NaFIS Core Forest Attribute Data: Forest Type Group, MRLC Zone 51

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Additional Metadata Resources: NaFIS Core Forest Attribute Data: Forest Type Group, MRLC Zone 51 Attribute Accuracy Report

Frequently-anticipated questions:

What does this data set describe?

Title:
NaFIS Core Forest Attribute Data: Forest Type Group, MRLC Zone 51
Abstract:
This data layer is a raster of forest type group over Multi-Resolution Land Characteristics (MRLC) Mapping Zone 51. The information was produced by using k-Nearest Neighbors classification techniques. Forest Inventory and Analysis (FIA) subplots are the source of the reference set of forest attribute data. The target feature space variables are a stack of 8 raster bands which include: the brightness, greenness, and wetness bands from a tasseled-cap transformed Landsat Thematic Mapper (TM) satellite image, NDVI derived from TM imagery, the average annual precipitation, maximum temperature, and minimum temperature from 1971 - 2000 derived from PRISM climate data, and elevation derived from the USGS Elevation Data for National Applications (EDNA) digital elevation model (DEM).
Supplemental_Information:
This project (Nationwide Forest Imputation Study, NaFIS) evaluates alternative nearest neighbor techniques with the ultimate goal of recommending an approach for nationwide implementation. Study objectives are to: (1) evaluate alternative nearest neighbor algorithms, (2) develop computing systems for efficient implementation, and (3) produce map products, including variance estimators and accuracy assessments, for multiple forest attributes. The vision for a national nearest neighbor application is to rely on FIA data as the primary source of forest data, and Landsat as the primary remotely sensed data. Other forest, environmental, and physiographic data will be tested for applicability, and ultimately these data inputs could vary by region.
  1. How should this data set be cited?

    Nationwide Forest Imputation Study (NaFIS), 20090324, NaFIS Core Forest Attribute Data: Forest Type Group, MRLC Zone 51: Nationwide Forest Imputation Study (NaFIS) NaFIS Core Forest Attribute Data: Forest Type Group, MRLC Zone 51, Nationwide Forest Imputation Study (NaFIS), East Lansing, Michigan.

    Online Links:

  2. What geographic area does the data set cover?

    West_Bounding_Coordinate: -91.001258
    East_Bounding_Coordinate: -81.247578
    North_Bounding_Coordinate: 48.300197
    South_Bounding_Coordinate: 41.148606

  3. What does it look like?

  4. Does the data set describe conditions during a particular time period?

    Beginning_Date: 2001
    Ending_Date: 2006
    Currentness_Reference: Ground Condition

  5. What is the general form of this data set?

    Geospatial_Data_Presentation_Form: Raster Digital Data

  6. How does the data set represent geographic features?

    1. How are geographic features stored in the data set?

      Indirect_Spatial_Reference: MRLC Mapping Zone 51
      This is a Raster data set. It contains the following raster data types:
      • Dimensions 24302 x 23317, type Pixel

    2. What coordinate system is used to represent geographic features?

      The map projection used is Albers Conical Equal Area.

      Projection parameters:
      Standard_Parallel: 29.5
      Standard_Parallel: 45.5
      Longitude_of_Central_Meridian: -96
      Latitude_of_Projection_Origin: 23
      False_Easting: 0
      False_Northing: 0

      Planar coordinates are encoded using Row and Column
      Abscissae (x-coordinates) are specified to the nearest 30
      Ordinates (y-coordinates) are specified to the nearest 30
      Planar coordinates are specified in Meters

      The horizontal datum used is North American Datum of 1983.
      The ellipsoid used is Geodetic Reference System 80.
      The semi-major axis of the ellipsoid used is 6378137.
      The flattening of the ellipsoid used is 1/298.257222.

  7. How does the data set describe geographic features?

    Layer_1
    Forest Type Group (Source: Forest Inventory and Analysis Program. 2008. The Forest Inventory and Analysis Database: Database Description and Users Manual Version 3.0 for Phase 2, Revision 1. U.S. Department of Agriculture, Forest Service, Washington Office. Available: <http://www.fia.fs.fed.us/library/database-documentation/FIADB_user_manual_v3-0.pdf>.)

    Forest Type Group
    Forest type groups are the aggregation of FIA forest types into similar groups. Forest type is defined as "a classification of forest land based upon the trees or tree communities that constitute the majority of stocking on the site" (Forest Inventory and Analysis Program, 2007). The forest type group codes can be found in Appendix D of The Forest Inventory and Analysis Database: Database Description and Users Manual Version 3.0 for Phase 2. (Source: Forest Inventory and Analysis Program. 2008. The Forest Inventory and Analysis Database: Database Description and Users Manual Version 3.0 for Phase 2, Revision 1. U.S. Department of Agriculture, Forest Service, Washington Office. Available: <http://www.fia.fs.fed.us/library/database-documentation/FIADB_user_manual_v3-0.pdf>. Forest Inventory and Analysis Program. 2007. Forest Inventory and Analysis National Core Field Guide, Volume 1: Field Data Collection Procedures for Phase 2 Plots, Version 4.0. U.S. Department of Agriculture, Forest Service, Washington Office. Available: <http://www.fia.fs.fed.us/library/field-guides-methods-proc/docs/core_ver_4-0_10_2007_p2.pdf>)

    ValueDefinition
    100White/Red/Jack Pine Group
    120Spruce/Fir Group
    180Pinyon/Juniper Group
    200Douglas-Fir Group
    260Fir/Spruce/Mountain Hemlock Group
    380Exotic Softwoods Group
    400Oak/Pine Group
    500Oak/Hickory Group
    600Oak/Gum/Cypress Group
    700Elm/Ash/Cottonwood Group
    800Maple/Beech/Birch Group
    900Aspen/Birch Group

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)

  2. Who also contributed to the data set?

    Collaborators and Sponsors: Forest Health Technology Enterprise Team (FHTET); USDA Forest Service; Forest Inventory and Analysis (FIA) Program; Western Wildlands Environmental Threat Assessment Center (WWETAC); Eastern Forest Environmental Threat Assessment (EFETAC).

  3. To whom should users address questions about the data?

    Brian Walters
    Michigan State University
    126 Natural Resources Building
    East Lansing, Michigan 48824
    United States

    517-432-3537 (voice)

Why was the data set created?

Provide data that are spatially explicit and statistically valid large- and small-area estimates of forest attributes measured by the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service. For use in supporting applications ranging from scenario modeling (e.g., fire, insect, pathogens, wildlife habitat) at the mid- or regional-scale, to broad ecosystem modeling (e.g., carbon sources/sinks, climate change, and ecosystem services).

How was the data set created?

  1. From what previous works were the data drawn?

    FIA_Data (source 1 of 8)
    USDA Forest Service Forest Inventory and Analysis Program (FIA), 2008, FIA Database.

    Online Links:

    Type_of_Source_Media: Online
    Source_Contribution: Spatial and Attribute Information

    RSAC_Mosaic_Tasseled_Cap (source 2 of 8)
    USDA Forest Service Remote Sensing Applications Center (RSAC), Unpublished Material, z51_mosaic_tm5_bands_12345n7_tcap.img.

    Type_of_Source_Media: Disc
    Source_Contribution: Remotely Sensed, Tasseled Cap Transformed Spectral Data

    RSAC_Mosaic_NDVI (source 3 of 8)
    USDA Forest Service Remote Sensing Applications Center (RSAC), Unpublished Material, z51_mosaic_tm5_ndvi.img.

    Type_of_Source_Media: Disc
    Source_Contribution: Normalized Differential Vegetation Index (NDVI) Data

    PPT_PRISM (source 4 of 8)
    USDA Forest Service Remote Sensing Applications Center (RSAC), Unpublished Material, z51_ppt_1971_2000_albers_nad83_30m_13layers_sceneboundary_buffer_2400m.img.

    Type_of_Source_Media: Disc
    Source_Contribution: PRISM Precipitation Data

    TMax_PRISM (source 5 of 8)
    USDA Forest Service Remote Sensing Applications Center (RSAC), Unpublished Material, z51_tmax_1971_2000_albers_nad83_30m_13layers_fixed_background_sceneboundary_buffer_2400m.img.

    Type_of_Source_Media: Disc
    Source_Contribution: PRISM Temperature Data

    TMin_PRISM (source 6 of 8)
    USDA Forest Service Remote Sensing Applications Center (RSAC), Unpublished Material, z51_tmin_1971_2000_albers_nad83_30m_13layers_fixed_background_sceneboundary_buffer_2400m.img.

    Type_of_Source_Media: Disc
    Source_Contribution: PRISM Temperature Data

    RSAC_Topo (source 7 of 8)
    USDA Forest Service Remote Sensing Applications Center (RSAC), Unpublished Material, z51_topo_stack_dem_slp_asp_taspsin_taspcos_cti.img.

    Type_of_Source_Media: Disc
    Source_Contribution: Topographical Data

    Strata_Mask (source 8 of 8)
    Walters, Brian, Unpublished Material, Modified Date Strata, 4 Strata.

    Type_of_Source_Media: Disc
    Source_Contribution: Stratification for use with classification

  2. How were the data generated, processed, and modified?

    Date: 03-Mar-2009 (process 1 of 5)
    Create a dataset of FIA subplots that are within MRLC Zone 51 and meet necessary requirements. Those requirements include subplots that were sampled, had condition status code 1 (forested), were given a forest type, and were in the appropriate evaluation for each state within Zone 51 (Table 1).

    Table 1: Zone 51 Evaluations
    Evaluation ID Evaluation Description
    180601 Indiana, 2002-2006: area/volume
    260601 Michigan, 2002-2006: area/volume
    395552 Ohio, 2001-2005: area/volume
    550601 Wisconsin, 2002-2006: area/volume

    Data sources used in this process:

    • FIA_Data

    Data sources produced in this process:

    • z51_FIA_subplots

    Date: 19-Feb-2009 (process 2 of 5)
    Extract the average annual band from each of the PRISM climate data rasters. Using the Geographic Resources Analysis Support System (GRASS) Version 6.4, run a 9 x 9 averaging kernal over each band. The original PRISM data has a resolution of 800 meters which was resampled for this analysis to 30 meters by RSAC. The averaging kernal smooths the data.

    Data sources used in this process:

    • PPT_PRISM
    • TMax_PRISM
    • TMin_PRISM

    Data sources produced in this process:

    • ppt_9x9
    • tmx_9x9
    • tmn_9x9

    Date: 20-Feb-2009 (process 3 of 5)
    Extract the brightness, greenness, and wetness bands from the tasseled cap mosaic and extract the DEM from the topographic data mosaic. Create a stack of the data layers to be used in the analysis (Table 2).

    Table 2: Spectral Data Stack
    Layer # Layer Description
    1 Tasseled Cap Brightness
    2 Tasseled Cap Greenness
    3 Tasseled Cap Wetness
    4 NDVI
    5 Average Annual Precipitation 1971-2000 (smoothed)
    6 Average Annual Maximum Temperature 1971-2000 (smoothed)
    7 Average Annual Minimum Temperature 1971-2000 (smoothed)
    8 Elevation

    Data sources used in this process:

    • RSAC_Mosaic_Tasseled_Cap
    • RSAC_Mosaic_NDVI
    • ppt_9x9
    • tmx_9x9
    • tmn_9x9
    • RSAC_Topo

    Data sources produced in this process:

    • spectral_data_stack

    Date: 04-Mar-2009 (process 4 of 5)
    Use XY coordinate locations from the zone 51 FIA data table to get the pixel values from the spectral data stack and the stratification raster layer at each subplot. Add those pixel values to the zone 51 FIA data table.

    Data sources used in this process:

    • spectral_data_stack
    • Strata_Mask
    • z51_FIA_subplots

    Date: 16-Mar-2009 (process 5 of 5)
    Produce a raster data layer by means of k-Nearest Neighbor classification. Preliminary tests were run to find the best k value for each strata (Table 3). Using those k values, an identity weight matrix, and the 'Modified Date Strata, 4 Strata' raster as the stratification, kNN classification was performed. A minimum horizontal search radius was implemented so that nearest neighbors could not be selected among subplots from the same FIA plot.

    Table 2: Strata k Values
    Strata k Value
    Stratum 1 31
    Stratum 2 18
    Stratum 3 32
    Stratum 4 32

    Data sources used in this process:

    • spectral_data_stack
    • z51_FIA_subplots
    • Strata_Mask

  3. What similar or related data should the user be aware of?

How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?

    Classification accuracy of forest type group is tested by building a confusion matrix to find user's, producer's and overall accuracy and by calculating the kappa coefficient value. These attribute accuracy tests were performed on March 24, 2009 using R: A language and environment for statistical computing and the R package nnDiag. For accuracy assessment results see the report NaFIS Core Forest Attribute Data: Forest Type Group, MRLC Zone 51 Attribute Accuracy.

  2. How accurate are the geographic locations?

    Horizontal positional accuracy of this data is unknown.

  3. How accurate are the heights or depths?

  4. Where are the gaps in the data? What is missing?

    Every pixel in the raster data layer within MRLC Zone 51 has been classified with a forest type group.

  5. How consistent are the relationships among the observations, including topology?

    Data set is in raster format. The data is believed to be logically consistent, though no tests were performed.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?

Access_Constraints: None
Use_Constraints:
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.

  1. Who distributes the data set? (Distributor 1 of 1)

    Brian Walters
    Michigan State University
    126 Natural Resources Building
    East Lansing, Michigan 48824
    United States

    517-432-3537 (voice)

  2. What's the catalog number I need to order this data set?

  3. What legal disclaimers am I supposed to read?

    This data file and accompanying documentation are provided "as is" without any warranty whatsoever by the principal investigators, co-principal investigators, collaborators, sponsors, and academic institutions involved in the Nationwide Forest Imputation Study, hereinafter called "NaFIS." Extensive effort has been made to produce accurate and complete data, however all geographic information has limitations due to scale, resolution, date, and interpretation of the original source materials. Users should consult the available metadata for this particular data to determine limitations. The burden for determining fitness of use lies entirely with the user. NaFIS shall not be held liable for improper or incorrect use of this data. Although this data has been processed successfully on a computer system at Michigan State University, no warranty, expressed or implied, is made by Michigan State University or NaFIS regarding the utility of the data on any other system, nor shall the act of distribution constitute any such warranty.

  4. How can I download or order the data?

  5. What hardware or software do I need in order to use the data set?

    To view this data a GIS data viewer must be installed that supports the ERDAS Imagine image format.

Who wrote the metadata?

Dates:
Last modified: 20-Mar-2009
Metadata author:
Brian Walters
Michigan State University
126 Natural Resources Building
East Lansing, Michigan 48824
United States

517-432-3537 (voice)

Metadata standard:
FGDC Content Standards for Digital Geospatial Metadata (FGDC-STD-001-1998)

Generated by mp version 2.9.8 on Tue Mar 24 14:17:42 2009