape circa 2014. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2019-0026
Process_Date: 2021
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Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Raster
Raster_Object_Information:
Raster_Object_Type: Pixel
Row_Count: 97279
Column_Count: 154180
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Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Planar:
Map_Projection:
Map_Projection_Name: Albers Conical Equal Area
Albers_Conical_Equal_Area:
Standard_Parallel: 29.5
Standard_Parallel: 45.5
Longitude_of_Central_Meridian: -96.0
Latitude_of_Projection_Origin: 23.0
False_Easting: 0
False_Northing: 0
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: Coordinate Pair
Coordinate_Representation:
Abscissa_Resolution: 0.0000000037527980722984474
Ordinate_Resolution: 0.0000000037527980722984474
Planar_Distance_Units: Meters
Geodetic_Model:
Horizontal_Datum_Name: North American Datum of 1983
Ellipsoid_Name: Geodetic Reference System 80
Semi-major_Axis: 6378137.0000
Denominator_of_Flattening_Ratio: 298.25722210
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Entity_and_Attribute_Information:
Overview_Description:
Entity_and_Attribute_Overview:
Below you will find a list and description of the files included in this data publication.

IMPORTANT INFORMATION

The FuelMap is provided in two formats: 1) GeoTIFF (.tif) and 2) Esri geodatabase (.gdb). Both can be linked to the FIA databases using the FuelMapCN raster and a lookup table to retrieve attributes related to fuels/DWM. The FuelMapCN raster contains a numeric code for each pixel that can be looked up in an accompanying table (the attribute table of the “FuelMapCN_tif” raster in the geodatabase or the “CN_lookup.csv”) that contains the longer control numbers (CN) unique to each FIA plot visit (unfortunately the FIA CNs are so long they cannot be stored in a 32-bit raster, and creating a 64-bit raster of the CNs would be prohibitive in size). In FIA’s databases (FIADB), the FIA CNs are stored in the “CN” field of the “PLOT” table and the “PLT_CN” field in all other FIA tables. All plot CNs utilized in this analysis were single condition, 100% forested, 100% accessible, and physically located within the boundaries of CONUS.


DATA FILE DESCRIPTIONS

1. \Data\FuelMap2014.tif:
Raster dataset (GeoTIFF file) representing model output generated by random forests imputation of forest inventory plot data measured by Forest Inventory and Analysis (FIA) to unsampled (and sampled) spatial locations on the landscape for circa 2014 conditions. The values in each band of the raster are described below in the Variable Descriptions section.

2. \Data\FuelMap2014.gdb:
Esri geodatabase built in ArcPro 2.9 representing model output generated by random forests imputation of forest inventory plot data measured by Forest Inventory and Analysis (FIA) to unsampled (and sampled) spatial locations on the landscape for circa 2014 conditions. The values in each raster in the geodatabase are described below in the Variable Descriptions section.

For both files (.tif and .gdb), the predictor variables in the random forests imputation were chosen to optimize the prediction of aboveground forest carbon. These include topographic variables (slope, aspect, and elevation from the FIA PLOT and COND tables), true plot location, vegetation (forest cover, height, and vegetation group assigned to each plot via Forest Vegetation Simulator [FVS, https://www.fs.usda.gov/fvs/] and LANDFIRE methods), disturbance (years since disturbance and disturbance type as derived from LANDFIRE disturbance rasters), and biophysical variables (maximum and minimum temperature, relative humidity, precipitation, photosynthetically active radiation, and vapor pressure deficit derived by overlay of the plot coordinates with LANDFIRE biophysical rasters). Variables and methods are defined in more completeness in Riley et al. (2016), Riley et al. (2021), Riley et al. (2022), and the FIA documentation (Burrill et al. 2021).

3. \Data\CN_lookup.csv:
Comma-separated values file containing the predicted FIA plot CN for each pixel in the “FuelMapCN_tif” raster in the geodatabase or the “FuelMapCN.tif” in the multi-band tiff. The attributes in thie file are described below in the Variable Descriptions section.


VARIABLE DESCRIPTIONS for (1) \Data\FuelMap2014.tif and (2) \Data\FuelMap2014.gdb

FuelMapCN = Unique identifier for an FIA visit to a forest plot. Signifies the FIA plot visit assigned by random forests to each pixel in the FuelMap; this is the plot visit from which the DWM was assigned. This field holds 32-bit unique numeric codes for each plot visit; the longer FIA CN codes can be looked up in an accompanying table (the attribute table of the “FuelMapCN_tif” raster in the geodatabase or the “CN_lookup.csv”). The FIA CN codes can be used to link to tables in FIADB via the “CN” field in the PLOT table or the “PLT_CN” field in other tables including COND_DWM_CALC. This field is a text field due to its length and should not be converted to a numeric field or most software programs will round or truncate it. (In the .gdb: ObjectID = unique ID field added by ArcPro; Value = unique ID field; corresponds to ObjectID; Count = number of times each PredCN occurs; PredCN = the FIA plot CN imputed for each Value in the raster)

CWD_CARBON = The loading of coarse woody debris (1000-hour [hr] fuels or woody debris greater than or equal to 3 inches ["] in diameter) in pounds per acre (equivalent to CWD_CARBON_COND in FIA’s COND_DWM_CALC table for the imputed FuelMapCN at this pixel).

DUFF_CARBON = The average duff loading in pounds per acre on the plot (equivalent to DUFF_CARBON in FIA’s COND_DWM_CALC table for the imputed FuelMapCN at this pixel).

FWD_LG_CARBON = The loading of fine woody debris in the 100-hr size class (from 1" up to 3" in diameter) in pounds per acre (equivalent to the FWD_LG_CARBON_COND field in FIA’s COND_DWM_CALC table for the imputed FuelMapCN at this pixel).

FWD_MD_CARBON = The loading of fine woody debris in the 10-hr size class (from ¼” up to 1” in diameter) in pounds per acre (equivalent to the FWD_MD_CARBON_COND field in FIA’s COND_DWM_CALC table for the imputed FuelMapCN at this pixel).

FWD_SM_CARBON = The loading of fine woody debris in the 1-hr size class (up to ¼” in diameter) in pounds per acre (equivalent to the FWD_SM_CARBON_COND field in FIA’s COND_DWM_CALC table for the imputed FuelMapCN at this pixel).

LITTER_CARBON = The average litter loading in pounds per acre on the plot (equivalent to LITTER_CARBON in FIA’s COND_DWM_CALC table for the imputed FuelMapCN at this pixel).

TOTAL_C = Total carbon in the forest floor in pounds per acre, derived by adding the following fields: FWD_SM_CARBON + FWD_MD_CARBON + FWD_LG_CARBON + CWD_CARBON + DUFF_CARBON + LITTER_CARBON.


VARIABLE DESCRIPTIONS for (3) \Data\CN_lookup.csv

Value = A 32-bit numeric code that corresponds to the imputed plot in the “FuelMapCN_tif” raster in the geodatabase or the “FuelMapCN.tif” in the multi-band tiff.

PredCN = For each “Value”, the corresponding code for a unique visit to an FIA plot. The FIA CN codes can be used to link to tables in FIADB via the “CN” field in the PLOT table or the “PLT_CN” field in other tables including COND_DWM_CALC.
Entity_and_Attribute_Detail_Citation:
Burrill, Elizabeth A.; DiTommaso, Andrew; Turner, Jeffrey A.; Pugh, Scott A.; Christiansen, Glenn; Perry, Carol J.; Conkling, Barbara L. 2021. The Forest Inventory and Analysis Database: database description and user guide for Phase 2 (version 9.0.1). U.S. Department of Agriculture, Forest Service. https://research.fs.usda.gov/understory/forest-inventory-and-analysis-database-user-guide-nfi

Riley, Karin L.; Grenfell, Isaac C.; Finney, Mark A. 2016. Mapping forest vegetation for the western United States using modified random forests imputation of FIA forest plots. Ecosphere. 7(10): e01472. https://doi.org/10.1002/ecs2.1472 and https://research.fs.usda.gov/treesearch/53114

Riley, Karin L.; Grenfell, Isaac C.; Finney, Mark A.; Wiener, Jason M. 2021. TreeMap, a tree-level model of conterminous US forests circa 2014 produced by imputation of FIA plot data. Scientific Data. 8: 11. https://doi.org/10.1038/s41597-020-00782-x and https://research.fs.usda.gov/treesearch/61840

Riley, Karin L.; Grenfell, Isaac C.; Shaw, John D.; Finney, Mark A. 2022. TreeMap 2016 dataset generates CONUS-wide maps of forest characteristics including live basal area, aboveground carbon, and number of trees per acre. Journal of Forestry. 2022: 607-632. https://doi.org/10.1093/jofore/fvac022 and https://research.fs.usda.gov/treesearch/65597
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Distribution_Information:
Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA Forest Service, Research and Development
Contact_Position: Research Data Archivist
Contact_Address:
Address_Type: mailing and physical
Address: 240 West Prospect Road
City: Fort Collins
State_or_Province: CO
Postal_Code: 80526
Country: USA
Contact_Voice_Telephone: see Contact Instructions
Contact Instructions: This contact information was current as of August 2024. For current information see Contact Us page on: https://doi.org/10.2737/RDS.
Resource_Description: RDS-2023-0042
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Metadata documents have been reviewed for accuracy and completeness. Unless otherwise stated, all data and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. However, neither the author, the Archive, nor any part of the federal government can assure the reliability or suitability of these data for a particular purpose. The act of distribution shall not constitute any such warranty, and no responsibility is assumed for a user's application of these data or related materials.

The metadata, data, or related materials may be updated without notification. If a user believes errors are present in the metadata, data or related materials, please use the information in (1) Identification Information: Point of Contact, (2) Metadata Reference: Metadata Contact, or (3) Distribution Information: Distributor to notify the author or the Archive of the issues.
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Format_Name: CSV
Format_Version_Number: see Format Specification
Format_Specification:
Comma-separated values file
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Network_Address:
Network_Resource_Name: https://doi.org/10.2737/RDS-2023-0042
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Digital_Transfer_Information:
Format_Name: TIFF
Format_Version_Number: see Format Specification
Format_Specification:
Georeferenced tagged image format file
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Network_Address:
Network_Resource_Name: https://doi.org/10.2737/RDS-2023-0042
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Metadata_Reference_Information:
Metadata_Date: 20240830
Metadata_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA Forest Service, Rocky Mountain Research Station
Contact_Person: Karin Riley
Contact_Position: Research Ecologist
Contact_Address:
Address_Type: mailing and physical
Address: 5775 W. Broadway
City: Missoula
State_or_Province: MT
Postal_Code: 59808
Country: USA
Contact_Voice_Telephone: 406-533-5820
Contact_Electronic_Mail_Address: karin.l.riley@usda.gov
Contact Instructions: This contact information was current as of original publication date. For current information see Contact Us page on: https://doi.org/10.2737/RDS.
Metadata_Standard_Name: FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001.1-1999
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