Raster surfaces created from the mapping of longleaf extent and condition using Landsat 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: 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
Description:
Abstract:
This data publication contains nine GeoTIFF files for the Fort Stewart-Altamaha significant geographic area (SGA) in Georgia. The extent of the SGA is defined within the America’s Longleaf Range-wide Conservation Plan for Longleaf (2009). A raster grid file is provided for the extent of the SGA and shows the amount of pine basal area per acre (BAA), the amount of hardwood species BAA, the amount of pine trees per acre (TPA), the amount of hardwood species TPA, dominant forest type classification, the probability of an area being composed primarily of regeneration, the probability of longleaf pine being present in an area, a raster of pine species presence or absence and a raster of hardwood species presence or absence. These raster surfaces were created using machine learning relationships between USDA Forest Service, Forest Inventory and Analysis (FIA) plot information (2010-2015) and normalized Landsat imagery (2013-2015) 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 the Fort Stewart-Altamaha significant geographic areas described in America’s Longleaf Range-wide Conservation Plan for Longleaf (2009).
Supplemental_Information:
Data were originally published on 09/14/2018. Minor metadata updates made on 01/08/2020.
Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2015
Currentness_Reference:
Ground condition
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None planned
Spatial_Domain:
Description_of_Geographic_Extent:
Fort Stewart-Altamaha significant geographic area in Georgia
Bounding_Coordinates:
West_Bounding_Coordinate: -83.73000
East_Bounding_Coordinate: -80.94000
North_Bounding_Coordinate: 32.97000
South_Bounding_Coordinate: 31.25000
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 pine
Theme_Keyword: Pinus palustris
Theme_Keyword: mapping
Theme_Keyword: restoration
Theme_Keyword: prioritization
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: Georgia
Taxonomy:
Keywords/Taxon:
Taxonomic_Keyword_Thesaurus:
None
Taxonomic_Keywords: single species
Taxonomic_Keywords: plants
Taxonomic_System:
Classification_System/Authority:
Classification_System_Citation:
Citation_Information:
Originator: ITIS
Publication_Date: 2018
Title:
Integrated Taxonomic Information System
Geospatial_Data_Presentation_Form: database
Other_Citation_Details:
Retrieved [August, 13, 2018]
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. 2018. Raster surfaces created from the mapping of longleaf extent and condition using Landsat and FIA data project. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2018-0039
Point_of_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA Forest Service, Rocky Mountain Research Station
Contact_Person: John Hogland
Contact_Position: Biological Scientist
Contact_Address:
Address_Type: mailing and physical
Address: 800 East Beckwith
City: Missoula
State_or_Province: MT
Postal_Code: 59801
Country: USA
Contact_Voice_Telephone: 406-329-2138
Data_Set_Credit:
This project was funded by USDA Forest Service, Rocky Mountain Research Station and USDA Forest Service, State and Private Forestry.
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 02/06/2018
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: 2017
Title:
Raster surfaces created from the longleaf mapping 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
Cross_Reference:
Citation_Information:
Originator: Hogland, John S.
Originator: Anderson, Nathaniel M.
Originator: St. Peter, Joseph R.
Originator: Drake, Jason
Originator: Medley, Paul
Publication_Date: 2018
Title:
Mapping forest characteristics at fine resolution across large landscapes of the southeastern United States using NAIP imagery and FIA field plot data
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: ISPRS International Journal of Geo-Information
Issue_Identification: 7(4): 140
Online_Linkage: https://doi.org/10.3390/ijgi7040140
Online_Linkage: https://www.fs.usda.gov/treesearch/pubs/56140
Analytical_Tool:
Analytical_Tool_Description:
RMRS Raster Utility is an object oriented coding library that facilitates a wide range of spatial and statistical analysis using the newly developed Function Modeling (https://www.fs.fed.us/rm/raster-utility/function-modeling/) framework. This 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. For more information about the RMRS Raster Utility toolbar please refer to Hogland and Anderson 2017.
Tool_Access_Information:
Online_Linkage: https://www.fs.fed.us/rm/raster-utility/
Tool_Access_Instructions:
see URL
Tool_Citation:
Citation_Information:
Originator: Hogland, John
Originator: Anderson, Nathaniel
Publication_Date: 2017
Title:
Function modeling improves the efficiency of spatial modeling using big data from remote sensing
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Big Data and Cognitive Computing
Issue_Identification: 1: 1-14
Online_Linkage: https://doi.org/10.3390/bdcc1010003
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Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
See individual raster dataset metadata.
Logical_Consistency_Report:
FIA field plots and Landsat 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 Forest Service, Forest Inventory and Analysis
Publication_Date: 2016
Title:
FIA Database
Geospatial_Data_Presentation_Form: database
Publication_Information:
Publication_Place: St. Paul, MN
Publisher: U.S. Department of Agriculture, Forest Service, Northern Research Station
Other_Citation_Details:
(accessed on 28 March 2018)
Online_Linkage: https://apps.fs.usda.gov/fia/datamart/datamart.html
Type_of_Source_Media: Online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2015
Source_Currentness_Reference:
Ground Condition
Source_Citation_Abbreviation:
FIA plot data
Source_Contribution:
Actual plot location and field data were obtained through a data request from FIA and the FIA data mart. FIA tree data were summarized to the plot and used as response variables.

Also used:
Forest Inventory and Analysis Spatial Data Request [FIA SDR] Requesting Spatial Data, 2016. Available online: https://www.fia.fs.fed.us/tools-data/spatial/requests/index.php (accessed on 16 September 2016).
Source_Information:
Source_Citation:
Citation_Information:
Originator: United States Geological Survey
Publication_Date: 2015
Title:
Landsat 8
Geospatial_Data_Presentation_Form: raster digital data
Online_Linkage: https://landsat.usgs.gov/landsat-data-access
Source_Time_Period_of_Content:
Time_Period_Information:
Multiple_Dates/Times:
Single_Date/Time:
Calendar_Date: 2013
Single_Date/Time:
Calendar_Date: 2015
Source_Currentness_Reference:
Ground Condition
Source_Citation_Abbreviation:
Landsat imagery
Source_Contribution:
Base Landsat 8 imagery used in the analysis were acquired during the spring, fall, and winter seasons for 2013 and 2015.
Process_Step:
Process_Description:
These datasets were built using FIA plot data and Landsat imagery. Plot data were summarized using the RMRS Raster Utility. Statistical and machine learning relationships were built using the RMRS Raster Utility (Hogland and Anderson 2017). Outputs estimate plot summaries given the spectral and values of the Landsat 8 imagery. Additional details can be found in the metadata files associated with each GeoTIFF, or contact the author John Hogland who can provide specific details until the project final report is published.

NORMALIZED LANDSAT
Landsat 8 imagery was normalized using a series of steps that included Aggregate No-Change Regression image normalization (ANR; Hogland 2005). Reference scenes for each Landsat phenology type came from path/row 17/38. In the instance that substantial land use change had occurred due to difference in image acquisition additional spatial masks were used to remove pixels from the ANR procedure. Change percentages used in the normalization process ranged from < 20% to 40% >.

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 Landsat 8 imagery and derived outputs at the spatial resolution of the FIA plot.

REGENERATION (Regen)
The regen model identifies locations that 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. 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 Landsat 8 imagery and derived outputs at the spatial resolution of the FIA plot.

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 Needle leaf, Broad leaf, and non-forested areas. Explanatory variables for these models include mean, standard deviation, and GLCM contrast for each band within the Landsat imagery.

PRESENCE MODELS (B_Leaf, N_Leaf, L_Leaf)
Three presence models identify areas where the FIA plot’s BAA composition is greater than zero for the target tree species group; Broad leaf tree species (B_Leaf), needle leaf species (N_Leaf), and longleaf pine trees (L_Leaf). The raster output from these models are a single band identifying areas where the probability that a given plot contains the target species BAA > 0 at greater than 50% probability. Cells that met this criteria are given a value of 1, cells that do not are given a value of 0.

L2 MODELS (B_BAA, B_TPA, N_BAA, N_TPA)
L2 models represents BAA and TPA linear regression models calculated from FIA plot measurements for broad leaf, and needle leaf trees greater than 5 inch in diameter respectively. Normalized Landsat scenes for a leaf on spring growing, leaf on late summer season, and a leaf off winter season, from 2013-2015, were used as base predictive layers.


Hogland, John. 2005. Creating spatial probability distributions for longleaf pine ecosystems across east Mississippi, Alabama, the Panhandle of Florida and West Georgia. Thesis. Auburn, AL: Auburn University. https://hdl.handle.net/10415/603

Hogland, John; Anderson, Nathaniel. 2017. Function modeling improves the efficiency of spatial modeling using big data from remote sensing. Big Data Cognit. Comput. 1: 1–14. https://doi.org/10.3390/bdcc1010003
Process_Date: 2017
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Entity_and_Attribute_Information:
Overview_Description:
Entity_and_Attribute_Overview:
This data publication contains 9 GeoTIFF files. Below is a complete description of each. (See individual tif file metadata documents for more details.)


\Data\B_BAA.tif: GeoTIFF (and associated files, including XML metadata file) containing the amount of broad leaf tree species basal area per acre (BAA).

\Data\B_Leaf.tif: GeoTIFF (and associated files, including XML metadata file) containing the presence of broad leaf trees.

\Data\B_TPA.tif: GeoTIFF (and associated files, including XML metadata file) containing the amount of broad leaf tree species trees per acre (TPA).

\Data\DomType.tif: GeoTIFF (and associated files, including XML metadata file) containing the dominant forest type classification.

\Data\L_Leaf.tif: GeoTIFF (and associated files, including XML metadata file) containing the porbability of the presence of longleaf species trees.

\Data\N_BAA.tif: GeoTIFF (and associated files, including XML metadata file) containing the amount of needle leaf tree species basal area per acre (BAA).

\Data\N_Leaf.tif: GeoTIFF (and associated files, including XML metadata file) containing the presence of needle leaf trees.

\Data\N_TPA.tif: GeoTIFF (and associated files, including XML metadata file) containing the amount of needle leaf tree species trees per acre (TPA).

\Data\Regen.tif: GeoTiff (and associated files, including XML metadata file) containing the probability of an area being composed primarily of regeneration.
Entity_and_Attribute_Detail_Citation:
none provided
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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 January 2020. For current information see Contact Us page on: https://doi.org/10.2737/RDS.
Resource_Description: RDS-2018-0039
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, which is a tif file that includes additional spatial (georeferencing) information embedded in the tif file as tags.
File_Decompression_Technique: Files zipped with 7-Zip 18.05
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.2737/RDS-2018-0039
Fees: None
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Metadata_Reference_Information:
Metadata_Date: 20200108
Metadata_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA Forest Service, Rocky Mountain Research Station
Contact_Person: John Hogland
Contact_Position: Biological Scientist
Contact_Address:
Address_Type: mailing and physical
Address: 800 East Beckwith
City: Missoula
State_or_Province: MT
Postal_Code: 59801
Country: USA
Contact_Voice_Telephone: 406-329-2138
Metadata_Standard_Name: FGDC Content Standard for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998
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