Raster surfaces created from the cost-effective mapping of longleaf extent and condition using NAIP imagery and FIA data project

Metadata:
Identification_Information:
Citation:
Citation_Information:
Originator: Hogland, John S.
Originator: St. Peter, Joseph R.
Originator: Anderson, Nathaniel M.
Publication_Date: 2017
Title:
Raster surfaces created from the cost-effective mapping of longleaf extent and condition using NAIP imagery and FIA data project
Geospatial_Data_Presentation_Form: raster digital data
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: Forest Service Research Data Archive
Online_Linkage: https://doi.org/10.2737/RDS-2017-0014
Description:
Abstract:
This data publication contains twenty-four GeoTIFF files for four significant geographic areas (SGAs) in Alabama, Florida, and Georgia. The extent of the SGAs are defined within the America’s Longleaf Range-wide Conservation Plan for Longleaf (2009). A raster grid file is provided for the extent of each SGA within each state and shows the amount of pine basal area per acre (BAA), the amount of all species BAA, the amount of pine trees per acre (TPA), the amount of all species TPA, dominant forest type classification, visually identified classification, the probability of an area being composed primarily of longleaf pine BAA, and the probability of an area being composed primarily of regeneration. These raster surfaces were created using machine learning relationships between FIA plot information (2010-2015) and NAIP imagery (2013) and are intended to be used to help quantify existing conditions of forested ecosystems and help prioritize longleaf restoration efforts across the four SGAs.
Purpose:
Intended use for these datasets include: helping quantify existing conditions of forested ecosystems and helping to prioritize Longleaf restoration efforts across four significant geographic areas described in America’s Longleaf Range-wide Conservation Plan for Longleaf (2009).
Supplemental_Information:
Original metadata date is 03/06/2017. Minor metadata updates made on 9/14/2018, 07/02/2019, and 09/16/2024.
Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2013
Currentness_Reference:
Ground condition
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None planned
Spatial_Domain:
Description_of_Geographic_Extent:
Significant geographic areas (SGAs) in the southern portions of Alabama, Florida, and Georgia
Bounding_Coordinates:
West_Bounding_Coordinate: -88.22
East_Bounding_Coordinate: -81.60
North_Bounding_Coordinate: 32.11
South_Bounding_Coordinate: 29.91
Keywords:
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: biota
Theme:
Theme_Keyword_Thesaurus: National Research & Development Taxonomy
Theme_Keyword: Forest & Plant Health
Theme_Keyword: Inventory, Monitoring, & Analysis
Theme_Keyword: Natural Resource Management & Use
Theme_Keyword: Wildlife (or Fauna)
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: Longleaf
Theme_Keyword: mapping
Theme_Keyword: restoration
Theme_Keyword: prioritization
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: Alabama
Place_Keyword: Florida
Place_Keyword: Georgia
Taxonomy:
Keywords/Taxon:
Taxonomic_Keyword_Thesaurus:
None
Taxonomic_Keywords: multiple species
Taxonomic_Keywords: plants
Taxonomic_System:
Classification_System/Authority:
Classification_System_Citation:
Citation_Information:
Originator: ITIS
Publication_Date: 2017
Title:
Integrated Taxonomic Information System
Geospatial_Data_Presentation_Form: database
Other_Citation_Details:
Retrieved [February, 21, 2017]
Online_Linkage: https://www.itis.gov
Taxonomic_Procedures:
Taxonomic_Classification:
Taxon_Rank_Name: Kingdom
Taxon_Rank_Value: Plantae
Applicable_Common_Name: plantes
Applicable_Common_Name: Planta
Applicable_Common_Name: Vegetal
Applicable_Common_Name: plants
Taxonomic_Classification:
Taxon_Rank_Name: Subkingdom
Taxon_Rank_Value: Viridiplantae
Taxonomic_Classification:
Taxon_Rank_Name: Infrakingdom
Taxon_Rank_Value: Streptophyta
Applicable_Common_Name: land plants
Taxonomic_Classification:
Taxon_Rank_Name: Superdivision
Taxon_Rank_Value: Embryophyta
Taxonomic_Classification:
Taxon_Rank_Name: Division
Taxon_Rank_Value: Tracheophyta
Applicable_Common_Name: vascular plants
Applicable_Common_Name: tracheophytes
Taxonomic_Classification:
Taxon_Rank_Name: Subdivision
Taxon_Rank_Value: Spermatophytina
Applicable_Common_Name: spermatophytes
Applicable_Common_Name: seed plants
Applicable_Common_Name: phanérogames
Taxonomic_Classification:
Taxon_Rank_Name: Class
Taxon_Rank_Value: Pinopsida
Applicable_Common_Name: conifers
Taxonomic_Classification:
Taxon_Rank_Name: Subclass
Taxon_Rank_Value: Pinidae
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Pinales
Applicable_Common_Name: pines
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Pinaceae
Applicable_Common_Name: pines
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Pinus
Applicable_Common_Name: pine
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Pinus palustris
Applicable_Common_Name: longleaf pine
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:

Hogland, John S.; St. Peter, Joseph R.; Anderson, Nathaniel M. 2017. Raster surfaces created from the longleaf mapping project. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2017-0014
Data_Set_Credit:
This project was funded by USDA Forest Service, Rocky Mountain Research Station; National Fish and Wildlife Foundation; and the Southern Company.
Cross_Reference:
Citation_Information:
Originator: Regional Working Group for America’s Longleaf
Publication_Date: 2009
Title:
America’s longleaf range-wide conservation plan for longleaf
Geospatial_Data_Presentation_Form: document
Other_Citation_Details:
Last accessed 5/12/2015
Online_Linkage: http://www.americaslongleaf.org/media/86/conservation_plan.pdf
Cross_Reference:
Citation_Information:
Originator: Hogland, John S.
Originator: St. Peter, Joseph R.
Originator: Anderson, Nathaniel M.
Publication_Date: 2018
Title:
Raster surfaces created from the mapping of longleaf extent and condition using Landsat and FIA data project
Geospatial_Data_Presentation_Form: raster digital data
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: Forest Service Research Data Archive
Online_Linkage: https://doi.org/10.2737/RDS-2018-0039
Analytical_Tool:
Analytical_Tool_Description:
The RMRS Raster Utility is an object oriented coding library that facilitates a wide range of spatial and statistical analysis using a newly developed Function Modeling framework. The library focuses on significantly reducing processing time and storage space associated with analyzing large datasets and has an easy to use graphical user interface, packaged as an ESRI add-in toolbar.

The RMRS Raster Utility toolbar plugs directly into ESRI’s ArcMap and provides quick access to a variety of tools that streamline and simplify Data Acquisition, Sampling, Raster Analysis and Statistical Modeling.

Hogland, John S.; Anderson, Nathaniel M. 2014. Improved analyses using function datasets and statistical modeling. In: Proceedings of the 2014 ESRI Users Conference; July 14-18, 2014, San Diego, CA. Redlands, CA: Environmental Systems Research Institute. https://research.fs.usda.gov/treesearch/46334
Tool_Access_Information:
Online_Linkage: https://research.fs.usda.gov/rmrs/products/dataandtools/tools/rmrs-raster-utility
Tool_Access_Instructions:
See website listed above.
Tool_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: John Hogland
Contact_Organization: USDA Forest Service, Rocky Mountain Research Station
Contact_Position: Biological Scientist
Contact_Address:
Address_Type: mailing and physical
Address: Rocky Mountain Research Station
Address: 800 East Beckwith
City: Missoula
State_or_Province: MT
Postal_Code: 59801
Country: USA
Contact_Voice_Telephone: 406-329-2138
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.
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Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
See individual raster dataset metadata.
Logical_Consistency_Report:
Visually identified classes, FIA field plots, and NAIP imagery were used to create the raster surfaces. Estimates of classification accuracy, model error, and strength of relationships can be found within the metadata of each surface.
Completeness_Report:
Complete
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Originator: USDA Farm Service Agency
Publication_Date: Unknown
Title:
National Agriculture Imagery Program imagery
Geospatial_Data_Presentation_Form: raster digital data
Online_Linkage: https://www.fsa.usda.gov/programs-and-services/aerial-photography/imagery-programs/naip-imagery/
Type_of_Source_Media: online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2013
Source_Currentness_Reference:
ground condition
Source_Citation_Abbreviation:
NAIP
Source_Contribution:
2013 color infrared NAIP imagery was acquired from apfo ftp site: ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/NAIP/.
Source_Information:
Source_Citation:
Citation_Information:
Originator: USDA Forest Service, Forest Inventory and Analysis Program
Publication_Date: Unknown
Title:
FIA plot data
Geospatial_Data_Presentation_Form: raster digital data
Online_Linkage: https://research.fs.usda.gov/programs/fia#data-and-tools
Type_of_Source_Media: online
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 2010
Ending_Date: 2013
Source_Currentness_Reference:
ground condition
Source_Citation_Abbreviation:
FIA
Source_Contribution:
2010-2013 FIA plot data summaries were used to relate spectral data to field measurements.
Process_Step:
Process_Description:
These datasets were built using FIA plot data and NAIP imagery. Plot data were summarized using the RMRS Raster Utility. Statistical and machine learning relationships were built using the RMRS Raster Utility. Outputs estimate plot summaries given the spectral and textural values of the NAIP imagery. For more information on processing steps please contact the author John Hogland, who can provide more details until the project final report is published.

BASAL AREA PER ACRE (BAA)
BAA are calculated from FIA plot measurements for trees greater than 1 inch in diameter. Given the FIA plot protocol, trees less than 5 inches in diameter are measured less intensively than trees greater than 5 inches. To address this discrepancy per acre estimates were used and related to NAIP texture and derived outputs at the spatial resolution of the FIA plot.

RENERATION (Regen)
The regen model identifies which plots are primarily composed of trees less than 5 inches in diameter. Regen plots are identified as forested areas with less than 20 TPA larger than 5 inches in diameter and more than 300 TPA of trees less than 5 inches in diameter. Overall map accuracy for a most likely classification rule is 94% (Florida), 95% (Alabama), and 90% (Georgia). However, regen plots were relatively infrequent and a most likely class is not necessarily the best way to determine if a given pixel’s TPA plot composition is composed of primarily regen. The raster dataset contains one band depicting the probability of a given location being composed primarily of trees less than 5 inches in diameter.

TREES PER ACRE (TPA)
TPA are calculated from FIA plot measurements for trees greater than or equal to 5 inches in diameter. Per acre estimates were used and related to NAIP texture and derived outputs at the spatial resolution of the FIA plot.

LONGLEAF DOMINANT (LongDom)
Longleaf Dominant models identify areas that the FIA plot’s BAA composition is composed primarily of Longleaf pine trees. The raster output from these models are a single band identifying the probability that a given plots BAA composition comes primarily from Longleaf pine. Most likely class rule accuracy ranges from 92% - 97%. However, longleaf plots were relatively infrequent and a most likely class is not necessarily the best way to determine if a given pixel’s TPA plot composition is composed of primarily Longleaf pine BAA. The raster dataset contains one band depicting the probability of a given location being composed primarily of Longleaf BAA.

L1
L1 models represent a basic classification at the pixel level that identify visually unique characteristics in the imagery. The probabilistic outputs from these models are used in subsequent models as predictive variables. The outputs from the L1 classification can be used to extract multiple characteristics from the landscape. Map accuracies for each state’s most likely class vary from 54% to 58% with the majority of errors occurring between shadows, grey, pink, and red canopy classes.

DOMINANT FOREST TYPES (DomType)
Dominant forest types are based on the maximum BAA for species grouping found at each FIA plot. Species groupings consist of Pine, Hardwood, and non-forested area. Explanatory variables for these models include mean, standard deviation, and GLCM contrast for each of the 6 principal components. Overall map accuracy for a most likely classification rule is 70% (Florida), 73% (Alabama), and 82% (Georgia) with the majority of misclassifications occurring between Pine and Hardwood categories (table below).While a most likely rule will identify each pixel’s plot composition as belonging to a give class it may not be the best way to determine the dominant forest type of a given plot.
Source_Used_Citation_Abbreviation:
NAIP
Source_Used_Citation_Abbreviation:
FIA
Process_Date: 2016
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Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Raster
Raster_Object_Information:
Raster_Object_Type: Grid Cell
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Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Geographic:
Latitude_Resolution: 0
Longitude_Resolution: 0
Geographic_Coordinate_Units: Decimal degrees
Geodetic_Model:
Horizontal_Datum_Name: North American Datum of 1983
Ellipsoid_Name: Geodetic Reference System 80
Semi-major_Axis: 6378137
Denominator_of_Flattening_Ratio: 298.25722210088
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Entity_and_Attribute_Information:
Overview_Description:
Entity_and_Attribute_Overview:
This data publication contains eight GeoTIFF files for each of the following states: Alabama (*=AL), Florida (*=FL), and Georgia (*=GA). Below you will find a description of these files.

\Data\*_AllBAA.tif: GeoTiff (and associated files, including XML metadata file) containing the amount of all species basal area per acre (BAA) in the specified state.

\Data\*_AllTPA.tif: GeoTiff (and associated files, including XML metadata file) containing the amount of all species TPA in the specified state.

\Data\*_DomType.tif: GeoTiff (and associated files, including XML metadata file) containing dominant forest type classification in the specified state.

\Data\*_L1.tif: GeoTiff (and associated files, including XML metadata file) containing the visually identified classification in the specified state.

\Data\*_LongDom.tif: GeoTiff (and associated files, including XML metadata file) containing the probability of an area being composed primarily of longleaf pine BAA in the specified state.

\Data\*_PineBAA.tif: GeoTiff (and associated files, including XML metadata file) containing the amount of pine BAA in the specified state.

\Data\*_PineTPA.tif: GeoTiff (and associated files, including XML metadata file) containing the amount of pine TPA in the specified state.

\Data\*_Regen.tif: GeoTiff (and associated files, including XML metadata file) containing the probability of an area being composed primarily of regeneration in the specified state.
Entity_and_Attribute_Detail_Citation:
Contact the author John Hogland, who can provide more details until the project final report is published.
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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 September 2024. For current information see Contact Us page on: https://doi.org/10.2737/RDS.
Resource_Description: RDS-2017-0014
Distribution_Liability:
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: TIFF
Format_Version_Number: see Format Specification
Format_Specification:
GeoTIFF (and associated files)
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.2737/RDS-2017-0014
Fees: None
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Metadata_Reference_Information:
Metadata_Date: 20240916
Metadata_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: John Hogland
Contact_Organization: USDA Forest Service, Rocky Mountain Research Station
Contact_Position: Biological Scientist
Contact_Address:
Address_Type: mailing and physical
Address: Rocky Mountain Research Station
Address: 800 East Beckwith
City: Missoula
State_or_Province: MT
Postal_Code: 59801
Country: USA
Contact_Voice_Telephone: 406-329-2138
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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