arcview metadata training: american samoa james byrne josh murphy noaa coastal services center july...
TRANSCRIPT
ArcView Metadata Training:ArcView Metadata Training:American SamoaAmerican Samoa
James ByrneJosh Murphy
NOAA Coastal Services CenterJuly 29-30, 2003
Course Outline
Part I: What Is Metadata?
Part II: Metadata Creation
Part III: Class Exercise
Part IV: Clearinghouses
First…. Some Terms
Metadata - Documentation of geospatial data written in a consistent manner
FGDC - Federal Geographic Data Committee
CSDGM - Content Standard for Digital Geospatial Metadata, referred to commonly as “The Standard” or “The Content Standard”
Clearinghouse - A distributed catalog of metadata
Geospatial - refers to a geographic location
Part I: What Is Metadata?Part I: What Is Metadata?
Simply put, metadata is information
about your data.
What is Metadata?
This is the metadata for this.
What’s Missing?
Aunu`u
Author(s) Boullosa, Carmen. Title(s) History of American Samoa / by Carmen Boullosa Place New York : Grove Press, 1997. Physical Descr viii, 180 p ; 22 cm. Subject(s) Oceana Format Reference
Author(s) Boullosa, Carmen. Title(s) History of American Samoa / by Carmen Boullosa Place New York : Grove Press, 1997. Physical Descr viii, 180 p ; 22 cm. Subject(s) Oceana Format Reference
This is the metadata for this.
While the card-catalog entry is a form of metadata, it does not address topics such as
quality, accuracy, or scale. Well-written geospatial metadata describes these and many more aspects of the data.
Identification_Information: Citation: Citation_Information: Originator: United States Department of Commerce, National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Coastal Services Center (CSC) Publication_Date: 20020923 Title: Vectorized Shoreline of Hawaii, Derived from Landsat ETM, 2002 Edition: first Geospatial_Data_Presentation_Form: vector digital data Publication_Information: Publication_Place: Charleston, SC Publisher: United States Department of Commerce,
Identification_Information: Citation: Citation_Information: Originator: United States Department of Commerce, National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Coastal Services Center (CSC) Publication_Date: 20020923 Title: Vectorized Shoreline of Hawaii, Derived from Landsat ETM, 2002 Edition: first Geospatial_Data_Presentation_Form: vector digital data Publication_Information: Publication_Place: Charleston, SC Publisher: United States Department of Commerce,
This is the metadata for this.
What is Metadata?
Metadata contains vital information.Metadata contains vital information.Imagine, if you will…
You are given two identical cans without labels. One contains cat food, the other contains tuna (dolphin-safe, of course).
You must choose one these cans,
and then eat the contents.
Other Examples?
What is Metadata?
Properly documented
data provides vital information
to interested parties.
Metadata is that component of data which describes it.
Environmental Sensitivity Index Data
Metadata
RARNUM - unique combination of species, concentration, and seasonality
CONC (concentration) = Density species is found at location
Season_ID = seasonality code link to the seasonal table
Element - Biology group
What is Metadata?
It’s data about a data set.It’s data about a data set.
Title
Scale
Source
Content
Location
Publication
Access
Title
Scale
Source
Content
Location
Publication
Access
MetadataMetadataMetadataMetadata
GIS files
Imagery
Geospatial databases
GPS data
GIS files
Imagery
Geospatial databases
GPS data
Data setData setData setData set
What is Metadata?
Metadata describes…
CONTENT
CONDITION
QUALITY
Characteristics of the data
Characteristics of the data
What is Metadata?
Metadata
Non-spatial orattributes
Spatial
Because metadata provides vital information about a dataset, it should never be viewed or
treated as a separate entity.
Take Home Message
Metadata is a critical and
integral component of any complete
data set.
Metadata is a critical and
integral component of any complete
data set.
Two similar Two similar paintings by paintings by
Picasso up for Picasso up for auction sold for auction sold for vastly different vastly different
prices. prices.
Why?
One had metadata...
...One didn’t.
The Value of Metadata
Metadata should be updated to reflect changes in the data.
19701970
HEWHEWWestern SamoaWestern SamoaBritish HondurasBritish Honduras
Trust TerritoryTrust TerritoryCape Hatteras Light Cape Hatteras Light
ArpanetArpanetMt. St. HelenMt. St. Helen
West GermanyWest Germany
20002000
HHS & HUDHHS & HUDSamoaSamoaBelizeBelizeU.S. CommonwealthU.S. CommonwealthCape Hatteras LightCape Hatteras LightInternetInternetMt. St. HelenMt. St. HelenGermanyGermany
Metadata has Metadata has other value other value
associated with associated with it.it.
• Avoid duplication Avoid duplication
• Share reliable informationShare reliable information
• Publicize effortsPublicize efforts
• Reduce workloadReduce workload
For data developers, metadata...
The Value of Metadata
• Facilitates understandingFacilitates understanding
• Focuses on key elements Focuses on key elements
• Enables discovery — inside and outside Enables discovery — inside and outside of organizationsof organizations
For data users, metadata...
The Value of Metadata
For organizations, metadata...
The Value of Metadata
• Protect investment in data
• Create an institutional memory
• Counter personnel changes
• Allow sharing of data with other agencies
• Reduce costs
• Limit potential liability
• Save time and money
Metadata as a “data discovery” toolMetadata as a “data discovery” tool
This saves time and money.
If it’s geospatial data you need, metadata helps
• Find data of interest
• Determine the usefulness of the data
• Determine how to access the data
The Value of Metadata
Metadata Standards
Think for a moment how hard it would be to…
… bake a cake without standard units of measurement.
… put gas into your car without standard nozzle sizes.
… plug a lamp into a socket without standard electrical outlets.
The standard for
metadata ensures a level
of consistency in
data documentation.
Standards ensure consistency.
Metadata Standards
The Federal Geographic Data Committee (FGDC) was organized in 1990 under the
Office of Management and Budget to promote the coordinated use, sharing,
and dissemination of geospatial data on a national basis. The FGDC was tasked
with creating a metadata standard to meet these objectives.
The Metadata Standard
Metadata Standards
"... each agency shall document all new
geospatial data it collects or produces, either
directly or indirectly, using the standard under
development by the FGDC, and make that
standardized documentation electronically
accessible to the Clearinghouse network."
The Content Standard for Digital Geospatial Metadata (CSDGM)
Executive Order 12906, 1994
Metadata Standards
The Content Standard utilizes...The Content Standard utilizes...
• Common termsCommon terms
• Common definitionsCommon definitions
• Common languageCommon language
• Common structureCommon structure Access
constraints
Citation
currentness
entity
attrib
ute
domain
lineage
Process step
Metadata Standards
The Content Standard helps The Content Standard helps
the user determine...the user determine...
• If a set of geospatial data is available and fit for a particular use.
•How to access and transfer the data set.
Metadata Standards
FGDC’s Metadata
Workbook
Defines the 334
metadata elements.
Metadata Standards
What do I use “The Workbook” for?
• It is the definitive resource for applying the FGDC Content Standard.
• However, it does not define the production rules.
• It describes element domain values, which are valid values that can be assigned to the data element.
• It provides section and element definitions.
Interpreting the Metadata Workbook
A data element is a logically primitive itemof data. Data elements are the things thatyou “fill in.”
The form for the definition of a data element is:
Data element name -- definition.Type: (choice of “integer”, “real”, “text”, “date”, or “time”)Domain: (describes valid values that can be assigned)
An example of the definition of a data element is:
Abstract -- a brief narrative summary of the data set.Type: textDomain: free text
Note: Data element definitions are containedin the text of the Content Standard,
not in the graphical production rules.
• It is a quick reference for production rules and structure.
Use the “Graphical Representation”for quick access.
• You will still need to use the workbook to find the definition of a particular element and its domain.
Organization of the Content Standard
DataQuality
Information
SpatialData
OrganizationInformation
SpatialReference
Information
Entityand
AttributeInformation
4 52 6 731
Metadata
The Three Supporting SectionsThe Three Supporting Sections
9 Time PeriodInformation
10 Contact
Information
8 Citation
Information
DistributionInformation
MetadataReference
Information
IdentificationInformation
Organization of the Content Standard
The Seven Main Sections The Seven Main Sections
Mandatory - must be provided.
MeaningData
ElementCompound
Element
What’s Mandatory? What’s Not?
Mandatory if Applicable - must be provided if the data set exhibits
the defined characteristic.
Optional - provided at the discretion of the data set producer.
Remember, metadata is a legacy document that
concisely sums up your data or data set.
Without metadata, your data set is
incomplete.
Part II: Metadata CreationPart II: Metadata Creation
Writing Metadata
is not THAT bad!
• First records are the hardest.• Not all fields may need to be filled in.• Tools are available.• Training classes can be taken.• Can often be produced automatically.• Can (and should) be reviewed
for updates.
Templates can help!!
• Contain information that is specific to your project or organization
• Allow you to enter and save pertinent information for use at later date
• Save time and effort!• No special tools needed!• Like any other metadata, can (and
should) be reviewed for updates.
Writing Metadata
Before you begin writing,get organized.
Writing Metadata
Document your data as you go.
Writing Metadata
Write so others can understand.
Writing Metadata
• Define all acronyms.
• Avoid using jargon.
• Clearly state data limitations.
Writing Metadata
Keep your readers in mind.
Always review your document.
Writing Metadata
Items required
Chocolate
FGDCWorkbook
Metadata entry tool
Tool Time
A sample of some of the available tools for metadata creation, validation, and publication.
• CNS and MP“Chew ‘n spit,” checks and corrects structural errors, and “Metadata Parser”, which checks for errors in element compliance.
• NOAA CSC MetaScribe Allows you to create a template record that can be used to create large numbers of similar records.
• NOAA CSC ArcView Metadata Collector Extension for ArcView 3.x.
• TKMEText editor used for metadata entry.
• ArcCatalog Metadata Editor Metadata creation in ArcGIS
TKME
• An editor for formal metadata.• TKME is intended to simplify the process of creating metadata that conform to the content standard
Metadata Collector for ArcView 3.2
• A free, downloadable extension for ArcView 3.x users• Enters information for certain elements automatically• Allows user to save individual elements for future use
At the right side of most of the screens will be the option to Retrieve and Save the information you have entered into the fields. This allows you to save frequently used information such as contact and similar abstracts to be used repeatedly. These are generally saved as either .dbf or .txt files in the working directory specified.
On each screen, there is a SectionHelp and a Section Example button.The Section Help button opens a window containing definitions of the metadataelements for that section. The SectionExample button provides an example of an FGDC-compliant metadata record.
Metadata Collector for ArcView 3.2
Certain sections are read directly from the data set by the ArcView Metadata Collector
Metadata Collector for ArcView 3.2
When you have finished all of the metadata sections, you will be presented with the option to save the metadata file as both a text and an HTML file.
Metadata Collector for ArcView 3.2
MetaScribeMetaScribe
• A tool for the creation of multiple, similar metadata records• Template driven
Metadata Parser (mp)Metadata Parser (mp)
• DOS-based tool that compiles and checks the syntax of “raw” metadata
• Input must be either text, XML, or SGML• Creates outputs in multiple formats (HTML, TXT, XML, SGML)• Also creates an error file
ArcCatalog Metadata EditorArcCatalog Metadata Editor
• Included with basic ArcGIS 8.x software• Simple to use:
• Projection parameters automatically captured (if .prj file present)
• Can use template to automatically fill in contact, distribution information
Using the AV Metadata Collector ExtensionUsing the AV Metadata Collector Extension
• For the remainder of this section, the instructor will demonstrate For the remainder of this section, the instructor will demonstrate metadata creation using the FGDC Content Standard and the metadata creation using the FGDC Content Standard and the ArcView Metadata Collector extension. ArcView Metadata Collector extension.
Section 1 – Identification InformationSection 2 – Data Quality InformationSection 3 – Spatial Data Organization InformationSection 4 – Spatial Reference InformationSection 5 – Entity and Attribute InformationSection 6 – Data Distribution InformationSection 7 – Metadata Reference Information
Review: The Seven Main Sections of the Content Standard
Using the AV Metadata Collector ExtensionUsing the AV Metadata Collector Extension
Data Set Example
Tutuila Shoreline
Section 1 – Identification Information
Basic Information about the data set.
Section 1 – Identification Information
Metadata
The title is critical in helping others find your data.
Which is better?
Greater Yellowstone Rivers from 1:126,700 Forest Visitor Maps (1961-1983)
Section 1
• The title is the first thing a user sees when searching for data• The title helps a user quickly determine the usefulness of data
Include topic, time and place!
Bad title (user has to read description):“Roads”
Better title:“Roads Shapefile for Guam - 2000”
Title, title, title
Section 1
Bounding Coordinates
West_Bounding_Coordinate: 145.69
East_Bounding_Coordinate: 145.83
North_Bounding_Coordinate: 15.29
South_Bounding_Coordinate: 15.09
15.29, 145.69
15.09, 145.83
Select your key words wisely.
• Use unambiguous words.
• Use descriptive words.
• Fully qualify geographic locations.
Key Words
Theme:Theme_keyword_thesaurus: NoneTheme_keyword: major roadsTheme_keyword: highwaysTheme_keyword: transportation networkTheme_keyword: thoroughfaresTheme_keyword: vector digital dataTheme_keyword: geographic information system
Key Words
Access and Use Constraints
• Essentially liability statements
• Example:
Section 1
Use_Constraints: Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, NOAA, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. NOAA makes no warranty, expressed or implied, nor does the fact of distributionconstitute such a warranty.
Use_Constraints: Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, NOAA, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. NOAA makes no warranty, expressed or implied, nor does the fact of distributionconstitute such a warranty.
Link to on-line data
Other_Citation_Details:Online_Linkage: http://www.csc.noaa.gov/hurricane_tracks.shp
Section 1 – Identification Information
Metadata
Section 2 – Data Quality Information
A general assessment of the quality of the data set.
Section 2 – Data Quality Information
A general assessment of the quality of the data set.
How thoroughly and correctly the features in the data set are described.
• What features have been omitted ? • What non-existent features are represented ? • How correct is their classification ? How can you test and report Attribute Accuracy?
• Field Verification• Visual comparison of source data to hard copy
Attribute Accuracy
Attributes
How accurate are these attributes?
Attribute Accuracy
DATA_QUALITY_INFORMATION
Attribute_Accuracy Attribute_Accuracy_Report: A team of field investigators participated in data verification exercises June, 1996 and December, 1996. Data validation teams consisted of personnel from Oak Ridge National Laboratory, Moss Landing Marine Laboratories, Ray L. Harris, Jr., and the Coastal Services Center. The team was equipped with a portable color laptop computer linked to a Global Positioning System (GPS). The field station runs software that supports the classified data as a raster background with the road network as a vector overlay with a simultaneous display of live GPS coordinates. Accuracy assessment points were generated with Erdas Imagine software using a stratified random sample. To make the acquisition of the field reference data more practical, a sixteen pixel buffer area around roads (i.e. 8 pixels on each side of the road) including logging trails was created. Seven thousand random points were generated within this area for the accuracy assessment. See the accuracy assessment table for results of data verification exercise.
Attribute Accuracy
Exa
mp
le A
ttri
bu
te A
ccu
racy
Rep
ort
A closer lookDo these footprints accurately represent these?
Attribute_Accuracy: Attribute_Accuracy_Report: Attribute accuracy was tested by manual comparison of the source with hardcopy printouts of the digital building footprint data. The attributes were visually compared to attributes in the source data (digital orthophoto).
Attribute Accuracy
Addresses geometric problems in your dataset-overshoots-undershoots-broken polygons-missing or duplicate labels
A typical Logical Consistency Statement:
Logical_Consistency_Report: These data are believed to be logically consistent, though no tests were performed. There are no overshoots, undershoots or broken polygons. Line geometry is topologically clean.
Logical Consistency
Geometric/Logical Consistency Problems
How the coordinate descriptions of features compare to the actual locations of those features on the ground.
How far away is a map feature from its actual location in the world?
How can you test for and report Positional Accuracy?
Comparison of your data to more accurate data (survey data) GPS accuracy Using the National Map Accuracy Standards (positional accuracy for paper maps only)
Positional Accuracy
Q: How horizontally accurate is the position of this shoreline?
A: As accurate as the data itwas derived from.
Positional Accuracy
Positional_Accuracy: Horizontal_Positional_Accuracy: Horizontal_Positional_Accuracy_Report: The data were created by delineating the boundary off a USGS 7.5 minute Topographic Map at 1:24000 scale. Therefore, the horizontal accuracy is assumed to be within National Map Accuracy Standards, with a horizontal accuracy of 45.6 feet at the 95% confidence level.
Positional_Accuracy: Horizontal_Positional_Accuracy: Horizontal_Positional_Accuracy_Report: The data were collected with a trimble pathfinder Global Positioning System. The horizontal accuracy of the point data is 300ft.
Positional Accuracy
Examples
Using National Map Accuracy Standards
Using GPS accuracy
Be specific. Quantify when you can.
Vague: We checked our work and it looks complete.
Specific: We checked our work using 3 separate sets of check plots reviewed by 2 different people. We determined our work to be 95% complete based on these visual inspections.
Process Step
Section 2 – Data Quality Information
Metadata
Section 3 – Spatial Data Organization Information
The mechanism used to represent spatial Information in the data set.
Spatial Data Organization Information
What is the Structure of the Data?
Raster
Vector
Row and Column count
Vector Object Count
Section 3 – Spatial Data Organization Information
Metadata
Section 4 – Spatial Reference Information
The description of the reference frame for, andThe means to encode coordinated in the data set.
Section 4 - Spatial Reference Information
Three Choices under Horizontal Coordinate System
• Geographic Latitude and Longitude
• Planar Map Projection Grid Coordinate System Local Planar
• Local
Geographic Coordinate System
Latitiude and longitude measurements define a position on the Earth.
Units of measurement can be• decimal degrees• decimal minutes• decimal seconds• degrees and decimal minutes• degrees minutes and seconds• radians • grads
Planar Systems
Map Projection - representation of the earth’s surface
East-West Projections: Lambert, Albers (Conic)Used in Florida, Massachusetts, and Ohio
North-South Projections: Transverse Mercator (Cylindrical) Used in Florida and California
Grid Coordinate Systems - State Plane and UTM
Used by states as common coordinate systemsBased on map projections
Datums
A datum is a set of parameters defining a coordinate system.
Typically, your data’s projection will be referenced to either North American Datum NAD 83World Geodetic System 1984North American Datum NAD 27
Section 4 – Spatial Reference Information
Metadata
Section 5 – Entity and Attribute Information
Information about the content of the data set,including the entity types, their attributes, andthe attribute values that may be assigned.
Attribute Table
attributes
attribute values
Attribute Table
Detailed Attribute DescriptionNot only do you have to describe your attributes but you also have to describe the values
Attribute Domains: domains are used to describe attribute values
1) Range Domain: a sequence of values- if the attribute is “water_depth” and the values are between 0 and 150, a range domain is suitable.
2) Enumerated Domain: comprised of a list of values- if the attribute is “landcover_code” and the list of values is between 1 16, then an enumerated domain should be used.
3) Codeset Domain: data values are defined by a set of codes- if the attribute is “wetland_id#” and the codes are defined in a standard or code book, then the codeset domain should be used.
4) Unrepresentable Domain: the set of data values cannot be represented- numbers assigned by software program that are meaningless
Enumerated Domain
To understand thislegend, each value in this enumerateddomain will have to be defined.
Section 5 – Entity and Attribute Information
Metadata
Section 6 – Distribution Information
Information about the distributor of and optionsfor obtaining the data set.
Section 6 – Distribution Information
Metadata
Section 7 – Metadata Reference Information
Information on the currentness of the metadata information, and the responsible party.
Section 7 – Metadata Reference Information
Metadata
• Have someone else read it.
• If you’re the only reviewer, put it away and read it again later.
• Check for clarity and omissions.
Review your final product.
Reviewing Metadata
• Can a novice understand what you wrote?
• Are your data properly documented for posterity?
When you review your work, ask:
Reviewing Metadata
• Does the documentation present all the information needed to use or reuse the data?
• Are any pieces missing?
When you review your work, ask:
Reviewing Metadata
Part III: Class ExercisePart III: Class Exercise
Part IV: ClearinghousesPart IV: Clearinghouses
ClearinghousesClearinghouses
A metadata clearinghouse is a A metadata clearinghouse is a
location — typically accessed location — typically accessed
through the Internet — to through the Internet — to
search for spatial data setssearch for spatial data sets
A clearinghouse is a decentralized system of Internet servers you can search
Servers with metadataServers with metadata
Client
ClearinghousesClearinghouses
Clearinghouses make Clearinghouses make
metadata records easy to metadata records easy to
find find
ClearinghousesClearinghouses
The National Geospatial Data The National Geospatial Data
Clearinghouse has more than 100 spatial Clearinghouse has more than 100 spatial
data servers with digital geographic datadata servers with digital geographic data
ClearinghousesClearinghouses
The NGDC The NGDC is a set of information services is a set of information services
that use that use hardware, software,hardware, software, and and
telecommunications networkstelecommunications networks to provide to provide
searchable access to informationsearchable access to information
ClearinghousesClearinghouses
• FGDC Geospatial Data Clearinghouse
• Montana State Library Natural Resource Information System GIS
• Nebraska Geospatial Data Clearinghouse
• Wisconsin Land Information Clearinghouse
Some specific examples:Some specific examples:
ClearinghousesClearinghouses
You can search all or part of You can search all or part of
the community in a single the community in a single
sessionsession
x
ClearinghousesClearinghouses
ClearinghousesClearinghouses
www.fgdc.gov
You can define your criteria
ClearinghousesClearinghouses
You can select a server
ClearinghousesClearinghouses
You can view your search results
ClearinghousesClearinghouses
The FGDC Clearinghouse selected
the search and retrieve software
ANSI Z39.50-1995 (ISO 10163-1995)
Clearinghouse ImplementationClearinghouse Implementation
How can you participate? How can you participate?
• Set up your own node
• Send metadata to an existing node
• Have another organization host your node
• Put metadata on a web page for future “harvesting” to a node
Clearinghouse ImplementationClearinghouse Implementation
Why set up a node? Why set up a node?
• YouYou control your metadata
• It’s easy to set up
• You choose the software
• The software operates on typical web server platforms
Clearinghouse ImplementationClearinghouse Implementation
• In setting up a node, most work is in preparing metadata for available data sets
• Store these data in a structured form, according to the standard
Clearinghouse ImplementationClearinghouse Implementation
Before you can index your
metadata into a clearinghouse,
you must check for completeness,
accuracy, and quality
Clearinghouse ImplementationClearinghouse Implementation
Your metadata must meet clearinghouse requirements:
• Proper format
• Proper field names and values
• Appropriate formats: text, HTML, and fgfSGML
Clearinghouse ImplementationClearinghouse Implementation
Parsing and validation tools check for Parsing and validation tools check for structural or content errorsstructural or content errors
errorerrorreportsreports
metadatametadatadocumentsdocuments
metadata parser metadata parser softwaresoftware
mpmp
Clearinghouse ImplementationClearinghouse Implementation
Run cns output through mp to make text, SGML, HTML files
Run cns output through mp to make text, SGML, HTML files
YESYESCorrect original fileCorrect original file
Run original file through cnsRun original file through cns
Errors in error.txt?YESYES
CreateMetadataCreate
Metadata
Run cns output through mpRun cns output through mp
NONO
Correct original fileCorrect original file
Place 3 files on searchable system
Place 3 files on searchable system
Errors in error.txt?
Errors in error.txt?
NONO
Clearinghouse ImplementationClearinghouse Implementation
mp produces metadata in HTML, mp produces metadata in HTML, SGML, and TEXTSGML, and TEXT
mpmpmpmp TEXTTEXTTEXTTEXTHTMLHTMLHTMLHTML
SGMLSGMLSGMLSGML
Clearinghouse ImplementationClearinghouse Implementation
<html>
<head>
<title>1989 Land Cover/Land Use on the Upper Mississippi River System</title>
</head>
<body>
<h1>1989 Land Cover/Land Use on the Upper Mississippi River System</h1>
<h2>Metadata:</h2>
<ul>
<li><A HREF="#Identification_Information">Identification_Information</A>
<li><A HREF="#Data_Quality_Information">Data_Quality_Information</A>
<li><A HREF="#Spatial_Data_Organization_Information">Spatial_Data_Organization_Information</A>
<html>
<head>
<title>1989 Land Cover/Land Use on the Upper Mississippi River System</title>
</head>
<body>
<h1>1989 Land Cover/Land Use on the Upper Mississippi River System</h1>
<h2>Metadata:</h2>
<ul>
<li><A HREF="#Identification_Information">Identification_Information</A>
<li><A HREF="#Data_Quality_Information">Data_Quality_Information</A>
<li><A HREF="#Spatial_Data_Organization_Information">Spatial_Data_Organization_Information</A>
mp HTML filemp HTML file mp HTML filemp HTML file
Clearinghouse ImplementationClearinghouse Implementation
mp HTML filemp HTML file mp HTML filemp HTML file
Clearinghouse ImplementationClearinghouse Implementation
<!DOCTYPE METADATA PUBLIC "-//FGDC//DTD METADATA 1.0//EN"><metadata>
<idinfo>
<citation>
<citeinfo>
<origin>Kurt P. Kowalski and Douglas A. Wilcox</origin>
<origin>Great Lakes Science Center</origin>
<origin>Biological Resources Division</origin>
<pubdate>1997</pubdate>
<title>Coastal Wetland Vegetation Analysis (Metzger Marsh)
</title>
<pubinfo>
<pubplace>Ann Arbor, MI</pubplace>
<!DOCTYPE METADATA PUBLIC "-//FGDC//DTD METADATA 1.0//EN"><metadata>
<idinfo>
<citation>
<citeinfo>
<origin>Kurt P. Kowalski and Douglas A. Wilcox</origin>
<origin>Great Lakes Science Center</origin>
<origin>Biological Resources Division</origin>
<pubdate>1997</pubdate>
<title>Coastal Wetland Vegetation Analysis (Metzger Marsh)
</title>
<pubinfo>
<pubplace>Ann Arbor, MI</pubplace> mp SGML filemp SGML file mp SGML filemp SGML file
Clearinghouse ImplementationClearinghouse Implementation
Identification_Information:
Citation:
Citation_Information:
Originator: Environmental Management Technical Center
Publication_Date: 19950829
Title: 1989 Land Cover/Land Use on the Upper Mississippi River System
Geospatial_Data_Presentation_Form: Map
Publication_Information:
Publication_Place: Environmental Management Technical Center
Publisher: Environmental Management Technical Center (EMTC)
Other_Citation_Details: White, B. M. and T. W. Owens. 1991. Geographic Information System Pilot Project For The Upper Mississippi River System. U.S. Fish and Wildlife Service, National Ecology Research Center, Fort Collins, Colorado, June 1991. LTRMP 91-05. 48 pp. + Appendix.
Identification_Information:
Citation:
Citation_Information:
Originator: Environmental Management Technical Center
Publication_Date: 19950829
Title: 1989 Land Cover/Land Use on the Upper Mississippi River System
Geospatial_Data_Presentation_Form: Map
Publication_Information:
Publication_Place: Environmental Management Technical Center
Publisher: Environmental Management Technical Center (EMTC)
Other_Citation_Details: White, B. M. and T. W. Owens. 1991. Geographic Information System Pilot Project For The Upper Mississippi River System. U.S. Fish and Wildlife Service, National Ecology Research Center, Fort Collins, Colorado, June 1991. LTRMP 91-05. 48 pp. + Appendix.
mp TEXT filemp TEXT file mp TEXT filemp TEXT file
Clearinghouse ImplementationClearinghouse Implementation
Clearinghouse ImplementationClearinghouse Implementation
For more information on For more information on clearinghouse implementation:clearinghouse implementation:
Clearinghouse ImplementationClearinghouse Implementation
www.fgdc.gov/clearinghouse/tutorials/howto.html
OR
Please contactJohn Ulmer
NOAA CSC Computer [email protected]
Any Questions?Any Questions?
Clearinghouse ImplementationClearinghouse Implementation