Distribution of White Spruce in Alaska. An Open Access prediction surface from climatic and bioclimatic parameters using ESRI GRID formats.
Metadata also available as
Metadata:
- Identification_Information:
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- Citation:
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- Citation_Information:
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- Originator: Bettina Ohse
- Originator: Falk Huettmann
- Publication_Date: summer 2008
- Title:
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Distribution of White Spruce in Alaska. An Open Access prediction surface from climatic and bioclimatic parameters using ESRI GRID formats.
- Edition: no 1
- Series_Information:
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- Series_Name: Distribtion of Tree Species in Alaska
- Publication_Information:
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- Publisher: Bettina Ohse, Falk Huettmann, Steffi Ickert-Bond
- Online_Linkage: <http://science.nature.nps.gov/nrdata>
- Description:
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- Abstract:
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This open access data set contains a spatially gridded distribution of White Spruce in Alaska (ESRI GRID format), predicted from climatic and bioclimatic parameters (temperature, precipitation, elevation, and aspect). A species distribution model, developed by Bettina Ohse, was used to determine the ecological niche of the species based on the environmental variables. The model was developed within TreeNet, a classification and regression tree software. The ecological niche was then projected into geographical space, resulting in a predictive map of the species distribution in Alaska (4km resolution, tested accuracy of c. 95 %). We used ArcGIS 9.2. Data sources were freely available for the global public, and so were all tools used (prediction algorithms and specific GIS tools). We promote these data and this concept as a role model how to model plant distributions in wilderness areas and for overcoming data gaps in species distributions world-wide. We encourage the use and update of these data for further updating of this concept and its findings.
- Purpose:
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Display and/or analyses requiring spatially distributed occurrence of WHite Spruce in alaska. This dataset provides high resolution data that should serve researchers concerned with species biogeography, wildlife habitat, nature conservation planning, or natural resource management as a source of information and basis of further investigation. This model is also meant as a baseline for further exploration of opportunities of plant species distribution modeling for the last remaining wilderness areas and can be used as a baseline for assessing and predicting effects of climate change or land use change on tree species ranges.
- Supplemental_Information:
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Most wilderness areas still lack accurate distribution information on tree species. Mapping of species is often done with roughly interpolated polygons and area restricted expert maps for such regions (Hulten 1968; Viereck and Little 2007), as data sampling in remote areas is difficult to conduct and often not affordable. This situation definitely applies to Alaska. However, wildlife research, vegetation type modeling and adaptive resource management call for better data on specific tree species distribution (Calef et al. 2005). Thus, there was a need for other approaches to efficiently obtain high-quality maps on the distribution of tree species, such as a species distribution model (SDM). SDMs are widely applied for the study of plant and animal species distribution (e.g. Engler et al. 2004; Franklin 1998; Guisan et al. 1998; Wisz et al. 2008), and have been reviewed extensively (e.g. Guisan and Zimmerman 2000). Here we applied a predictive GIS modeling approach, using freely available digital data on species occurrences and (bio-)climatic parameters (Ohse et al. 2009).The shown map is a result of a model approach, that derives spatially explicit distribution maps with a resolution of 4km. Here we try to show how data gaps can be overcome world-wide and help improve spatial decision-making for global sustainability.
- Time_Period_of_Content:
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- Time_Period_Information:
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- Single_Date/Time:
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- Calendar_Date: 1950-2000
- Currentness_Reference:
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period from which most of the point observations were taken (1950-2000)
- Status:
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- Progress: Complete
- Maintenance_and_Update_Frequency: As needed
- Spatial_Domain:
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- Bounding_Coordinates:
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- West_Bounding_Coordinate: -2301787.77313
- East_Bounding_Coordinate: 1730212.22687
- North_Bounding_Coordinate: 2748069.78588
- South_Bounding_Coordinate: 108069.78588
- Altitude_Distance_Units: meters
- Keywords:
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- Theme:
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- Theme_Keyword_Thesaurus: none
- Theme_Keyword: SDM
- Theme_Keyword: White spruce
- Theme_Keyword: map
- Theme_Keyword: tree species
- Theme:
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- Theme_Keyword_Thesaurus: National Park Service Theme Category Thesaurus
- Theme:
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- Theme_Keyword_Thesaurus: ISO 19115 Topic Category
- Place:
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- Place_Keyword: Alaska
- Access_Constraints: none
- Use_Constraints: high statewide accuracy, accuracy on local scale not guaranteed
- Point_of_Contact:
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- Contact_Information:
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- Contact_Person_Primary:
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- Contact_Person: Bettina Ohse
- Contact_Organization: EWHALE Lab University of Alaska Fairbanks
- Contact_Position: graduate student
- Contact_Electronic_Mail_Address: ftbo1@uaf.edu
- Contact_Electronic_Mail_Address: bettina.ohse@web.de
- Browse_Graphic:
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- Browse_Graphic_File_Name: SDM_PicGla_best_model.jpg
- Browse_Graphic_File_Description:
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Map showing predicted distribution of White Spruce in Alaska as derived by the best-performing model
- Browse_Graphic_File_Type: JPEG
- Browse_Graphic:
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- Browse_Graphic_File_Name: SDM_PicGla_four_models.jpg
- Browse_Graphic_File_Description:
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Map comparing predicted distribution of White Spruce in Alaska as derived by the four best-performing models
- Browse_Graphic_File_Type: JPEG
- Data_Set_Credit: citation
- Security_Information:
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- Security_Classification_System: none
- Security_Classification: Unclassified
- Security_Handling_Description: none
- Native_Data_Set_Environment:
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Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 2; ESRI ArcCatalog 9.2.0.1324
- Taxonomy:
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- Taxonomic_Classification:
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- Taxon_Rank_Name: Kingdom
- Taxon_Rank_Value: Plantae
- Taxonomic_Classification:
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- Taxon_Rank_Name: Subkingdom
- Taxon_Rank_Value: Tracheobionta
- Taxonomic_Classification:
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- Taxon_Rank_Name: Division
- Taxon_Rank_Value: Coniferophyta
- Taxonomic_Classification:
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- Taxon_Rank_Name: Class
- Taxon_Rank_Value: Pinopsida
- Taxonomic_Classification:
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- Taxon_Rank_Name: Order
- Taxon_Rank_Value: Pinales
- Taxonomic_Classification:
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- Taxon_Rank_Name: Family
- Taxon_Rank_Value: Pinaceae
- Taxonomic_Classification:
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- Taxon_Rank_Name: Genus
- Taxon_Rank_Value: Picea
- Taxonomic_Classification:
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- Taxon_Rank_Name: Species
- Taxon_Rank_Value: Picea glauca
- Applicable_Common_Name: white spruce
- Applicable_Common_Name: black hills spruce
- Applicable_Common_Name: canadian spruce
- Applicable_Common_Name: cat spruce
- Applicable_Common_Name: porsild spruce
- Applicable_Common_Name: skunk spruce
- Applicable_Common_Name: western white spruce
- Data_Quality_Information:
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- Attribute_Accuracy:
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- Attribute_Accuracy_Report:
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Index of relative occurrence was predicted by the model with values ranging from 0 to 1 (floating point values). This map classifies the values into 5 equal classes for easier application.
- Quantitative_Attribute_Accuracy_Assessment:
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- Attribute_Accuracy_Value: 0 to 1
- Attribute_Accuracy_Explanation: Index of relative occurrence, rounded off to 2 decimals
- Logical_Consistency_Report:
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All data were based on a longterm time period (species data 1928-2005, climatic variables 1961-1990). Similar quality assurance procedures were used with all input data sets.
- Positional_Accuracy:
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- Horizontal_Positional_Accuracy:
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- Horizontal_Positional_Accuracy_Report:
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Accuracy of this data set is based on the specification of the species dataset that was used to train the model. The stated accuracy of the species dataset ranges from 0 to 3615m, depending on the specific sample point. Accordingly we chose 4km as an appropriate resolution.
- Quantitative_Horizontal_Positional_Accuracy_Assessment:
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- Horizontal_Positional_Accuracy_Value: 4km
- Horizontal_Positional_Accuracy_Explanation: based on training dataset used to build the model
- Vertical_Positional_Accuracy:
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- Vertical_Positional_Accuracy_Report:
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Accuracy of this data set is based on the specification of the species dataset that was used to train the model. The stated accuracy of the species dataset ranges from 0 to 3615m, depending on the specific sample point. Accordingly we chose 4km as an appropriate resolution.
- Quantitative_Vertical_Positional_Accuracy_Assessment:
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- Vertical_Positional_Accuracy_Value: 4km
- Vertical_Positional_Accuracy_Explanation: based on training dataset used to build the model
- Lineage:
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- Source_Information:
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- Source_Citation:
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- Citation_Information:
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- Originator:
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Dr. Christopher Daly of the Spatial Climate Analysis Service at Oregon State University.
- Publication_Date: 20020408
- Title: Alaska Average Monthly or Annual Mean Temperature, 1961-90
- Geospatial_Data_Presentation_Form: raster digital data
- Online_Linkage: <http://www.climatesource.com/ak/fact_sheets/meta_tmean_ak.html>
- Source_Scale_Denominator: 2km grid
- Type_of_Source_Media: online
- Source_Time_Period_of_Content:
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- Source_Currentness_Reference: publication date
- Source_Citation_Abbreviation: tmean
- Source_Contribution:
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mean temperature of april, may, june, september, and difference in mean temperature july-january used as climatic variable for building the model
- Source_Information:
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- Source_Citation:
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- Citation_Information:
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- Originator:
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Dr. Christopher Daly of the Spatial Climate Analysis Service at Oregon State University.
- Publication_Date: 20020408
- Title: Alaska Average Monthly or Annual Precipitation, 1961-90
- Geospatial_Data_Presentation_Form: raster digital data
- Online_Linkage: <http://www.climatesource.com/ak/fact_sheets/meta_precip_ak.html>
- Source_Scale_Denominator: 2km grid
- Type_of_Source_Media: online
- Source_Time_Period_of_Content:
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- Source_Currentness_Reference: publication date
- Source_Citation_Abbreviation: ppt
- Source_Contribution:
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precipitation of august, april, may, and growing season (may-sept) grow used as climatic variables for building the model
- Source_Information:
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- Source_Citation:
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- Citation_Information:
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- Originator: U.S. Geological Survey EROS Alaska Field Office
- Publication_Date: 19961210
- Title: Alaska 1km Digital Elevation Model
- Geospatial_Data_Presentation_Form: raster digital data
- Online_Linkage: <http://agdcftp1.wr.usgs.gov/pub/projects/fhm/elevmeta.html>
- Source_Scale_Denominator: 1km grid
- Type_of_Source_Media: online
- Source_Time_Period_of_Content:
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- Source_Currentness_Reference: publication date
- Source_Citation_Abbreviation: elevation
- Source_Contribution:
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used as bioclimatic variable for building the model,
used for calculating aspect for use as bioclimatic variable for building the model
- Source_Information:
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- Source_Citation:
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- Citation_Information:
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- Title:
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Herbarium (ALA), University of Alaska Museum of the North, Fairbanks, AK
- Geospatial_Data_Presentation_Form: tabular digital data
- Online_Linkage: <http://arctos.database.museum/SpecimenSearch.cfm>
- Source_Scale_Denominator: point location accuracy: 3615m
- Type_of_Source_Media: online
- Source_Time_Period_of_Content:
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- Source_Currentness_Reference: date of download (05-22-2008)
- Source_Citation_Abbreviation: Arctos Database
- Source_Contribution:
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species locations used as training dataset for building the model
- Process_Step:
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- Process_Description:
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Free online data on confirmed species locations and on climatic and bioclimatic variables were overlayed in GIS and a regular grid over the entire state of Alaska was created. Also, preinformed pseudo-absence points were created.
- Process_Date: 2008
- Process_Step:
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- Process_Description:
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Variable values were extracted to the confirmed presence points, to pseudo-absence points, and to all points of the regular grid.
- Process_Date: 2008
- Process_Step:
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- Process_Description:
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Model development, i.e. derivation of index of relative occurrence according to the environmental parameters
- Process_Date: 2008
- Process_Step:
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- Process_Description:
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Application of model to all gridpoints, i.e. extrapolation to the entire state
- Process_Date: 2008
- Process_Step:
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- Process_Description:
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Mapping the values of predicted index of relative occurrence for white spruce in Alaska
- Process_Date: 2008
- Spatial_Data_Organization_Information:
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- Direct_Spatial_Reference_Method: Raster
- Raster_Object_Information:
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- Raster_Object_Type: Grid Cell
- Row_Count: 660
- Column_Count: 1008
- Spatial_Reference_Information:
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- Horizontal_Coordinate_System_Definition:
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- Geodetic_Model:
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- Horizontal_Datum_Name: North American Datum of 1983
- Ellipsoid_Name: GRS_1980
- Semi-major_Axis: 6378137.000000000000000000
- Denominator_of_Flattening_Ratio: 298.257222101000020000
- Entity_and_Attribute_Information:
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- Detailed_Description:
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- Entity_Type:
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- Entity_Type_Label: predicted index of relative occurrence
- Attribute:
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- Attribute_Label: Pixel Value
- Attribute_Label: Rel Index of Occurrence
- Attribute_Definition: Value of Pixel
- Attribute_Definition: Rel. Index of Occurrence 0 to 1
- Attribute_Definition_Source: UAF
- Attribute_Definition_Source: UAF
- Distribution_Information:
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- Distribution_Liability:
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The authors, or the National Park Service shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics (i.e. GIF or JPG format files) are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time. The data are not better than the original sources from which they were derived. 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. The related graphics are intended to aid the data user in acquiring relevant data; it is not appropriate to use the related graphics as data. The authors or the National Park 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 an NPS server and not indirectly through other sources which may have changed the data in some way. Although these data have been processed successfully on computer systems at the National Park Service, no warranty expressed or implied is made regarding the utility of the data on other systems 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.
- Standard_Order_Process:
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- Fees: None
- Resource_Description: Map Files in ESRI and jpg format.
- Technical_Prerequisites: none (Computer and ideally a GIS)
- Metadata_Reference_Information:
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- Metadata_Date: 20080826
- Metadata_Contact:
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- Contact_Information:
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- Contact_Person_Primary:
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- Contact_Person: Bettina Ohse
- Contact_Organization: EWHALE Lab University of Alaska Fairbanks
- Contact_Position: PhD graduate student
- Contact_Address:
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- Address_Type: 419 Irving I
- City: Fairbanks
- State_or_Province: Alaska
- Postal_Code: 99775
- Contact_TDD/TTY_Telephone: +1 907 474 7882
- Contact_Electronic_Mail_Address: bettina.ohse@uni-greifswald.de
- Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata
- Metadata_Standard_Version: FGDC-STD-001-1998
- Metadata_Extensions:
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- Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
- Profile_Name: ESRI Metadata Profile
- Metadata_Time_Convention: local time
- Metadata_Access_Constraints: none
- Metadata_Use_Constraints: none
- Metadata_Security_Information:
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- Metadata_Security_Classification_System: none
- Metadata_Security_Classification: Unclassified
- Metadata_Security_Handling_Description: none
Generated by mp version 2.8.25 on Fri Mar 06 01:20:14 2009