Contiguous U.S. Biomass Map

Metadata:

Identification_Information:
Citation:
Citation_Information:
Originator:
USDA Forest Service Forest Invenstory and Analysis, Remote Sensing Applications Center
Publication_Date: 2008
Title:
Mapping U.S. forest biomass using nationwide forest inventory data and moderate resolution information
Authors: J.A. Blackard, M.V. Finco, E.H. Helmer, G.R. Holden, M.L. Hoppus, D.M. Jacobs, A.J. Lister, G.G. Moisen, M.D. Nelson, R. Riemann, B. Ruefenacht, D. Salajanu, D.L Weyermann, K.C. Winterberger, T.J. Brandeis, R.L. Czaplewski, R.E. McRoberts, P.L. Patterson, R.P. Tymcio
Geospatial_Data_Presentation_Form: remote-sensing image
Series_Information:
Series_Name: Remote Sensing of Environment
Issue_Identification: 112:1658-1677
Publication_Information:
Publisher: Elsevier
Online_Linkage: <https://data.fs.usda.gov/geodata/rastergateway/biomass/>
Description:
Abstract:
A spatially explicit dataset of aboveground live forest biomass was made from ground measured inventory plots for the conterminous U.S., Alaska and Puerto Rico. The plot data are from the USDA Forest Service Forest Inventory and Analysis (FIA) program. To scale these plot data to maps, we developed models relating field-measured response variables to plot attributes serving as the predictor variables. The plot attributes came from intersecting plot coordinates with geospatial datasets. Consequently, these models serve as mapping models. The geospatial predictor variables included Moderate Resolution Imaging Spectrometer (MODIS)-derived image composites and percent tree cover; land cover proportions and other data from the National Land Cover Dataset (NLCD); topographic variables; monthly and annual climate parameters; and other ancillary variables. We segmented the Mapping models for the U.S. into 65 ecologically similar mapping zones, plus Alaska and Puerto Rico. First, we developed a forest mask by modeling the forest vs. nonforest assignment of field plots as functions of the predictor layers using classification trees in See5©. Secondly, forest biomass models were built within the predicted forest areas using tree-based algorithms in Cubist©. To validate the models, we compared field-measured with model predicted forest/nonforest classification and biomass from an independent test set, randomly selected from available plot data for each mapping zone. The estimated proportion of correctly classified pixels for the forest mask ranged from 0.79 in Puerto Rico to 0.94 in Alaska. For biomass, model correlation coefficients ranged from a high of 0.73 in the Pacific Northwest, to a low of 0.31 in the Southern region. There was a tendency in all regions for these models to over-predict areas of small biomass and under-predict areas of large biomass, not capturing the full range in variability. Map-based estimates of forest area and forest biomass compared well with traditional plot-based estimates for individual states and for four scales of spatial aggregation. Variable importance analyses revealed that MODIS-derived information could contribute more predictive power than other classes of information when used in isolation. However, the true contribution of each variable is confounded by high correlations. Consequently, excluding anyone class of variables resulted in only small effects on overall map accuracy. An estimate of total C pools in live forest biomass of U.S. forests, derived from the nationwide biomass map, also compared well with previously published estimates.
Purpose:
The purpose of this dataset is to portray broad distribution patterns of biomass in the contiguous U.S. and provide input to national scale modeling projects.
Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2003
Currentness_Reference: ground condition
Status:
Progress: Complete
Maintenance_and_Update_Frequency: Irregular
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -127.977889
East_Bounding_Coordinate: -65.256686
North_Bounding_Coordinate: 51.652084
South_Bounding_Coordinate: 22.802651
Keywords:
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: FIA
Theme_Keyword: Biomass
Theme_Keyword: Forest Inventory and Analysis
Theme_Keyword: MODIS
Theme_Keyword: CART
Access_Constraints: None
Use_Constraints:
None. It is the responsibility of the data user to use the data appropriately and consistent within the limitations of geospatial data in general and these data in particular. Using the data for other than their intended purpose may yield inaccurate or misleading results.
Point_of_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA Forest Service Forest Inventory and Analysis
Contact_Person: Gretchen G. Moisen, Ph.D.
Contact_Position: Research Scientist
Contact_Address:
Address_Type: mailing and physical address
Address: 507 25th Street
City: Ogden
State_or_Province: Utah
Postal_Code: 84401
Country: USA
Contact_Voice_Telephone: 801-625-5384
Contact_Facsimile_Telephone: 801-625-5723
Contact_Electronic_Mail_Address: gmoisen@fs.fed.us
Data_Set_Credit:
Acknowledgement of the USDA Forest Service Forest Inventory and Analysis Program and Remote Sensing Applications Center would be appreciated in products derived from these data.
Native_Data_Set_Environment:
Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 4; ESRI ArcCatalog 9.1.0.722

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Data_Quality_Information:
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Originator: USDA Forest Service Remote Sensing Applications Center
Publication_Date: 2002
Title: Dominate Aspect
Other_Citation_Details:
Created using USGS National Elevation Dataset (<https://www.usgs.gov>) Processing Steps 1. Imported BILmeters format into ESRI GRID format. 2. Reprojected into Albers Conical Equal Area NAD 27 with a 60m resolution 3. Mosaicked tiles into a contiguous dataset 4. Resampled to 30m resolution to maintan continuity with CONUS dataset 5. Used a 3x3 focal mean function to output a 90m DEM dataset 6. Created an Aspect Dataset from the 90m DEM 7. Reclassified the Aspect dataset into 4 categories Category 1: 0° - 90° Category 2: 90° - 180° Category 3: 180° - 270° Category 4: 270° - 360° 8. Performed a 3x3 Focal Majority output to 270m resolution 9. Reprojected/Resampled to a 250m NAD83 dataset.
Source_Scale_Denominator: 30-meter
Type_of_Source_Media: CD-ROM
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2002
Source_Currentness_Reference: ground condition
Source_Citation_Abbreviation: Dominate Aspect
Source_Information:
Source_Citation:
Citation_Information:
Originator: USDA Forest Service Remote Sensing Applications Center
Publication_Date: 2002
Title: Mean Elevation
Other_Citation_Details:
Created using USGS National Elevation Dataset (<https://www.usgs.gov>) Processing Steps 1. Imported BILmeters format into ESRI GRID format. 2. Reprojected into Albers Conical Equal Area NAD 27 with a 60m resolution 3. Mosaicked tiles into a contiguous dataset 4. Resampled to 30m resolution to maintan continuity with CONUS dataset 5. Used a 3x3 focal mean function to output a 90m DEM dataset 6. Reprojected / Resampled to NAD83 with 250m cell size using Bilear Interpolation.
Source_Scale_Denominator: 30-m
Type_of_Source_Media: CD-ROM
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2002
Source_Currentness_Reference: ground condition
Source_Citation_Abbreviation: Mean Elevation
Source_Information:
Source_Citation:
Citation_Information:
Originator: USDA Forest Service Remote Sensing Applications Center
Publication_Date: 2002
Title: Percent Slope
Other_Citation_Details:
Created using USGS National Elevation Dataset (<https://www.usgs.gov>) Processing Steps 1. Imported BILmeters format into ESRI GRID format. 2. Reprojected into Albers Conical Equal Area NAD 27 with a 60m resolution 3. Mosaicked tiles into a contiguous dataset 4. Resampled to 30m resolution to maintan continuity with CONUS dataset 5. Used a 3x3 focal mean function to output a 90m DEM dataset 6. Reprojected / Resampled to NAD83 with 250m cell size using Bilear Interpolation.
Source_Scale_Denominator: 30-meter
Type_of_Source_Media: CD-ROM
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2002
Source_Currentness_Reference: ground condition
Source_Citation_Abbreviation: Percent Slope
Source_Information:
Source_Citation:
Citation_Information:
Originator: USDA Forest Service Remote Sensing Applications Center
Publication_Date: 2002
Title: Variety Dominate Aspect
Other_Citation_Details:
Created using USGS National Elevation Dataset (<https://www.usgs.gov>) Processing Steps 1. Imported BILmeters format into ESRI GRID format. 2. Reprojected into Albers Conical Equal Area NAD 27 with a 60m resolution. 3. Mosaicked tiles into a contiguous dataset. 4. Resampled to 30m resolution to maintan continuity with CONUS dataset. 5. Used a 3x3 focal mean function to output a 90m DEM dataset. 6. Created an Aspect Dataset from the 90m DEM. 7. Reclassified the Aspect dataset into 4 categories. Category 1: 0° - 90° Category 2: 90° - 180° Category 3: 180° - 270° Category 4: 270° - 360° 8. Performed 3x3 Focal Variety function output to 270m. 9. Reprojeced / Resampled to NAD83 at 250m resolution.
Source_Scale_Denominator: 30-meter
Type_of_Source_Media: CD-ROM
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2002
Source_Currentness_Reference: ground condition
Source_Citation_Abbreviation: Variety Dominate Aspect
Source_Information:
Source_Citation:
Citation_Information:
Originator: USDA Forest Service
Publication_Date: 200403
Title:
Baileys Ecoregions and Subregions of the United States, Puerto Rico, and the U.S. Virgin Islands
Other_Citation_Details:
This map layer is commonly called Baileys ecoregions and shows ecosystems of regional extent in the United States, Puerto Rico, and the U.S. Virgin Islands. Processing Steps: 1. Downloaded file from <https://www.fs.fed.us/institute/ecoregions/eco_download.html>. 2. Imported ArcInterchange file into ArcCoverage format (Albers Conical Equal Area Clark1866) 3. Imported ArcCoverage file into raster format with 250m cell resolution. 4. Reprojected / Resampled to common Albers Conical Equal Area NAD83 projection.
Online_Linkage: <https://www.nationalatlas.gov>
Type_of_Source_Media: online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 200403
Source_Currentness_Reference: ground condition
Source_Citation_Abbreviation: Bailey's Ecoregions
Source_Information:
Source_Citation:
Citation_Information:
Originator: USGS
Publication_Date: 2002
Title: MODIS Enhanced Vegetation Index
Other_Citation_Details:
Created using MODIS data from the Land Processes Distribution Active Archive Center (<https://edcdaac.usgs.gov/main.html>) LP DAAC Data Set - MODIS/Terra Vegetation Indices 16-Day L3 Global 250 ISIN GRID v003 MODIS Product - MOD13Q1 Processing Steps: 1. Imported MODIS EOD HDF format file into ERDAS Imagine (*,img) format. 2. Reprojected into Albers Conical Equal Area NAD27 from Integerized Sinusoidal using ERDAS Imagine 8.5 with the Nearest Neighbor and Rigerous Transformation options selected. 3. Mosaicked Tiled data into a contiguous dataset. 4. Subset area of interest from entire image 5. Resampled / reprojected to a common coordinate system & resolution (250m) in an Albers Conical Equal Area NAD83 projection.
Online_Linkage: <https://edcdaac.usgs.gov/main.html>
Source_Scale_Denominator: 250-meter
Type_of_Source_Media: online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2002
Source_Currentness_Reference: ground condition
Source_Citation_Abbreviation: MODIS EVI
Source_Information:
Source_Citation:
Citation_Information:
Originator: USGS
Publication_Date: 2002
Title: MODIS NDVI
Other_Citation_Details:
Created using MODIS data from the Land Processes Distribution Active Archive Center (<https://edcdaac.usgs.gov/main.html>) LP DAAC Data Set - MODIS/Terra Vegetation Indices 16-Day L3 Global 250 ISIN GRID v003 MODIS Product - MOD13Q1 Processing Steps: 1. Imported MODIS EOD HDF format file into ERDAS Imagine (*,img) format. 2. Reprojected into Albers Conical Equal Area NAD27 from Integerized Sinusoidal using ERDAS Imagine 8.5 with the Nearest Neighbor and Rigerous Transformation options selected. 3. Mosaicked Tiled data into a contiguous dataset. 4. Subset area of interest from entire image 5. Resampled / reprojected to a common coordinate system & resolution (250m) in an Albers Conical Equal Area NAD83 projection.
Online_Linkage: <https://edcdaac.usgs.gov/main.html>
Source_Scale_Denominator: 250-meter
Type_of_Source_Media: online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2002
Source_Currentness_Reference: ground condition
Source_Citation_Abbreviation: MODIS NDVI
Source_Information:
Source_Citation:
Citation_Information:
Originator: University of Maryland
Publication_Date: 2002
Title: MODIS 8-day Composites - Global Land Cover Facility
Other_Citation_Details:
The GLCF develops and distributes remotely sensed satellite data and products concerned with land cover from the local to global scales.
Online_Linkage: <http://glcf.umiacs.umd.edu/index.shtml>
Source_Scale_Denominator: 250-meter
Type_of_Source_Media: online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2002
Source_Currentness_Reference: ground condition
Source_Citation_Abbreviation: MODIS
Source_Information:
Source_Citation:
Citation_Information:
Originator: U.S. Geological Survey (USGS)
Publication_Date: 20000815
Title: National Land Cover Data Set
Other_Citation_Details:
Created using USGS National Land Cover dataset (<http://landcover.usgs.gov/natllandcover.html>) Processing Steps 1. Mosaicked individual state datasets into FIA Regions 2. Extracted desired class into a binary dataset 3. Ran a 9x9 focal sum function then divided by 81 to get percentage. 4. Resampled to 250m resolution using Nearest Neighbor 5. Mosaicked FIA regions into a CONUS dataset.
Online_Linkage: <http://landcover.usgs.gov>
Source_Scale_Denominator: 30-meter
Type_of_Source_Media: online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 20000815
Source_Currentness_Reference: ground condition
Source_Citation_Abbreviation: NLCD
Source_Information:
Source_Citation:
Citation_Information:
Originator: U.S. Geological Survey (USGS)
Publication_Date: 2002
Title: MODIS Vegetation Continuous Fields
Other_Citation_Details:
Created using MODIS data from the Land Processes Distribution Active Archive Center (<https://edcdaac.usgs.gov/main.html>) LP DAAC Data Set - MODIS/Terra Vegetation Continuous Fields Yearly L3 Global 500m ISIN v003 MODIS Product - MOD44B Processing Steps: 1. Imported MODIS EOD HDF format file into ERDAS Imagine (*,img) format. 2. Reprojected into Lambert Conformal Conic NAD27 from Integerized Sinusoidal using ERDAS Imagine 8.5 with the Nearest Neighbor and Rigerous Transformation options selected. 3. Subset area of interest from entire image 4. Resampled / reprojected to a common coordinate system & resolution (250m)
Online_Linkage: <https://edcdaac.usgs.gov/main.html>
Source_Scale_Denominator: 250-meter
Type_of_Source_Media: online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2002
Source_Currentness_Reference: ground condition
Source_Citation_Abbreviation: MODIS VCF
Source_Information:
Source_Citation:
Citation_Information:
Originator: University of Montana
Publication_Date: 1980-1997
Title: Daymet Precipitation and Temperature
Online_Linkage: <http://www.daymet.org/>
Source_Scale_Denominator: 1-kilometer
Type_of_Source_Media: CD-ROM
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 1980
Ending_Date: 1997
Source_Currentness_Reference: ground condition
Source_Citation_Abbreviation: Precipitation and Temperature
Process_Step:
Process_Description:
The methodology used to produce the database combined ground-truth (from FIA plot data) with multi-date imagery and variety of other spatially continuous geospatial data. The predictor data themes include,

- Elevation, slope, and aspect - Bailey's Ecoregions - MODIS Vegetation Indices such as EVI, NDVI - MODIS Vegetation Continuous Fields - MODIS fire points for developed from the MODIS Active Fire Maps - MODIS 8-day composites - climate data.

Statistical models developed in Rulequest's Cubist data mining software link the FIA plot variables with the imagery and geospatial data. Cubist creates rulesets, which have the advantage of not assuming parametric properties within the predictor data and are thus are more appropriate for the multi-scale, multi-source data, which are being used.

Process_Date: 2003

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Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Raster
Raster_Object_Information:
Raster_Object_Type: Pixel
Row_Count: 11659
Column_Count: 18501
Vertical_Count: 1

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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: 29.500000
Standard_Parallel: 45.500000
Longitude_of_Central_Meridian: -96.000000
Latitude_of_Projection_Origin: 23.000000
False_Easting: 0.000000
False_Northing: 0.000000
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: row and column
Coordinate_Representation:
Abscissa_Resolution: 250.000000
Ordinate_Resolution: 250.000000
Planar_Distance_Units: meters
Geodetic_Model:
Horizontal_Datum_Name: North American Datum of 1927
Ellipsoid_Name: Clarke 1866
Semi-major_Axis: 6378206.400000
Denominator_of_Flattening_Ratio: 294.978698

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Entity_and_Attribute_Information:
Detailed_Description:
Entity_Type:
Entity_Type_Label: Layer 1
Entity_Type_Definition: Biomass
Attribute:
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 0
Range_Domain_Maximum: 2205.8
Attribute_Units_of_Measure: Mg/ha

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Distribution_Information:
Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA Forest Service Remote Sensing Applications Center
Contact_Address:
Address_Type: mailing and physical address
Address: 2222 West 2300 South
City: West Valley City
State_or_Province: Utah
Postal_Code: 84119
Country: USA
Contact_Voice_Telephone: 801-975-3750
Contact_Facsimile_Telephone: 801-975-3478
Resource_Description: Downloadable Data
Distribution_Liability:
Although these data have been used by the USDA Forest Service, the USDA Forest Service shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data are not legal documents and are not intended to be used as such. It is the responsibility of the data user to use the data appropriately and consistent within the limitations of geospatial data in general and these data in particular. Using the data for other than their intended purpose may yield inaccurate or misleading results. The USDA Forest Service gives no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data. It is strongly recommended that these data are directly acquired from the USDA Forest Service server and not indirectly through other sources which may have changed the data in some way. Although these data have been processed successfully on a computer system at the USDA Forest Service, no warranty expressed or implied is made regarding the utility of the data on another system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. This disclaimer applies both to individual use of the data and aggregate use with other data.

The USDA Forest Service reserves the right to correct, update or modify this data and related materials without notification.

Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Format_Name: ERDAS
Transfer_Size: 0.000

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Metadata_Reference_Information:
Metadata_Date: 20081104
Metadata_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA Forest Service Remote Sensing Applications Center
Contact_Person: Bonnie Ruefenacht
Contact_Position: Remote Sensing Analyst
Contact_Address:
Address_Type: mailing and physical address
Address: 2222 West 2300 South
City: West Valley City
State_or_Province: Utah
Postal_Code: 84119
Country: USA
Contact_Voice_Telephone: 801-975-3828
Contact_Facsimile_Telephone: 801-975-3478
Contact_Electronic_Mail_Address: bruefenacht@fs.fed.us
Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998
Metadata_Time_Convention: local time
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile

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