Land_Cover -- National Land Cover Dataset

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Metadata:


Identification_Information:
Citation:
Citation_Information:
Originator: U.S. Geological Survey EROS Data Center, Sioux Falls, SD.
Publication_Date: 2000
Title: Land_Cover -- National Land Cover Dataset
Geospatial_Data_Presentation_Form: remote-sensing image
Other_Citation_Details: MRLC Regional Land Cover Characterization Project
Online_Linkage: <http://www.epa.gov/mrlc/nlcd.html>
Description:
Abstract:
This raster spatial layer contains land cover information from the 1992 National Land Cover Dataset (NLCD) and was constructed to show land cover and land use in the upper Washita River basin in southwestern Oklahoma. The 1992 NLCD was designed primarily for analysis at the state or multistate level and should be used with caution when evaluating smaller areas.

The associated tabular file "LandCover_key" contains the land cover class definitions. This table can be related using the attribute "VALUE".

Purpose:
To provide land cover information for users working in the upper Washita River basin.
Supplemental_Information:
The base data set was leaves-off Landsat Thematic Mapper (TM) data, nominal-1992 acquisitions. Other ancillary data layers included leaves-on TM, USGS 3-arc second Digital Terrain Elevation Data (DTED) and derived slope, aspect and shaded relief, Bureau of the Census population and housing density data, USGS land use and land cover (LUDA), and National Wetlands Inventory (NWI) data, if available.

The analysis and interpretation of the satellite imagery was conducted using very large, sometimes multi-state image mosaics (up to 18 Landsat scenes). Using a relatively small number of aerial photographs for "ground truth", the thematic interpretations were necessarily conducted from a spatially broad perspective. Furthermore, the accuracy assessments correspond to "federal regions", which are groupings of contiguous states. Thus, the reliability of the data is greatest at the state or multi-state level. The statistical accuracy of the data is known only for the region.

Additional information about the National Land Cover Dataset (NLCD) can found at URL: <http://www.epa.gov/mrlc/nlcd.html>

These data can be used in a geographic information system (GIS) for many purposes such as assessing wildlife habitat, water quality, pesticide runoff, and land use change.

Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 1992
Currentness_Reference: 1992
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None planned
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -99.401273
East_Bounding_Coordinate: -97.712744
North_Bounding_Coordinate: 35.933590
South_Bounding_Coordinate: 34.742288
Keywords:
Theme:
Theme_Keyword: Land cover
Access_Constraints: None
Use_Constraints:
Users are cautioned who intend to apply the data to highly localized studies, such as over a small urban-suburban setting or a watershed of only tens of square miles. The land cover data quality of such a small geographic extent is unknown and the users should carefully examine the NLCD product in the local context to determine utility.
Point_of_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Carol Becker
Contact_Organization: U.S. Geological Survey
Contact_Position: Hydrologist
Contact_Address:
Address_Type: mailing address
Address: 202 NW 66th, bldg. 7
City: Oklahoma City
State_or_Province: OK
Postal_Code: 73116
Contact_Voice_Telephone: 405 810-4400
Contact_Electronic_Mail_Address: cjbecker@usgs.gov
Native_Data_Set_Environment:
Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 2; ESRI ArcCatalog 9.1.0.780

Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
An accuracy assessment was conducted on the NLCD by private sector vendors under contract to the USEPA. A protocol has been established by the USGS and USEPA that incorporates a two-stage, geographically stratified cluster sampling plan utilizing National Aerial Photography Program (NAPP) photographs as the sampling frame and the basic sampling unit. In this design a NAPP photograph is defined as a primary sampling unit (PSU), and a sampled pixel within each PSU is treated as a secondary sampling unit (SSU).

PSUs are selected from a sampling grid based on NAPP flight lines and photograph centers, each grid cell measures 15' x 15' (minutes of latitude and longitude) and consists of 32 photographs from the National High Altitude Program (NHAP). A geographically stratified random sampling is performed with one photograph from the National Aerial Photography Program photo being randomly selected from each cell (geographic strata), if a sampled photograph falls outside of the regional boundary it is not used. Second stage sampling is accomplished by selecting SSUs (pixels) within each PSU (NAPP photograph) to provide the actual locations for the reference land cover classification.

The SSUs are manually interpreted and misclassification errors are estimated and described using a traditional error matrix as well as a number of other important measures including the overall proportion of pixels correctly classified, user's and producer's accuracies, and omission and commission error probabilities.

Major factors that have contributed to disagreements between mapped land cover and reference land cover labels include:

1) Landsat TM data quality and mapping error, 2) time difference in source imagery and reference data acquisition (hay/pasture, row crop, wetland, transitional), 3) definition related to land use (high intensity residential and urban built-up, and the two barren classes), and 4) spatial uncertainty, such as geo-registration error.

An example of mapping error is the limited success in discriminating hay/pasture from row crops using leaf-off season (spring or fall) Landsat TM data. The data analyst assumes that there is a temporal window during which hay and pasture green up before most other annual or perennial vegetation. However, if leaf-off data acquisition is not temporally ideal (e.g., the greenness level of hay/pasture areas is low), it may result in misclassification between hay/pasture and other agricultural lands.

Another source of error is the discrepancy between satellite imagery and NAPP photograph acquisition time. Acquisition dates of the NAPP photographs range from the late 1980s to 1997, whereas the satellite data were mostly acquired from 1991 to 1993. Any changes that took place across the landscape over this time period complicate interpretation and comparison between reference and mapped land cover. One class that suffers most is the transitional barren, a class that is designed for conditions such as temporary clearing and regeneration of forest cover. Similar problems exist within agricultural classes due to crop rotations.

Low accuracy for classes related to land use is understandable. Despite the extensive use of ancillary data, such as the census data, it is very difficult to unambiguously separate high intensity residential from other urban uses, either during the mapping or photo-interpretation process. The same is true for the land use related differences between the quarry/strip mine class and the sandy/gravel class.

Logical_Consistency_Report:
An unsupervised classification algorithm was used to classify leaf-off TM scenes. Aerial photographs were used to interpret and label classes into land cover categories and ancillary data sources resolved the class confusion. Further land cover information from leaf-on TM data, National Wetlands Inventory data, and other sources were incorporated to refine and augment the "basic" classification.
Completeness_Report:
The methods used to create the NLCD have resulted in a good general land cover classification product for the nation, it is important to indicate to the user where there might be potential problems. The biggest concerns are described in the following text:

1) Some of the TM data sets are not temporally ideal. Leaves-off data sets are used for discriminating between hay/pasture and row crops, and for discriminating between deciduous, coniferous, and mixed forest classes. The success of discriminating between these classes using leaves-off data sets depends on the time of data acquisition. When hay and pasture areas are non-green, those areas not easily distinguishable from other agricultural areas using remotely sensed data. However, there is a temporal window during which hay and pasture areas green up before most other vegetation (excluding evergreens, which have different spectral properties); during this window these areas are easily distinguishable from other crop areas. The discrimination between hay and pasture and deciduous forest is likewise optimized by selecting data in a temporal window where deciduous vegetation has yet to leaf out. It is difficult to acquire a single-date of imagery (leaves-on or leaves-off) that adequately differentiates between both deciduous and hay/pasture and hay/pasture and row crops.

2) The data sets used cover a range of years (see data sources), so changes that have occurred across the landscape over the time period may not have been captured. While this is not viewed as a major problem for most classes, it is possible that some land cover features change more rapidly than might be expected (for example, hay one year, row crop the next). More information about the NLCD can be found at URL: <http://landcover.usgs.gov/nationallandcover.html>

3) Wetlands classes are extremely difficult to extract from Landsat TM spectral information alone. The use of ancillary information such as National Wetlands Inventory data is highly desirable. Much emphasis was put on GAP, LUDA, or proximity to streams and rivers as well as spectral data to delineate wetlands in areas without NWI data.

4) Separation of natural grass and shrub is problematic. Areas observed on the ground to be shrub or grass are not always distinguishable spectrally. Likewise, there was often disagreement between LUDA and the Gap Analylsis Program on these classes.

Selected References:

Cowardin, L.M., Carter, V., Golet, F.C., and LaRoe, E.T., 1979, Classification of wetlands and deepwater habitats of the United States: U.S. Fish and Wildlife Service, Department of the Interior, Washington, D.C., 191 p.

Kelly, P.M. and White, J.M., 1993, Preprocessing remotely sensed data for efficient analysis and classification, Applications of Artificial Intelligence 1993: Knowledge-Based Systems in Aerospace and Industry, Proceeding of SPIE, 1993, p. 24-30.

Vogelmann, J.E., Sohl, T., and Howard, S.M., 1998, Regional characterization of land cover using multiple sources of data: Photogrammetric Engineering and Remote Sensing, v. 64, no. 1, p. 45-57.

Vogelmann, J.E., Sohl, T., Campbell, P.V., and Shaw, D.M., 1998, Regional land cover characterization using landsat thematic mapper data and ancillary data sources: Environmental Monitoring and Assessment, v. 51, pp. 415-428.

Zhu, Z.hiliang, Yang, Limin., Stehman, S.V., and Czaplewski, R.L., 1999, Accuracy assessment for the U.S. Geological Survey regional land cover mapping program: New York and New Jersey Region: Photogrammetric Engineering and Remote Sensing 66:1425-1435.

Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report:
Each Landsat TM image used to create the NLCD was precision terrain-corrected using 3-arc-second digital terrain elevation data (DTED), and georegistered using ground control points. This resulted in a root mean square registration error of less than 1 pixel (30 meters).
Lineage:
Source_Information:
Source_Contribution:
Questions about the data set can be directed to the MRLC Regional Team at (605) 594-6114 or mrlc@edcmail.cr.usgs.gov.
Process_Step:
Process_Description:
The 1992 NLCD for the State of Oklahoma was downloaded from <http://www.mrlc.gov/> .

The raster spatial layer was projected and land cover information was selected using the 8-digit hydrologic unit code (HUC8) and the ARC/INFO GRIDCLIP command. The land cover values were reclassified and numbered 1 to 20. The spatial layer was imported in the geodatabase and metadata written.

Process_Date: 2006
Process_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Jason Masoner
Contact_Organization: U.S. Geological Survey
Contact_Address:
Address_Type: 202 NW 66th, bldg. 7
City: Oklahoma City
State_or_Province: OK
Postal_Code: 73116
Contact_Voice_Telephone: 405 810-4436

Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Raster
Raster_Object_Information:
Raster_Object_Type: Pixel
Row_Count: 4313
Column_Count: 4958
Vertical_Count: 1

Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Planar:
Map_Projection:
Map_Projection_Name: Albers Conical Equal Area
Albers_Conical_Equal_Area:
Standard_Parallel: 29.500000
Standard_Parallel: 45.500000
Longitude_of_Central_Meridian: -96.000000
Latitude_of_Projection_Origin: 23.000000
False_Easting: 0.000000
False_Northing: 0.000000
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: row and column
Coordinate_Representation:
Abscissa_Resolution: 30.000000
Ordinate_Resolution: 30.000000
Planar_Distance_Units: meters
Geodetic_Model:
Horizontal_Datum_Name: North American Datum of 1983
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: Band_1
Attribute:
Attribute_Label: ObjectID
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_Definition:
Land cover value. See file 'LandCover_key' for value descriptions
Attribute_Definition_Source: U.S. Geological Survey
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 1
Enumerated_Domain_Value_Definition: Open water
Enumerated_Domain:
Enumerated_Domain_Value: 3
Enumerated_Domain_Value_Definition: Low-intensity residential
Enumerated_Domain:
Enumerated_Domain_Value: 4
Enumerated_Domain_Value_Definition: High-intensity residential
Enumerated_Domain:
Enumerated_Domain_Value: 5
Enumerated_Domain_Value_Definition: Commercial/Industrial/Transportation
Enumerated_Domain:
Enumerated_Domain_Value: 6
Enumerated_Domain_Value_Definition: Bare rock/sand/clay
Enumerated_Domain:
Enumerated_Domain_Value: 7
Enumerated_Domain_Value_Definition: Quarries/strip mines/gravel pits
Enumerated_Domain:
Enumerated_Domain_Value: 8
Enumerated_Domain_Value_Definition: Transitional
Enumerated_Domain:
Enumerated_Domain_Value: 9
Enumerated_Domain_Value_Definition: Deciduous forest
Enumerated_Domain:
Enumerated_Domain_Value: 10
Enumerated_Domain_Value_Definition: Evergreen forest
Enumerated_Domain:
Enumerated_Domain_Value: 11
Enumerated_Domain_Value_Definition: Mixed forest
Enumerated_Domain:
Enumerated_Domain_Value: 12
Enumerated_Domain_Value_Definition: Shrubland
Enumerated_Domain:
Enumerated_Domain_Value: 13
Enumerated_Domain_Value_Definition: Grasslands/herbaceous
Enumerated_Domain:
Enumerated_Domain_Value: 14
Enumerated_Domain_Value_Definition: Pasture/Hay
Enumerated_Domain:
Enumerated_Domain_Value: 15
Enumerated_Domain_Value_Definition: Row crops
Enumerated_Domain:
Enumerated_Domain_Value: 16
Enumerated_Domain_Value_Definition: Small grains
Enumerated_Domain:
Enumerated_Domain_Value: 18
Enumerated_Domain_Value_Definition: Urban/recreational grasses
Enumerated_Domain:
Enumerated_Domain_Value: 19
Enumerated_Domain_Value_Definition: Woody wetlands
Enumerated_Domain:
Enumerated_Domain_Value: 20
Enumerated_Domain_Value_Definition: Emergent herbaceous wetlands
Attribute:
Attribute_Label: Count
Attribute_Definition: Pixel counts
Attribute_Definition_Source: Computed
Overview_Description:
Entity_and_Attribute_Overview:
The tabular file "LandCover_key" contains land cover class definitions and can be related to this file using the attribute "VALUE".

NOTE - All classes may NOT be represented in a specific state data set.

The class numbers shown below represent the original digital values of the classes in the NLCD data set. The class numbers were assigned to numbers from 1 to 20.

1. Open Water - areas of open water, generally with less than 25 percent or greater cover of water (per pixel).

3. Low Intensity Residential - Includes areas with a mixture of constructed materials and vegetation. Constructed materials account for 30 to 80 percent of the cover. Vegetation may account for 20 to 70 percent of the cover. These areas most commonly include single-family housing units. Population densities will be lower than in high intensity residential areas.

4. High Intensity Residential - Includes heavily built up urban centers where people reside in large numbers. Examples include apartment complexes and row houses. Vegetation accounts for less than 20 percent of the cover. Constructed materials account for 80 to 100 percent of the cover.

5. Commercial, Industrial, or Transportation - Includes infrastructure (roads, railroads) and all highways and all developed areas not classified as High Intensity Residential.

6. Bare Rock, Sand, or Clay - Perennially barren areas of bedrock, desert, pavement, scarps, talus, slides, volcanic material, glacial debris, and other accumulations of earthen material.

7. Quarries, Strip Mines, or Gravel Pits - Areas of extractive mining activities with significant surface expression.

8. Transitional - Areas of sparse vegetative cover (less than 25 percent that are dynamically changing from one land cover to another, often because of land use activities. Examples include forest clearcuts, a transition phase between forest and agricultural land, the temporary clearing of vegetation, and changes due to natural causes (such as fire or flood).

9. Deciduous Forest - Areas dominated by trees where 75 percent or more of the tree species shed foliage simultaneously in response to seasonal change.

10. Evergreen Forest - Areas characterized by trees where 75 percent or more of the tree species maintain leaves all year. Canopy is never without green foliage.

11. Mixed Forest - Areas dominated by trees where neither deciduous nor evergreen species represent more than 75 percent of the cover present.

12. Shrubland - Areas dominated by shrubs; shrub canopy accounts for 25 to 100 percent of land cover. Shrub cover is generally greater than 25 percent when tree cover is less than 25 percent. Shrub cover may be less than 25 percent in cases when the cover of other herbaceous or tree cover is less than 25 percent.

13. Grasslands or Herbaceous - Areas dominated by upland grasses and forbs. In rare cases, herbaceous cover is less than 25 percent, but exceeds the combined cover of the woody species present. These areas are not subject to intensive management, but are often utilized for grazing.

14. Pasture or Hay - Areas of grasses, legumes, or grass-legume mixtures planted for livestock grazing or the production of seed or hay crops.

15 Row Crops - Areas used for the production of crops, such as corn, soybeans, vegetables, tobacco, and cotton.

16. Small Grains - Areas used for the production of graminoid crops such as wheat, barley, oats, and rice.

18. Urban or Recreational Grasses - Vegetation (primarily grasses) planted in developed settings for recreation, erosion control, or aesthetic purposes. Examples include parks, lawns, golf courses, airport grasses, and industrial site grasses.

19. Woody Wetlands - Areas where forest or shrubland vegetation accounts for 25 to 100 percent of the cover and the soil or substrate is periodically saturated with or covered with water.

20. Emergent Herbaceous Wetlands - Areas where perennial herbaceous vegetation accounts for 75 to 100 percent of the cover and the soil or substrate is periodically saturated with or covered with water.


Distribution_Information:
Resource_Description: Downloadable Data
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Transfer_Size: 0.000

Metadata_Reference_Information:
Metadata_Date: 20070208
Metadata_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: U.S. Geological Survey
Contact_Person: Carol Becker
Contact_Address:
Address_Type: mailing address
Address: 202 NW 66th, bldg. 7
City: Oklahoma City
State_or_Province: OK
Postal_Code: 73116
Contact_Voice_Telephone: 405 810-4400
Contact_Electronic_Mail_Address: cjbecker@usgs.gov
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

Generated by mp version 2.8.6 on Thu Feb 08 16:07:51 2007