Tualatin River Watershed Data Dictionary


Metadata for USGSLC92

Table of Contents



Identification_Information
     Abstract 
     Purpose 
     Supplemental Information 
Data_Quality_Information
Spatial_Data_Organization_Information
Entity_and_Attribute_Information
     Detailed Description
     Overview 
Distribution_Information
Metadata_Reference_Section


Identification_Information

Citation_Information 
    Originator: 
    Publication_Date: 
    Title: 


Description  
    Abstract
    USGS Landcover (Classified 1992 TM Imagery - 9 classes)
     
     
    Purpose
    The Willamette Basin land cover map was created from Landsat
    thematic mapper (TM) data collected in June and August of 1992
    and 1993.  Of the eight scenes used, only one was collected in
    1993.  For the initial work the five August scenes were mosaiced
    together, with no smoothing or other kinds of spectral adjustment
    to minimize seam lines between images.  The basin boundary was
    then used to eliminate data outside of the basin.  Bands 3, 4,
    and 5 of the TM data were used to create the mosaic.  A color
    print of the TM mosaic was created, assigning band 5 to red, band
    4 to green, and band 3 to blue.  The resulting image depicted
    vegetation as green and non-vegetated or low density or dormant
    areas took on a pinkish tone. Water was shown in dark blue to
    black, and the snow caps of the peaks in the Cascades were
    lighter shades of blue.  Copies of the TM mosaic are available
    by calling User Services at the EROS Data Center (605 594 6151)
    and specifying order ID number E-1987-99cT in the PAO file.
    Copies of the land cover map are also available by specifying
    order ID E-1988-99cT.  Color prints at various sizes and 9 inch
    color positive transparencies can be ordered.
     
     
Supplemental_Information
    Procedures_Used
    The land cover map is currently available in an ARC GRID format.
    The grid is in the UTM projection, and coordinates can be gotten
    by using the ARC command DESCRIBE to display the location
    parameters.
     
    The file, wilcov.tar.Z, contains the grid image, tarred and compressed.
    The compressed file is about 6 megabytes in size,uncompressed is about
    16 megabytes.
     
     
    Revisions
    A small amount of manual editing of the cover map was done to
    correct some obvious misclassifications.  There were some deeply
    shadowed forest areas in the southern end of the basin which were
    misclassified as water.  Using 1:250,000 topographic sheets as a
    guide, obviously misclassified water bodies were converted to the
    mature forest class. The wet areas of a few center pivot
    irrigation systems along the Willamette River were misclassified
    as native vegetation and were changed to the other irrigation
    class.
     
     
    Reviews_Applied_to_Data
     
     
     
    Related_Spatial_and_Tabular_Data_Sets
     
     
     
    References_Cited
     
     
     
    Notes
    Address questions by email to seevers@edcsnw44.cr.usgs.gov or by phone
    to (605) 594-6010.  Also, please forward any comments or suggestions you
    may have regarding your experiences in using the map.  We are particularly
    interested in having examples of use of the data as a part of any analysis
    or decision-making process where it has been involved.
     
     
Time_Period_of_Content
    Currentness_Reference
     
     
     
Status
    Progress: Unknown
    Maintenance_and_Update_Frequency
     
     
     
Spatial_Domain
    Bounding_Coordinates
    West_Bounding_Coordinate: -123.44121567
    East_Bounding_Coordinate: -122.62379636
    North_Bounding_Coordinate: 45.81047805
    South_Bounding_Coordinate: 45.28708383


Keywords
    Theme
        Theme_Keyword_Thesaurus: None
        Theme_Keyword:  TM imagery, landcover, USGS
    Place
        Place_Keyword_Thesaurus: None
        Place_Keyword:  Tualatin River Watershed
    Stratum
        Stratum_Keyword_Thesaurus: None
        Stratum_Keyword:
    Temporal
        Temporal_Keyword_Thesaurus: None
        Temporal_Keyword:


Access_Constraints
 
 
 
Use_Constraints
Rather than attempt to use the classification process to define
the urban areas, the decision was made to use an urban layer
provided by the Water Resources Division as the urban land cover
class. This layer was used as a mask to remove that portion of
the mosaic which represented the urban class.  The remaining
digital data from bands 3, 4, and 5 of the August data were
processed to create an initial land cover map.  The data were
clustered using an unsupervised clustering algorithm (CLUSTER) in
EDCs Land Analysis System (LAS) software package.  The fifty
clusters from this processing were then assigned to land cover
categories through the following procedure.  Each cluster was
displayed individually, and by visually relating the pixel
locations to features in the mosaic and accompanying ground
information, the cluster was defined to be associated with a
specified land cover class.  Each cluster, in the majority of
cases, represented two or more cover classes.  To resolve the
conflicting cover class depictions, a modeling scheme using
ancillary data was devised to define the cover class based on the
relationship of the cluster pixels to the ancillary data at that
pixel location.  A set of decision rules was defined for each
cluster based on the cover classes indicated to be in conflict
and the relationship of the cover classes to the ancillary data
layers.  A simple example would be a cluster which defined both a
forest type and an irrigated crop.  Elevation would be a likely
factor to assign that pixel to the appropriate cover class; high
elevation indicating the forest type, low elevation indicating an
irrigated crop.  Slope also could be a decision factor; nearly
level land being required for irrigation, forests growing on
steeper terrain.  The ancillary data layers used in the modeling
scheme were digital elevation models (DEM), slope derived from
the DEMs, and STATSGO soils data.
 
The land cover map created from the modeling process did not
appear to define the agricultural classes as well as expected,
and it was desirable to have more agricultural classes if
possible.  It was decided to acquire spring data to take
advantage of the contrast in vegetative cover of the agricultural
fields between the spring and fall.  Three scenes covering the
agricultural portion of the basin, acquired in June of 1992, were
available.  All three scenes were acquired the same day
eliminating any problems associated with differences due to
different scene dates.  In order to focus on the agricultural
portion of the basin, a mask was created from the initial land
cover map which allowed only the data associated with the land
cover classes identified as agricultural to be extracted from the
two TM data sets.  These two extracted data sets were separately
processed using the CLUSTER algorithm and 25 clusters were
specified.  Each clustered data set was aggregated to five cover
classes using the features of the TM images and associated ground
data.  These aggregated data sets were then modeled together
using the association of the classes with their acquisition date
to the final cover class.  The resulting land cover image had
four land cover classes, which were concatenated back into the
initial land cover map.
 
 
 


Data_Set_Credit
 
 
 
Security_Information
    Security_Classification_System: None
    Security_Classification:  UNCLASSIFIED
    Security_Handling_Description: None


Native_Data_Set_Environment: Windows_NT Windows_NT, ARC/INFO version 7.1.1


Cross_Reference
    Originator: Unknown
    Publication_Date: 
    Publication_Time: 
    Title: 
    Edition: 
    Geospatial_Data_Presentation_Form: 
    Series_Information
        Series_Name: 
        Issue_Identification: 
    Publication_Information
        Publication_Place: 
        Publisher: 
    Other_Citation_Details: 
    Online_Linkage: 
    Larger_Work_Citation: 





Data_Quality_Information

Attribute_Accuracy
    Attribute_Accuracy_Report: See Entity_Attribute_Information


    Quantitative_Attribute_Accuracy_Assessment
        Attribute_Accuracy_Value:  See Explanation
        Attribute_Accuracy_Explanation:
           Attribute accuracy is described, where present, with each
           attribute defined in the Entity and Attribute Section.


Logical_Consistency_Report: Not applicable for raster data.


Completeness_Report
 
 
 
Positional_Accuracy 
    Horizontal_Positional_Accuracy
        Horizontal_Positional_Accuracy_Report:
         
         
         




    Vertical_Positional_Accuracy
        Vertical_Positional_Accuracy_Report:
         
         
         
Lineage: See Supplemental_Information for overview.


Process_Steps
    Process_Step
    Process_Description: JON PROJECT GRID WIL_TB USGSLC92 /S1/UTIL/PROJECT/UTM10-SP
    Source_Used_Citation_Abbreviation:None
    Process_Date:  19980310 
    Process_Time:  1909
    Source_Produced_Citation_Abbreviation: None
    Process_Step
    Process_Description: KEITH   DOCUMENT USGSLC92 CREATE KEITH
    Source_Used_Citation_Abbreviation:None
    Process_Date:  19980923 
    Process_Time:  1018
    Source_Produced_Citation_Abbreviation: None


Cloud_Cover
 
 
 

Spatial_Data_Organization_Information

Direct_Spatial_Reference_Method: Raster


    Raster_Object_Information:
    Raster_Object_Type:  Grid Cell
    Row_Count:  1819
    Column_Count:  2008



Spatial_Reference_Information

Horizontal_Coordinate_System_Definition 


    Planar
        Grid_Coordinate_System
        Grid_Coordinate_System_Name: State_Plane_Coordinate_System
           Zone_Number: 5076
        Planar_Distance_Units: FEET
    Geodetic Model
        Horizontal_Datum_Name: North American Datum of 1983
        Ellipsoid_Name:  GRS1980



Entity_and_Attribute_Information

Detailed_Description 
    Entity_Type
    Entity_Type_Label: USGSLC92.VAT
    Entity_Type_Definition: Value Attribute Table
    Entity_Type_Definition_Source: Generated
    Attribute:
        Attribute_Label: -
        Attribute_Definition: Value Attribute Table
        Attribute_Definition_Source: Generated
        Attribute_Domain_Values
            Enumerated_Domain
                Enumerated_Domain_Value: -
                Enumerated_Domain_Value_Definition
                Enumerated_Domain_Value_Definition_Source:
    Attribute:
        Attribute_Label: VALUE
        Attribute_Definition: Internal feature number for GRIDs
        Attribute_Definition_Source: Computed
        Attribute_Domain_Values
            Enumerated_Domain
                Enumerated_Domain_Value: Integer
                Enumerated_Domain_Value_Definition
                Enumerated_Domain_Value_Definition_Source:
    Attribute:
        Attribute_Label: COUNT
        Attribute_Definition: Number of GRID cells of a VALUE
        Attribute_Definition_Source: Computed
        Attribute_Domain_Values
            Enumerated_Domain
                Enumerated_Domain_Value: Integer
                Enumerated_Domain_Value_Definition
                Enumerated_Domain_Value_Definition_Source:
    Entity_Type
    Entity_Type_Label: USGSLC92.STA
    Entity_Type_Definition: Statistics table
    Entity_Type_Definition_Source: GRID
    Attribute:
        Attribute_Label: -
        Attribute_Definition: Statistics table
        Attribute_Definition_Source: GRID
        Attribute_Domain_Values
            Enumerated_Domain
                Enumerated_Domain_Value: -
                Enumerated_Domain_Value_Definition
                Enumerated_Domain_Value_Definition_Source:
    Attribute:
        Attribute_Label: MIN
        Attribute_Definition: Minimum GRID cell VALUE
        Attribute_Definition_Source: Computed
        Attribute_Domain_Values
            Enumerated_Domain
                Enumerated_Domain_Value: Real number
                Enumerated_Domain_Value_Definition
                Enumerated_Domain_Value_Definition_Source:
    Attribute:
        Attribute_Label: MAX
        Attribute_Definition: Maximum GRID cell VALUE
        Attribute_Definition_Source: Computed
        Attribute_Domain_Values
            Enumerated_Domain
                Enumerated_Domain_Value: Real number
                Enumerated_Domain_Value_Definition
                Enumerated_Domain_Value_Definition_Source:
    Attribute:
        Attribute_Label: MEAN
        Attribute_Definition: Mean GRID cell VALUE
        Attribute_Definition_Source: Computed
        Attribute_Domain_Values
            Enumerated_Domain
                Enumerated_Domain_Value: Real number
                Enumerated_Domain_Value_Definition
                Enumerated_Domain_Value_Definition_Source:
    Attribute:
        Attribute_Label: STDV
        Attribute_Definition: Standard Deviation of GRID cell VALUEs
        Attribute_Definition_Source: Computed
        Attribute_Domain_Values
            Enumerated_Domain
                Enumerated_Domain_Value: Positive real number
                Enumerated_Domain_Value_Definition
                Enumerated_Domain_Value_Definition_Source:


 Overview_Description 
    Entity_and_Attribute_Overview 
    The final land cover map had a total of nine land cover
    categories.  They were;
    1. Urban
    2. Water
    3. Mature Forest
    4. Regrowth Forest
    5. Non-forest Upland
    6. Native Vegetation, Valley Floor
    7. Irrigated Crops
    8. Grass Fields, Small Grains
    9. Perennial Snow
    The categories can be further defined as follows;
    Urban - Areas of urban development as defined by the WRD
    urban mask , which was a combination of USGS GIRAS
    data and 1990 census data.  These data represent a
    population density of 1000 or more persons per square
    mile.
    Water - Open water defined by spectral classification.
    Streams may show intermittent open water due to their
    width in relation to the spatial resolution of the
    satellite data.
    Mature forest - This category represents the forested areas
    which had the darkest shades of green in the mosaic.
    Regrowth forest - This category represents the remaining
    shades of green associated with forested areas in the
    mosaic.  It was the analysts call as to the cluster
    assignment between this category and the mature
    forest.   There seemed to be logical combinations of
    clusters which defined visually similar units within
    the forested areas.
    Non-forested upland - This category represents those areas
    which did not give a green vegetation signature, and
    was separated from the same signature on the valley
    floor by elevation and slope differences.  This
    category includes recent clearcuts, open grassland, non-
    forested alpine areas, and barren areas.
    Native vegetation, valley floor- This category represents the
    vegetated areas of the valley floor which did not
    appear to be associated with agricultural activities
    and gave a vegetated signature for both dates of data,
    suggesting a natural source of water all during the
    growing season.  This category would include wetlands
    and riparian vegetation associated with streams.
    Irrigated crops - This category represents the irrigated crops as
    defined by the vegetative patterns of the June and August data.
    The basic  assumption for irrigated crops was that fields planted
    to crops requiring irrigation would be non-vegetated in
    the June image and vegetated in the August image.
    Grass fields, small grains - This category primarily represents the
    grass seed producing fields of the valley floor.  Also
    included would be the hay fields, pastures, and small grains
    of the valley.
    Perennial snow - This category represents the unmelted snow of
    the peaks of the Cascade Range as found in the August
    data.
     
    Consistency in identification of land cover was investigated by
    comparison of available data sets with the land cover map.  Following
    are two initial comparisons.
     
    Land cover, percent of basin
     
    Cover category                  1988 TM, BLM         1992 TM, NAWQA
    water                             .89                   .85
    forested                        63.32                 60.19
    non forested                    35.78                 38.96
     
     
     
    Land cover, acres by county
     
    Cover category                  1992 Ag Census      1992 TM, NAWQA
     
    Marion County
    total cropland                  242,561             248,322
     
     
    Linn County
    total cropland                  297,200             297,675
     
     
    Entity_and_Attribute_Detail_Citation: Not Available



Distribution_Information




Metadata_Reference_Section

Metadata_Date: 19980923
Metadata_Contact:
 
Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata
Metadata_Standard_Version:  19940608
Metadata_Time_Convention:  Local Time
Metadata_Security_Information:
    Metadata_Security_Classification_System:  None
    Metadata_Security_Classification:  UNCLASSIFIED
    Metadata_Security_Handling_Description:  None


Last modified: 98-09-23.10:18:59.Wed