WA_2001.img

Metadata:

• Identification_Information
• Data_Quality_Information
• Spatial_Data_Organization_Information
• Spatial_Reference_Information
• Entity_and_Attribute_Information
• Distribution_Information
• Metadata_Reference_Information

Identification_Information:

Citation:

Citation_Information:

Originator:

Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Coastal Services Center (CSC)

Publication_Date: 20041001

Title: WA_2001.img

Geospatial_Data_Presentation_Form: remote-sensing image

Publication_Information:

Publication_Place: Charleston, SC

Publisher: NOAA's Ocean Service, Coastal Services Center (CSC)

Other_Citation_Details:

This Classification is based on Landsat TM scenes p45r26 (03/21/2001), (07/16/2000), (10/18/1999) p45r27 (03/26/2000), (07/22/2002), (10/04/2000) p45r28 (03/21/2001), (07/16/2000), (08/17/2000) p46r26 (05/07/2001), (08/11/2001), (09/12/2001) p46r27 (05/31/2001), (07/07/2000), (09/25/2000) p46r28 (04/10/2000), (07/07/2000), (09/25/2000) p47r26 (02/13/2000), (07/30/2000), (10/05/2001) p47r27 (02/26/2002), (07/30/2000), (11/01/1999) p47r28 (02/26/2002), (07/01/2001), (10/16/1999) p48r26 (04/03/2001), (07/21/2000), (09/23/2000) p48r27 (04/03/2001), (07/03/2000), (09/23/2000)

Online_Linkage: \\ecyfllcyadp01\data83\images\land_cover\LandCover\WA_2001.img

Description:

Abstract:

This data set is the 2001 era or classification of Coastal Washington. This data set consists of about 33 full or partial Landsat 7 Thematic Mapper (TM)scenes which were analyzed according to the Coastal Change Analysis Program (C-CAP) protocol to determine land cover.

Purpose:

To improve the understanding of coastal uplands and wetlands, and their linkages with the distribution, abundance, and health of living marine resources.

Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date:

REQUIRED: The year (and optionally month, or month and day) for which the data set corresponds to the ground.

Range_of_Dates/Times:

Beginning_Date: 19991016

Ending_Date: 20020722

Currentness_Reference: Date of the Landsat scenes

Status:

Progress: Complete

Maintenance_and_Update_Frequency: 5 years

Spatial_Domain:

Bounding_Coordinates:

West_Bounding_Coordinate: -125.350460

East_Bounding_Coordinate: -118.505581

North_Bounding_Coordinate: 49.637952

South_Bounding_Coordinate: 45.100670

Keywords:

Theme:

Theme_Keyword_Thesaurus: ISO 19115 Topic Category

Theme_Keyword: imageryBaseMapsEarthCover

Theme:

Theme_Keyword_Thesaurus: None

Theme_Keyword: Remotely Sensed Imagery/Photos

Theme_Keyword: Land Cover Analysis

Theme_Keyword: Change Detection Analysis

Place:

Place_Keyword_Thesaurus: None

Place_Keyword: US West Coast

Place_Keyword: Coastal Zone

Place_Keyword: Washington

Access_Constraints: None, except for a possible fee.

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 distribution constitute such a warranty.

Native_Data_Set_Environment:

Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 2; ESRI ArcCatalog 9.3.1.1850

Data_Quality_Information:

Attribute_Accuracy:

Attribute_Accuracy_Report:

According to accuracy assessment performed by Space Imaging, the overall accuracy is 86.1% and 85.0% Kappa. The accuracy results shown below are from a combined accuracy completed on both Oregon and Washington C-CAP areas. A total of 1043 points are located in Washington and 1165 points are located in Oregon.
Each class accuracy is as follows: (Errors of Omission/Commission) 0 Background (N/A) 1 Unclassified (Cloud, Shadow, etc)(N/A) 2 High Intensity Developed (50%/73%) 3 Medium Intensity Developed (79%/52%) 4 Low Intensity Developed (25%/41%) 5 Open Spaces Developed (50%/100%) 6 Cultivated Land (86%/72%) 7 Pasture/Hay (77%/73%) 8 Grassland (61%/76%) 9 Deciduous Forest (95%/88%) 10 Evergreen Forest (99%/85%) 11 Mixed Forest (80%/93%) 12 Scrub/Shrub (75%/84%) 13 Palustrine Forested Wetland (75%/75%) 14 Palustrine Scrub/Shrub Wetland (68%/84%) 15 Palustrine Emergent Wetland (91%/72%) 16 Estuarine Forested Wetland (N/A) 17 Estuarine Scrub/Shrub Wetland (N/A) 18 Estuarine Emergent Wetland (93%/100%) 19 Unconsolidated Shore (90%/95%) 20 Bare Land (79%/96%) 21 Water (100%/100%) 22 Palustrine Aquatic Bed (100%/100%) 23 Estuarine Aquatic Bed (100%/100%) 24 Tundra (N/A) 25 Snow/Ice (N/A)
The validation points were both collected in the field and photo interpreted. The accuracy assessment selection methods were developed to minimize spatial autocorrelation between the training and accuracy assessment. The first pool of accuracy assessment sites came from field data and photo interpretation of black and white digital orthophotos and digital color infrared imagery (primarily Emerge and Ikonos data). These sites were collected prior to initial mapping and were collected at the same time as the training data. The sites were selected to capture the physical and spectral diversity of the land cover. After these sites were identified, they were separated into training and accuracy assessment sites by imposing a 1 km x 1 km grid over the study area. Accuracy assessment sites could only be selected from alternate 1 km squares. Only 1 sample per class was allowed from each potential square. After the first criteria was met, the accuracy assessment sites were buffered to see if they fell within 1000 meters of another accuracy assessment site of the same class or within 1000 meters of a training site of the same class. Those that fell within the 1000 meter buffer were eliminated. All sites were to be from a homogeneous 3x3 area. After an analysis of the point distribution, it became clear that there were not enough samples for every class. The remaining points were selected from the initial draft final classification and had to be a homogeneous 3x3 area. A stratified random sample was used to locate sites. These sites were restricted to the same alternate 1 km x 1 km grid that was used to separate training from AA sites in the initial analysis. Sampling was limited to areas where there was high resolution color infrared imagery. The imagery included the previous Ikonos and Emerge imagery, but also included an additional 60 scenes of Ikonos imagery. The additional Ikonos imagery provided sampling areas across the entire study area. When possible, we tried to identify 50 samples of the uncommon classes and 20 sites of the common classes. Samples were selected for the common classes so that there were samples for classes using this methodology.
In total, an additional 637 additional points to the accuracy assessment analysis for a total of 2208. All classes have a minimum of 50 accuracy assessment points except for estuarine aquatic bed and estuarine emergent. These classes have 24 and 29 sites respectively. These classes are limited in the study area and to some extent in the imagery that was available to sample from.
Also as part of the assessment, NOAA staff field tested the classification to determine a subjective goodness of fit.
Post-Processing Steps: None
Known Problems: None
Spatial Filters: None

Logical_Consistency_Report:

Tests for logical consistency indicate that all row and column positions in the selected latitude/longitude window contain data. Conversion and integration with vector files indicates that all positions are consistent with earth coordinates covering the same area. Attribute files are logically consistent.

Completeness_Report:

Data does not exist for all classes. There are no pixels representing class 13 (Estuarine Forested Wetland), class 14 (Estuarine Scrub/Shrub Wetland), or class 21 (Tundra). There are pixels for class 19 (Palustrine Aquatic Vegetation) but there were too few areas to collect accuracy assessment points. All pixels have been classified. The NOAA Coastal Change Analysis Program (C-CAP): Guidance for Regional Implementation, NOAA National Marine Fisheries Service Report 123, discusses the interagency effort to develop the land cover classification scheme and defines all categories.

Positional_Accuracy:

Horizontal_Positional_Accuracy:

Horizontal_Positional_Accuracy_Report:

Landsat scenes were georeferenced by Eros Data Center. Spatial accuracy assessed by Space Imaging is found to be to 2 pixels accuracy or less.

Vertical_Positional_Accuracy:

Vertical_Positional_Accuracy_Report:

There was no terrain correction in the geo-referencing procedure.

Lineage:

Source_Information:

Source_Citation:

Citation_Information:

Originator: Space Imaging

Publication_Date: 20041001

Title: C-CAP Classification for Washington Coastal Zone,

Geospatial_Data_Presentation_Form: remote-sensing image

Publication_Information:

Publication_Place: Charleston SC

Publisher: NOAA Coastal Services Center

Online_Linkage: <http://www.csc.noaa.gov/>

Type_of_Source_Media: CD-ROM

Source_Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 19991016

Ending_Date: 20020226

Source_Currentness_Reference: 20020226

Source_Citation_Abbreviation: NOAA CSC

Source_Contribution: NOAA CSC

Process_Step:

Process_Description:

This dataset was created by Space Imaging. This version of the classification is the (2001-era). The study area is the Coastal Washington Region. An (1995-era) classification is also available for the same area.
Summary: This section outlines the classification procedure for the Oregon C-CAP. The three dates of imagery were first reviewed for image quality and shifts between image dates. Training points were used as the dependent variable in a CART (Classification Analysis by Regression Tree) approach. Ancillary data layers were calculated from the TM data and were used as additional independent variables in the analysis. Different versions of the map were produced using different combinations of independent variables. The rough map represented the output from the CART classification routine. Ancillary data were used in spatial models were applied to the rough map to produce the provisional map. This represented a fully automated product. This product was then altered by hand edits to refine the classification. In addition, a percent impervious data layer developed from TM data using high resolution imagery, was imbedded into the classification to define the developed classes. This produced the final-with-edits version which is the final version of the classification and is the one described here.
Pre-processing steps: Each Landsat TM scene was geo-referenced by USGS (United States Geological Survey) EROS Data Center. The Space Imaging staff reviewed the spectral and spatial quality of the imagery. Areas that were greater than 1-2 pixels off were sent back to USGS for reprocessing. The data was geo-referenced to Albers Conical Equal Area, with a spheroid of GRS 1980, and Datum of WGS84. The data units is in meters. The Washington TM data was delivered in the form of USGS zone mosaics. The data included three dates of TM: leaf-on, leaf-off, and spring. For each date of TM, spectral and tasseled cap data were received.
Field-Collected Data: The goals of the field data collection were to sample the diversity of the landscape, within the classes, and among image dates. Classes that would be more difficult to collect from air photos were targeted for field data collection. To meet these goals, Space Imaging stratified the image into spectral clusters and located the field sites throughout the study area based on these. In addition to these pre-arranged sites, Space Imaging collected points while driving between locations. Due to limited time and accessibility, not all polygons were assessed in the field. Those that we did not visit on the ground were labeled with digital orthophotographs or Emerge data if it was available. Both training and validation points were collected together. See the accuracy assessment section to see how the points were split into training and validation points.
Space Imaging used laptop computers and GPS (Global Positioning System)to correctly locate field points on the TM imagery. Software downloaded from the Minnesota's Department of Natural Resources (DNR)was used to connect the Garmin GPS to the laptop (<http://www.dnr.state.mn.us/mis/gis/tools/arcview/extensions/DNRGarmin/DNRGarmin.html>) computer and ESRI's ArcView software. Space Imaging's programmer developed an ArcView application that allowed entry of location and field notes with a click of the mouse. These data were stored in a shape file. The items that were collected were: Land Cover characterization Special conditions and remarks Photograph Number Date/time X,Y location
The data and equipment used for the fieldwork are as follows: Ancillary datasets: TIGER 2000 NLCD NWI - mosaicked into zones State road map and Delorme state atlas www.delorme.com
Hardware: Lap-tops with ArcView and data GARMIN GPS modules and external antennae, redundant data cables Cameras Backup devices (Floppy Drives) Extra batteries (lap-top and GPS) Mobile phones System backup CD's with data and software Compass Binoculars Field notebooks with instructions and road maps with pre-determined routes Wetland and Vegetation Field Guides
Imagery: Multi-spectral data for each zone Initial classifications
Classification: After the field points for training were collected, they were combined with photo-interpreted points and used as the dependent variable in a CART classification approach. Many layers tested as independent layers. They included three dates of spectral and tasseled cap imagery, DEM, slope, aspect, texture, band indices (NDVI, Moisture, NDVI-Green), shape indices fractal dimension, compactness, convexity, and form), Census data (housing and population density). Statistical analyses and visual inspection of the output was used to eliminate data that was redundant or not useful in the classification. Additional training points were added to help reduce some of the confusion between classes. The rough classification was created at the end of this process using only the CART discrete decision-tree software. A provisional classification was produced by applying spatial models using ancillary data to the rough classification. The provisional map was then edited using hand editing techniques while using high resolution imagery from as reference data. Independently, of this process, Space Imaging produced percent impervious data layers for Washington. This layer was developed from Regression Tree and used impervious classifications from IKONOS imagery to predict pixel level percent impervious at the TM pixel level. The continuous percent impervious data was thresholded to produce the to developed categories and imbedded into the final map.
Attributes for this product are as follows: 0 Background 1 Unclassified (Cloud, Shadow, etc) 2 High Intensity Developed 3 Medium Intensity Developed 4 Low Intensity Developed 5 Open Space Developed 6 Cultivated Land 7 Pasture/Hay 8 Grassland 9 Deciduous Forest 10 Evergreen Forest 11 Mixed Forest 12 Scrub/Shrub 13 Palustrine Forested Wetland 14 Palustrine Scrub/Shrub Wetland 15 Palustrine Emergent Wetland 16 Estuarine Forested Wetland 17 Estuarine Scrub/Shrub Wetland 18 Estuarine Emergent Wetland 19 Unconsolidated Shore 20 Bare Land 21 Water 22 Palustrine Aquatic Bed 23 Estuarine Aquatic Bed 24 Tundra 25 Snow/Ice
Ancillary Datasets: Non-TM image datasets used are DEM (Digital Elevation Model), slope, aspect, positional index, NWI, NLCD, TIGER2000, field-collected points, photo-interpreted points, Washington (Gap Analysis Program), Census data (housing and population density), Ecoregions, IVMP (Interagency Vegetation Mapping Program), Washington Coastal Atlas, Washington ShoreZone Inventory Data.
QA/QC Process: There were several QA/QC steps involved in the creation of this product. First, there was an internal QA/QC. This was done by viewing the classification frame- by-frame along with the TM imagery, the classification, and high resolution reference imagery. NOAA staff completed a similar review and provided both general and point comments.
Post-Processing Steps: Both Washington and Oregon zones were classified concurrently but independently. When they were completed, they were edgematched to each other.

Process_Date: 20021001 - 20041001

Process_Contact:

Contact_Information:

Contact_Person_Primary:

Contact_Person: CRS (Coastal Remote Sensing) Program Manager

Contact_Organization:

NOAA Coastal Services Center Coastal Change Analysis Program (C-CAP)

Contact_Position: CRS Program Manager

Contact_Address:

Address_Type: mailing and physical address

Address: 2234 S. Hobson Ave.

City: Charleston

State_or_Province: SC

Postal_Code: 29405

Country: USA

Contact_Voice_Telephone: 843-740-1210

Contact_Facsimile_Telephone: 843-740-1224

Contact_Electronic_Mail_Address: clearinghouse@csc.noaa.gov

Hours_of_Service: 8:00 am to 5:00 p.m. EST. M-F

Process_Step:

Process_Description: Classification

Process_Date: Unknown

Process_Contact:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization:

NOAA Coastal Services Center Coastal Change Analysis Program (C-CAP)

Contact_Position: CRS Program Manager

Contact_Address:

Address_Type: mailing and physical address

Address: 2234 S. Hobson Ave.

City: Charleston

State_or_Province: SC

Postal_Code: 29405

Country: USA

Contact_Voice_Telephone: 843-740-1210

Contact_Facsimile_Telephone: 843-740-1224

Contact_Electronic_Mail_Address: csc@csc.noaa.gov

Hours_of_Service: Monday to Friday, 8 a.m. to 5 p.m., Eastern Standard Time

Process_Step:

Process_Description: Metadata imported.

Source_Used_Citation_Abbreviation: C:\Temp\xml33.tmp

Process_Date: 20090820

Process_Time: 10392500

Spatial_Data_Organization_Information:

Direct_Spatial_Reference_Method: Raster

Raster_Object_Information:

Raster_Object_Type: Pixel

Row_Count: 16488

Column_Count: 16519

Vertical_Count: 1

Spatial_Reference_Information:

Horizontal_Coordinate_System_Definition:

Planar:

Map_Projection:

Map_Projection_Name: Lambert Conformal Conic

Lambert_Conformal_Conic:

Standard_Parallel: 45.833333

Standard_Parallel: 47.333333

Longitude_of_Central_Meridian: -120.500000

Latitude_of_Projection_Origin: 45.333333

False_Easting: 1640416.666667

False_Northing: 0.000000

Planar_Coordinate_Information:

Planar_Coordinate_Encoding_Method: row and column

Coordinate_Representation:

Abscissa_Resolution: 98.425000

Ordinate_Resolution: 98.425000

Planar_Distance_Units: survey feet

Geodetic_Model:

Horizontal_Datum_Name: D_North_American_1983_HARN

Ellipsoid_Name: Geodetic Reference System 80

Semi-major_Axis: 6378137.000000

Denominator_of_Flattening_Ratio: 298.257222

Entity_and_Attribute_Information:

Detailed_Description:

Entity_Type:

Entity_Type_Label: WA_2001.img.vat

Entity_Type_Definition:

US West Coast coastal zone as delineated by NOAA using scene boundaries, hydrological units, and county boundaries

Entity_Type_Definition_Source: unknown

Attribute:

Attribute_Label: OID

Attribute_Definition: Internal feature number.

Attribute_Definition_Source: ESRI

Attribute_Domain_Values:

Unrepresentable_Domain:

Sequential unique whole numbers that are automatically generated.

Attribute:

Attribute_Label: Value

Attribute:

Attribute_Label: Count

Attribute:

Attribute_Label: Red

Attribute:

Attribute_Label: Green

Attribute:

Attribute_Label: Blue

Attribute:

Attribute_Label: Opacity

Attribute:

Attribute_Label: Class_name

Distribution_Information:

Distributor:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization: NOAA Coastal Services Center

Contact_Person: Clearinghouse Manager

Contact_Position: Clearinghouse Manager

Contact_Address:

Address_Type: mailing and physical address

Address: 2234 South Hobson Avenue

City: Charleston

State_or_Province: SC

Postal_Code: 29405-2413

Country: USA

Contact_Voice_Telephone: (843)740-1210

Contact_Facsimile_Telephone: (843)740-1224

Contact_Electronic_Mail_Address: clearinghouse@csc.noaa.gov

Hours_of_Service: Monday-Friday, 8-5 EST

Resource_Description: Downloadable Data

Distribution_Liability:

Users must assume responsibility to determine the usability of these data.

Standard_Order_Process:

Digital_Form:

Digital_Transfer_Information:

Format_Name: ERDAS Imagine image file (.img)

Transfer_Size: 0.000

Digital_Transfer_Option:

Offline_Option:

Offline_Media: CD-ROM

Recording_Format: ISO 9660

Compatibility_Information:

ISO 9660 format allows the CD-ROM to be read by most computer operating systems.

Fees: none

Metadata_Reference_Information:

Metadata_Date: 20091006

Metadata_Review_Date: 20090701

Metadata_Contact:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization: NOAA Coastal Services Center

Contact_Person: Metadata Specialist

Contact_Position: Metadata Specialist

Contact_Address:

Address_Type: mailing and physical address

Address: 2234 S Hobson Ave.

City: Charleston

State_or_Province: SC

Postal_Code: 29405

Country: USA

Contact_Voice_Telephone: 843-740-1210

Contact_Facsimile_Telephone: 843-740-1224

Contact_Electronic_Mail_Address: csc@csc.noaa.gov

Hours_of_Service: 8:00 am to 5:00 pm EST.

Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata

Metadata_Standard_Version: FGDC-STD-001-1998

Metadata_Time_Convention: local time

Metadata_Extensions:

Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>

Profile_Name: ESRI Metadata Profile