2006 Ventenata dubia distribution in the Blue Mountains Ecoregion of Oregon, Washington, and Idaho - probability

Metadata:
Identification_Information:
Citation:
Citation_Information:
Originator: Nietupski, Ty C.
Originator: Kerns, Becky K.
Publication_Date: 2023
Title:
2006 Ventenata dubia distribution in the Blue Mountains Ecoregion of Oregon, Washington, and Idaho - probability
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-2022-0010
Description:
Abstract:
This data publication contains two (2) georeferenced raster (GeoTIFF) files representing the 2006 probability and probability classes of Ventenata dubia (ventenata) presence throughout the Blue Mountains Ecoregion located within Oregon, Washington, and Idaho. The Blue Mountains Ecoregion is part of the Environmental Protection Agency (EPA) Level III Ecoregion classification (https://www.epa.gov/eco-research/ecoregions). Presence of ventenata in these data was defined based on field observations of aerial cover, where 20% and greater cover was classified as presence and less than 20% cover was classified as absence. Thus, the probability and probability classes of ventenata presence corresponds to populations with greater than or equal to 20% cover (not individual ventenata plants). Field observations were aggregated from sources including the United States Department of Agriculture (USDA), Forest Service; the Bureau of Land Management (BLM); and Oregon State University (OSU). Ventenata was mapped using the random forests classification method with land surface phenology, climate, soils, and terrain attributes. The 2006 prediction of ventenata was produced from a model trained from land surface phenology in 2017. To improve model transferability, 2006 was chosen based on climatic similarity as measured by a drought severity index and RAWs weather station data. The model was used to determine a probability threshold that is optimal for differentiating both presence and absence (Threshold = 0.58). This threshold was used to split the probability gradient into 6 classes, 2 classes below the threshold and 4 above.
Purpose:
The 2006 ventenata distribution was developed to assess the extent and patterns of invasion within the heart of ventenata’s invaded range. Ventenata has been observed throughout the Blue Mountains Ecoregion, but no spatial product was available to indicate areas of infestation or total invaded area for management and policy decisions. These data have been applied to assess contemporary habitat associations, locations of ventenata populations, and the spread of ventenata over time.
Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2006
Currentness_Reference:
Publication date
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None planned
Spatial_Domain:
Description_of_Geographic_Extent:
The Blue Mountains Ecoregion, as defined by the U.S. EPA Level III Ecoregions (https://www.epa.gov/eco-research/ecoregions), is a complex of mountains, valleys, and plateaus that covers approximately 71,000 square kilometers (km²) of the interior Pacific Northwest. This region covers parts of the states of Oregon, Washington, and Idaho. The Cascade Mountains border this region to the west and the Rocky Mountains to the east. Grasslands are most common in the north while shrublands, dominated by sagebrush (Artemisia spp.) and Western juniper (Juniperus occidentalis) woodlands, are more common in the south. Much of the region is forested by ponderosa pine (Pinus ponderosa), dry and moist mixed conifer, and subalpine forests.
Bounding_Coordinates:
West_Bounding_Coordinate: -122.04092
East_Bounding_Coordinate: -115.63740
North_Bounding_Coordinate: 46.54461
South_Bounding_Coordinate: 43.15080
Keywords:
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: Ventenata dubia
Theme_Keyword: land surface phenology
Theme_Keyword: mapping
Theme_Keyword: invasive annual grass
Theme_Keyword: species distribution modelling
Theme_Keyword: remote sensing
Theme_Keyword: Landsat
Theme_Keyword: MODIS
Theme_Keyword: time series
Theme_Keyword: Joint Fire Science Program
Theme_Keyword: JFSP
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: biota
Theme_Keyword: imageryBaseMapsEarthCover
Theme:
Theme_Keyword_Thesaurus: National Research & Development Taxonomy
Theme_Keyword: Ecology, Ecosystems, & Environment
Theme_Keyword: Geography
Theme_Keyword: Ecology
Theme_Keyword: Plant ecology
Theme_Keyword: Forest & Plant Health
Theme_Keyword: Invasive species
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: Blue Mountains Ecoregion
Place_Keyword: Oregon
Place_Keyword: Washington
Place_Keyword: Idaho
Place_Keyword: Umatilla National Forest
Place_Keyword: Malheur National Forest
Place_Keyword: Wallowa-Whitman National Forest
Place_Keyword: Payette National Forest
Taxonomy:
Keywords/Taxon:
Taxonomic_Keyword_Thesaurus:
None
Taxonomic_Keywords: single species
Taxonomic_Keywords: plants
Taxonomic_Keywords: vegetation
Taxonomic_System:
Classification_System/Authority:
Classification_System_Citation:
Citation_Information:
Originator: ITIS
Publication_Date: 2021
Title:
Integrated Taxonomic Information System
Geospatial_Data_Presentation_Form: on-line database
Other_Citation_Details:
Retrieved [December, 16, 2021]; CC0
Online_Linkage: https://www.itis.gov
Online_Linkage: https://doi.org/10.5066/F7KH0KBK
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
Applicable_Common_Name: green plants
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: Magnoliopsida
Taxonomic_Classification:
Taxon_Rank_Name: Superorder
Taxon_Rank_Value: Lilianae
Applicable_Common_Name: monocots
Applicable_Common_Name: monocotyledons
Applicable_Common_Name: monocotylédones
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Poales
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Poaceae
Applicable_Common_Name: grasses
Applicable_Common_Name: graminées
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Ventenata
Applicable_Common_Name: North Africa grass
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Ventenata dubia
Applicable_Common_Name: North Africa grass
Applicable_Common_Name: ventenata
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:

Nietupski, Ty C.; Becky K. 2023. 2006 Ventenata dubia distribution in the Blue Mountains Ecoregion of Oregon, Washington, and Idaho - probability. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2022-0010
Point_of_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Becky K. Kerns
Contact_Organization: USDA Forest Service, Pacific Northwest Research Station
Contact_Position: Research Ecologist
Contact_Address:
Address_Type: mailing and physical
Address: 3200 SW Jefferson Way
City: Corvallis
State_or_Province: OR
Postal_Code: 97331-8550
Country: USA
Contact_Voice_Telephone: 541-750-7497
Contact_Electronic_Mail_Address: becky.kerns@usda.gov
Data_Set_Credit:
Funding for this project provided by Joint Fire Science Program (JFSP # 16-1-01-21): https://www.firescience.gov. USDA Forest Service, Pacific Northwest Research Station and Rocky Mountain Research Station also provided some salary funds.


Author Information:

Ty C. Nietupski
Oregon State University
https://orcid.org/0000-0003-0248-5753

Becky K. Kerns
USDA Forest Service, Pacific Northwest Research Station
https://orcid.org/0000-0003-4613-2191
Native_Data_Set_Environment:
Arch Linux; QGIS 3.22; Google Earth Engine
Cross_Reference:
Citation_Information:
Originator: Lemons, Rebecca E.
Originator: Dye, Alex W.
Originator: Kerns, Becky K.
Publication_Date: 2021
Title:
Ecosystem change in the Blue Mountains Ecoregion: Exotic invaders, shifts in fuel structure, and management implications
Geospatial_Data_Presentation_Form: document
Series_Information:
Series_Name: Joint Fire Science Program Final Report
Issue_Identification: JFSP # 16-1-01-21
Other_Citation_Details:
(Report is included in full data publication download: \Supplements\16-1-01-21_final_report.pdf.)
Online_Linkage: https://www.firescience.gov/projects/16-1-01-21/project/16-1-01-21_final_report.pdf
Cross_Reference:
Citation_Information:
Originator: Nietupski, Ty C.
Originator: Kennedy, Robert E.
Originator: Temesgen, Hailemariam
Originator: Kerns, Becky K.
Publication_Date: 2021
Title:
Spatiotemporal image fusion in Google Earth Engine for annual estimates of land surface phenology in a heterogenous landscape
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: International Journal of Applied Earth Observation and Geoinformation
Issue_Identification: 99: 102323
Online_Linkage: https://doi.org/10.1016/j.jag.2021.102323
Online_Linkage: https://www.fs.usda.gov/treesearch/pubs/63024
Cross_Reference:
Citation_Information:
Originator: Nietupski, Ty C.
Publication_Date: 2021
Title:
Characterizing an annual grass invasion and its link to environmental and disturbance factors using remote sensing: new tools and applications
Geospatial_Data_Presentation_Form: document
Series_Information:
Series_Name: Ph.D. Dissertation
Publication_Information:
Publication_Place: Corvallis, OR
Publisher: Oregon State University
Other_Citation_Details:
(Included in data publication download: \Supplements\NietupskiTyC2021.pdf)
Online_Linkage: https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/3n2046091
Cross_Reference:
Citation_Information:
Originator: Nietupski, Ty C.
Originator: Temesgen, Hailermariam
Originator: Kerns, Becky K.
Publication_Date: Unknown
Title:
Differentiating an invasive annual grass species with land surface phenology and environmental conditions in the northwestern US: Mapping Ventenata dubia
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Biological Invasions
Other_Citation_Details:
[In review]
Cross_Reference:
Citation_Information:
Originator: Nietupski, Ty C.
Originator: Kerns, Becky K.
Publication_Date: 2023
Title:
2017 Ventenata dubia distribution in the Blue Mountains Ecoregion of Oregon, Washington, and Idaho - probability
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-2022-0011
Analytical_Tool:
Analytical_Tool_Description:
GEE-Image-Fusion: scripts that can be used to automate large image fusion tasks in the Google Earth Engine (GEE).
Tool_Access_Information:
Online_Linkage: https://github.com/tytupski/GEE-Image-Fusion
Tool_Access_Instructions:
See webpage for details.
Tool_Citation:
Citation_Information:
Originator: Nietupski, Ty C.
Publication_Date: 2021
Title:
GoogleEarthEngine_ImageFusion
Geospatial_Data_Presentation_Form: software (code; algorithm)
Publication_Information:
Publisher: Mendeley Data
Online_Linkage: https://doi.org/10.17632/bcbptkrbsg.1
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Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
The accuracy of the model was assessed using 10-fold cross-validation (AUC-89; Accuracy-0.9; Sensitivity-0.54; Specificity-0.94).

Additional information can be found in Nietupski's dissertation (2021).

Nietupski, Ty C. 2021. Characterizing an annual grass invasion and its link to environmental and disturbance factors using remote sensing: new tools and applications. Ph.D. Dissertation. Oregon State University. https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/3n2046091
Logical_Consistency_Report:
The product was examined by local experts with on-the-ground knowledge of the distribution and occurrence of ventenata. Verbal confirmation of the occurrence of this species in certain parts of the ecoregion also supports the logical consistency of this product.
Completeness_Report:
The product was examined to ensure that valid data were present at all relevant locations. Areas unsuitable to ventenata within the region's boundary are masked. These areas were masked because of high conifer canopy cover, perennial water, or high elevation (> 6000 ft).

\Data\vedu_2006_class.tif: Areas with masked values are represented by the value 255.
\Data\vedu_pa_2006.tif: Areas with masked values are represented by the value -9999.
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Originator: Masek, Jeffrey G.
Originator: Vermote, Eric F.
Originator: Saleous, Nazmi E.
Originator: Wolfe, Robert E.
Originator: Hall, Forrest G.
Originator: Huemmrich, Karl F.
Originator: Gao, Feng
Originator: Kutler, J.
Originator: Lim, Teng-Kui
Publication_Date: 2006
Title:
A Landsat surface reflectance dataset for North America, 1990–2000
Geospatial_Data_Presentation_Form: raster digital data
Series_Information:
Series_Name: IEEE Geoscience and Remote Sensing Letters
Issue_Identification: 3(1): 68-72
Other_Citation_Details:
Accessed at URL code.earthengine.google.com
Online_Linkage: https://doi.org/10.1109/LGRS.2005.857030
Type_of_Source_Media: Online
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 2005
Ending_Date: 2007
Source_Currentness_Reference:
Publication Date
Source_Citation_Abbreviation:
Landsat 5
Source_Contribution:
The Landsat 5 satellite, launched in 1984, contains the Thematic Mapper (TM) multispectral sensor that collects observations of the earth's surface at an approximately 16-day interval at 30-meter (m) resolution. The Landat 5 Collection 1 data is processed to surface reflectance with the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS). Bands 4 and 3 were used in this analysis.
Source_Information:
Source_Citation:
Citation_Information:
Originator: Schaaf, Crystal
Originator: Wang, Zhuosen
Publication_Date: 2015
Title:
MCD43A4 MODIS/Terra+Aqua Nadir BRDF-Adjusted Reflectance Daily L3 Global - 500m
Geospatial_Data_Presentation_Form: raster digital data
Publication_Information:
Publication_Place: Greenbelt, MD
Publisher: NASA LP DAAC
Other_Citation_Details:
Accessed at URL code.earthengine.google.com
Online_Linkage: https://doi.org/10.5067/MODIS/MCD43A4.006
Type_of_Source_Media: Online
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 2005
Ending_Date: 2007
Source_Currentness_Reference:
Publication Date
Source_Citation_Abbreviation:
MODIS (MCD43A4v006)
Source_Contribution:
The Moderate Resolution Imaging Spectroradiometer (MODIS) is a multispectral sensor carried by the Terra and Aqua satellites. The satellites provide daily observations of the earth's surface at resolutions ranging from 250 meters (m) to 1 km. The data from these two satellites are processed to surface reflectance at a nadir viewing angle using the bidirectional reflectance distribution function derived from a 16-day moving window of MODIS images. Bands 1 and 2 were used in this analysis.
Source_Information:
Source_Citation:
Citation_Information:
Originator: U.S. Geological Survey
Publication_Date: 2002
Title:
National Elevation Dataset
Geospatial_Data_Presentation_Form: raster digital data
Publication_Information:
Publication_Place: Reston, VA
Publisher: U.S. Geological Survey
Other_Citation_Details:
Accessed June 2, 2020 at URL code.earthengine.google.com
Online_Linkage: https://www.usgs.gov/programs/national-geospatial-program/national-map
Type_of_Source_Media: Online
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: Unknown
Ending_Date: Unknown
Source_Currentness_Reference:
Publication Date
Source_Citation_Abbreviation:
USGS NED
Source_Contribution:
The National Elevation Dataset (NED) is the best available raster elevation data of the conterminous United States. The NED is derived from diverse source data that are processed to a common coordinate system and unit of vertical measure (meters). These data were obtained from Google Earth Engine, which sources the data directly from the USGS.

Terrain attributes were generated from the National Elevational Dataset (NED; https://www.sciencebase.gov/catalog/item/4f4e48b1e4b07f02db530759).
Source_Information:
Source_Citation:
Citation_Information:
Originator: PRISM Climate Group
Publication_Date: 2012
Title:
PRISM
Geospatial_Data_Presentation_Form: tabular digital data
Publication_Information:
Publication_Place: Corvallis, OR
Publisher: Oregon State University
Online_Linkage: https://prism.oregonstate.edu/normals/
Type_of_Source_Media: Online
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 1981
Ending_Date: 2010
Source_Currentness_Reference:
Publication Date
Source_Citation_Abbreviation:
PRISM Norm81
Source_Contribution:
The Parameter-elevation Relationships on Independent Slopes Model (PRISM) Norm81 data are 30-year averages of climate conditions spanning the 1981-2010 period. Climate variables are spatially interpolated across the conterminous United States from weather station data using a digital elevation model. Variables used from these data include temperature, precipitation, and vapor pressure deficit.
Source_Information:
Source_Citation:
Citation_Information:
Originator: Soil Survey Staff
Publication_Date: 2022
Title:
Gridded soil survey geographic (gSSURGO) database for the conterminous United States
Geospatial_Data_Presentation_Form: raster digital data
Publication_Information:
Publication_Place: Lincoln, NE
Publisher: United States Department of Agriculture, Natural Resources Conservation Service
Online_Linkage: https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/geo/?cid=nrcs142p2_053628
Type_of_Source_Media: Online
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: Unknown
Ending_Date: Unknown
Source_Currentness_Reference:
Publication Date
Source_Citation_Abbreviation:
gSSURGO
Source_Contribution:
The gridded Soil Survey Geographic (gSSURGO) Database is a version of the SSURGO dataset that has been transformed into a grid format. The SSURGO dataset contains information about soil properties that were collected as part of the National Cooperative Soil Survey. Soil properties included in the analysis from this dataset include texture information from the top 20 centimeters (cm) of the soil profile.
Process_Step:
Process_Description:
Field observations of ventenata aerial cover were gathered and aggregated from governmental and academic partners including the USDA Forest Service, Bureau of Land Management, and Oregon State University (data obtained from the latter 2 is not available due to privacy concerns, please contact authors if interested in more information). These observations were categorized into presence and absence where plots with greater than or equal to 20% ventenata cover were classified as presence and anything below 20% was classified as absence. These observations were combined with land surface phenology (Landsat 8, MODIS; see details below), climate (PRISM), soils (gSSURGO), and terrain (NED) predictors in a random forests style machine learning model (Breiman 2001; Chen et al. 2016). The resulting model was used to predict the probability of ventenata presence (>= 20% cover) with a 30 m resolution raster stack of the predictor variables.

For ease of interpretation, probability was split into 6 classes representing the probability gradient in a simplified format. Two classes (Low and Med Low) are below the threshold that best distinguishes presence and absence (0.58) and represent areas that are not likely to contain ventenata. Four classes (Medium, Med High, High, Very High) are above the threshold that best distinguishes presence and absence and represent areas that are likely to contain ventenata.

The following are details related to the development of the land surface phenology predictors. Image processing methods included cloud and snow masking, spectral index calculation (NDVI, SWI), image co-registration, spatio-temporal image fusion, compositing, and time series smoothing. For additional details about the image processing used to create the lands surface phenology predictors please see Nietupski et al. (2021) and for code used in the image processing see https://github.com/tytupski/GEE-Image-Fusion.


Breiman, Leo. 2001. Random forests. Mach Learn 45: 5–32. https://doi.org/10.1023/A:1010933404324

Chen, Tianqi; Guestrin, Carlos E. 2016. XGBoost: A Scalable Tree Boosting System. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. San Francisco, CA, pp 785–794. https://doi.org/10.1145/2939672.2939785

Nietupski, Ty C. 2021. Characterizing an annual grass invasion and its link to environmental and disturbance factors using remote sensing: new tools and applications. Ph.D. Dissertation. Oregon State University. https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/3n2046091

Nietupski, Ty C.; Kennedy, Robert E.; Temesgen, Hailemariam; Kerns, Becky K. 2021. Spatiotemporal image fusion in Google Earth Engine for annual estimates of land surface phenology in a heterogenous landscape. International Journal of Applied Earth Observation and Geoinformation. 99: 102323. https://doi.org/10.1016/j.jag.2021.102323

Nietupski, Ty C.; Temesgen, Hailermariam; Kerns, Becky K. [In review]. Mapping the invasive annual grass ventenata (Ventenata dubia) in the northwestern United States. Biological Invasions.
Source_Used_Citation_Abbreviation:
Landsat 5; MODIS; USGS NED; PRISM; gSSURGO
Process_Date: 2020
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Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Raster
Raster_Object_Information:
Raster_Object_Type: Pixel
Row_Count: 9278
Column_Count: 15073
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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
Latitude_of_Projection_Origin: 23
False_Easting: 0
False_Northing: 0
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: Coordinate Pair
Coordinate_Representation:
Abscissa_Resolution: 30
Ordinate_Resolution: 30
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 detailed description of the files included in this data publication.

DATA FILES (2)

1. \Data\vedu_2006_class.tif: GeoTIFF raster file (and associated files: *.aux.xml, *.vat.cpg, and *.vat.dbf) representing probability classes of Ventenata dubia presence throughout the Blue Mountains Ecoregion in 2006.

Attributes:

OID = ID number automatically generated by Esri
Value = Probability class

PROB_CLASS = Ventenata presence (units: probability class on scale of 1 through 6)
1 = Low (< 0.35)
2 = Med Low (0.35 - 0.58)
3 = Medium (0.58-0.65)
4 = Med High (0.65 - 0.72)
5 = High (0.72 - 0.79)
6 = Very High (> 0.79)

RED = RGB colormap value
GREEN = RGB colormap value
BLUE = RGB colormap value
ALPHA = RGB colormap value
Count = Number of pixels in each probability class.


2. \Data\vedu_pa_2006.tif: GeoTIFF raster file (and associated files: *.aux.xml) representing probability of Ventenata dubia presence throughout the Blue Mountains Ecoregion in 2006. The data are represented by a single band digital raster file with a float32 data type. Units are measured in probability on a scale of 0 to 1.



SUPPLEMENTAL FILES (7)

1. \Supplements\16-1-01-21_final_report.pdf: Portable Document Format (PDF) file containing the 2021 Joint Fire Science Program Final Report for JFSP Project ID: 16-1-01-21, "Ecosystem change in the Blue Mountains Ecoregion: Exotic invaders, shifts in fuel structure, and management implications".

2. \Supplements\NietupskiTyC2021.pdf: PDF file containing the 2021 dissertation, "Characterizing an annual grass invasion and its link to environmental and disturbance factors using remote sensing: new tools and applications".

3. \Supplements\ArcGIS\vedu_prob_viridis.tif.lyr: Esri layer (LYR) file containing the symbology for displaying the ventenata probability classes in the probability raster in an ArcGIS environment.

4. \Supplements\QGIS\QGIS_README.txt: ASCII text (TXT) file containing a readme file for displaying probability classes via a GDAL raster attribute table in QGIS.

5. \Supplements\QGIS\vedu_class.mkv: Matroska multimedia container (MKV) file containing a video on how to display the probability classes for the ventenata probability classes raster via a GDAL raster attribute table in QGIS.

6. \Supplements\QGIS\vedu_prob.mkv: Matroska multimedia container (MKV) file containing a video on how to display the probability classes for the ventenata probability raster via a GDAL raster attribute table in QGIS.

7. \Supplements\QGIS\vedu_prob_bgyr.txt: TXT file containing a QGIS generated color map export file.
Entity_and_Attribute_Detail_Citation:
Lemons, Rebecca E.; Dye, Alex W.; Kerns, Becky K. 2021. Ecosystem change in the Blue Mountains Ecoregion: Exotic invaders, shifts in fuel structure, and management implications. Joint Fire Science Program Final Report: JFSP # 16-1-01-21. (Report is included in full data publication download: \Supplements\16-1-01-21_final_report.pdf.)

Nietupski, Ty C. 2021. Characterizing an annual grass invasion and its link to environmental and disturbance factors using remote sensing: new tools and applications. Ph.D. Dissertation. Oregon State University. https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/3n2046091
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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 2023. For current information see Contact Us page on: https://doi.org/10.2737/RDS.
Resource_Description: RDS-2022-0010
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:
Georeferenced (GeoTIFF) raster file
File_Decompression_Technique: Files zipped with 7-Zip 19.0
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.2737/RDS-2022-0010
Digital_Form:
Digital_Transfer_Information:
Format_Name: PDF
Format_Version_Number: see Format Specification
Format_Specification:
Portable Document Format file
File_Decompression_Technique: Files zipped with 7-Zip 19.0
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.2737/RDS-2022-0010
Digital_Form:
Digital_Transfer_Information:
Format_Name: ASCII
Format_Version_Number: see Format Specification
Format_Specification:
ASCII text file
File_Decompression_Technique: Files zipped with 7-Zip 19.0
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.2737/RDS-2022-0010
Digital_Form:
Digital_Transfer_Information:
Format_Name: MKV
Format_Version_Number: see Format Specification
Format_Specification:
Matroska multimedia container format
File_Decompression_Technique: Files zipped with 7-Zip 19.0
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.2737/RDS-2022-0010
Digital_Form:
Digital_Transfer_Information:
Format_Name: LYR
Format_Version_Number: see Format Specification
Format_Specification:
Esri layer file
File_Decompression_Technique: Files zipped with 7-Zip 19.0
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.2737/RDS-2022-0010
Fees: None
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Metadata_Reference_Information:
Metadata_Date: 20230120
Metadata_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Becky K. Kerns
Contact_Organization: USDA Forest Service, Pacific Northwest Research Station
Contact_Position: Research Ecologist
Contact_Address:
Address_Type: mailing and physical
Address: 3200 SW Jefferson Way
City: Corvallis
State_or_Province: OR
Postal_Code: 97331-8550
Country: USA
Contact_Voice_Telephone: 541-750-7497
Contact_Electronic_Mail_Address: becky.kerns@usda.gov
Metadata_Standard_Name: FGDC Content Standard for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998
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