NLCD Tree Canopy (Analytical), New York, 2011

This is a human-readable view of the FGDC XML metadata.


static map preview

Identification_Information

Citation:
Citation_Information:
Publication_Date: 20160131
Title: NLCD Tree Canopy (Analytical), New York, 2011
Edition: 2011 Edition
Geospatial_Data_Presentation_Form: raster digital data
Series_Information:
Series_Name: National Land Cover Database
Issue_Identification: 2011 Tree Canopy (Analytical)
Publication_Information:
Publication_Place:
Publisher: U.S. Geological Survey
Other_Citation_Details: References: Benton et al., (In Preparation). A strategy for estimating tree canopy cover using Landsat 5 Thematic Mapper (TM) images over large areas. Brand, Gary J.; Nelson, Mark D.; Wendt, Daniel G.; Nimerfro, Kevin K. 2000. The hexagon/panel system for selecting FIA plots under an annual inventory. In: McRoberts, Ronald E.; Reams, Gregory A.; Van Deusen, Paul C., eds. Proceedings of the First Annual Forest Inventory and Analysis Symposium; Gen. Tech. Rep. NC-213. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Research Station: 8-13. Breiman, L. 2001. Random forests. Machine Learning 45:15-32. Chander, G.; Markham, B.L.; Helder, D.L. 2009. Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of Environment 113(2009): 893-903. Chavez, P.S. 1988. An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data. Remote Sensing of Environment 24(1988): 459-479. Coulston, John W.; Jacobs, Dennis M.; King, Chris R.; Elmore, Ivey C. 2013. The influence of multi-season imagery on models of canopy cover: a case study. Photogrammetric Engineering & Remote Sensing 79(5):469-477. Coulston, John W.; Moisen, Gretchen G.; Wilson, Barry T.; Finco, Mark V.; Cohen, Warren B.; Brewer, C. Kenneth. 2012. Modeling percent tree canopy cover: a pilot study. Photogrammetric Engineering & Remote Sensing 78(7): 715-727. Cutler, R.D.; Edwards, T.C.; Beard, K.H.; Cutler, A.; Hess, K.T.; Gibson, J.; Lawler, J.J. 2007. Random forest for classification in ecology. Ecology 88 (11):2783-2792. Huang, C.; Yang, L.; Wylie, B.; Homer, C. 2001. A strategy for estimating tree canopy density using Landsat 7 ETM+ and high resolution images over large areas. In: Third International Conference on Geospatial Information in Agriculture and Forestry; November 5-7, 2001; Denver, Colorado. CD-ROM, 1 disk. Moisen, Gretchen G.; Coulston, John W.; Wilson, Barry T.; Cohen, Warren B.; Finco, Mark V. 2012. Choosing appropriate subpopulations for modeling tree canopy cover nationwide. In: McWilliams, Will; Roesch, Francis A., eds. 2012. Monitoring Across Borders: 2010 Joint Meeting of the Forest Inventory and Analysis (FIA) Symposium and the Southern Mensurationists. e-Gen. Tech. Rep. SRS-157. Asheville, NC: US Department of Agriculture, Forest Service, Southern Research Station: 195-200. Tipton, John; Moisen, Gretchen; Patterson, Paul; Jackson, Thomas A.; Coulston, John. 2012. Sampling intensity and normalizations: Exploring cost-driving factors in nationwide mapping of tree canopy cover. In: McWilliams, Will; Roesch, Francis A., eds. 2012. Monitoring Across Borders: 2010 Joint Meeting of the Forest Inventory and Analysis (FIA) Symposium and the Southern Mensurationists. e-Gen. Tech. Rep. SRS-157. Asheville, NC: US Department of Agriculture, Forest Service, Southern Research Station: 201-208. Zhu, Z.; Woodcock, C.E. 2012. Object-based cloud and cloud shadow detection in Landsat imagery. Remote Sensing of Environment. 118(2012): 83-94.
Online_Linkage: https://cugir.library.cornell.edu/catalog/cugir-009007
Larger_Work_Citation:
Citation_Information:
Publication_Date: 20160131
Title: NLCD 2011
Edition: 4.0
Geospatial_Data_Presentation_Form: raster digital data
Series_Information:
Series_Name: none
Issue_Identification: none
Publication_Information:
Publication_Place:
Publisher: U.S. Geological Survey
Other_Citation_Details: References: Fry, J.; Xian, G.; Jin, S.; Dewitz, J.; Homer, C.; Yang, L.; Barnes, C.; Herold, N.; Wickham, J. 2011. Completion of the 2006 National Land Cover Database for the conterminous United States, Photogrammetric Engineering & Remote Sensing 77(9):858-864. Homer, C.; Gallant, A. 2001. Partitioning the conterminous United States into mapping zones for Landsat TM land cover mapping, USGS Draft White Paper. http://landcover.usgs.gov/pdf/homer.pdf Homer, C.; Huang, C.; Yang, L.; Wylie, W.; Coan, M. 2004. Development of a 2001 National Land-Cover Database for the United States. Photogrammetric Engineering & Remote Sensing 70(7): 829-840.
Description:
Abstract: The National Land Cover Database 2011 (NLCD2011) percent tree canopy cover (TCC 2011) layer was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium (www.mrlc.gov). The MRLC Consortium is a partnership of federal agencies, consisting of the U.S. Geological Survey, the National Oceanic and Atmospheric Administration, the U.S. Environmental Protection Agency, the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service, the U.S. Forest Service, the National Park Service, the U.S. Fish and Wildlife Service, the Bureau of Land Management, NASA, and the U.S. Army Corps of Engineers. One of the primary goals of the project was to generate a current, consistent, and seamless national land cover, percent tree canopy cover, and percent impervious cover at medium spatial resolution. TCC 2011 is the NLCD tree canopy cover dataset for CONUS at medium spatial resolution (30 m). It was produced by the USDA Forest Service Remote Sensing Applications Center (RSAC). The TCC 2011 dataset has two layers: percent tree canopy cover and standard error. For the tree canopy cover layer, the pixel values range from 0 to 100 percent. For the standard error layer, the pixel values range from 0 to 45 percent. The standard error represents the model uncertainty associated with the corresponding pixel in the tree canopy cover layer. The tree canopy cover layer was produced using a Random Forests™ regression algorithm and the standard error layer was calculated from the variance of the canopy cover estimates from the random forest regression trees.
Purpose: The goal of this project is to provide the Nation with complete, current and consistent public domain information on its tree canopy cover.
Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2011
Currentness_Reference: Ground condition
Status:
Maintenance_and_Update_Frequency: As needed
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -80.035689
East_Bounding_Coordinate: -70.516534
North_Bounding_Coordinate: 45.847801
South_Bounding_Coordinate: 40.086438
Keywords:
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: Percent Tree Canopy
Theme_Keyword: Tree Canopy Cover
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Category
Theme_Keyword: ImageryBaseMapEarthCover
Theme_Keyword: environment
>
Theme:
Theme_Keyword_Thesaurus: CUGIR Category
Theme_Keyword: environment
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: New York
Access_Constraints: None
Use_Constraints: Any hardcopy or electronic products utilizing these datasets will clearly indicate their source. If the user has modified the data in any way, they are obligated to describe the types of modifications they have performed. User specifically agrees not to misrepresent these data sets, nor to imply that the MRLC approved the changes. Any data downloaded must be properly cited.
Point_of_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: U.S. Geological Survey
Contact_Position: Customer Services Representative
Contact_Address:
Address_Type: mailing and physical
Address: USGS/EROS
Address: 47914 252nd Street
City: Sioux Falls
State_or_Province: SD
Postal_Code: 57198-0001
Country: US
Contact_Voice_Telephone: 605/594-6151
Contact_TDD/TTY_Telephone: 605/594-6933
Contact_Facsimile_Telephone: 605/594-6589
Contact_Electronic_Mail_Address: custserv@usgs.gov
Hours_of_Service: 0800 - 1600 CT, M - F (-6h CST/-5h CDT GMT)
Contact_Instructions: The USGS point of contact is for questions relating to the data display and download from this web site. For questions regarding data content and quality, refer to: http://www.mrlc.gov/mrlc2k.asp or email: mrlc@usgs.gov
Browse_Graphic:
Browse_Graphic_File_Name: https://cugir-data.s3.amazonaws.com/00/90/07/preview.png
Browse_Graphic_File_Description: preview of the dataset
Browse_Graphic_File_Type: PNG
Data_Set_Credit: USDA Forest Service Remote Sensing Applications Center
Security_Information:
Security_Classification_System: none
Security_Classification: Unclassified
Security_Handling_Description: n/a
Native_Data_Set_Environment: Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; ESRI ArcGIS 10.0.5.4400

Data_Quality_Information

Attribute_Accuracy:
Attribute_Accuracy_Report: No formal independent accuracy assessment of TCC 2011 has been made. The Random Forests™ regression algorithm (Breiman 2001; Cutler et al. 2007) employed in TCC 2011 mapping calculates the mean of squared residuals along with percent variability explained by the model for assessing prediction reliability. The Random Forests™ models consisted of 500 decision trees, which were used to determine the final response value. The response of each tree depended on a randomly chosen subset of predictor variables chosen independently (with replacement) for evaluation by that tree. The responses of the trees were averaged to obtain an estimate of the dependent variable. The standard error is the square root of the variance of the estimates given by all trees. A summary of the Random Forests™ models is available in the supplemental metadata.
Completeness_Report: This CONUS TCC 2011 product is the percent tree canopy layer version 1, dated 2014. The CONUS TCC 2011 dataset consists of two main data products: (1) per-pixel tree canopy cover and (2) per-pixel standard error for the predicted tree canopy cover. A summary of all the Landsat images and the predictor variables that were used for modeling tree canopy cover using the Random Forests™ regression algorithm is available in the supplemental metadata. For detailed information, please refer to http://www.mrlc.gov.
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Originator:
Publication_Date: unpublished material
Title: Digital Elevation Model (DEM)
Geospatial_Data_Presentation_Form: raster digital data
Type_of_Source_Media: None
Source_Citation_Abbreviation: DEM
Source_Contribution: elevation data
Source_Information:
Source_Citation:
Citation_Information:
Originator:
Publication_Date: unpublished material
Title: Photo-interpreted Canopy Cover (FIA)
Geospatial_Data_Presentation_Form: vector digital data
Type_of_Source_Media: None
Source_Citation_Abbreviation: FIACC
Source_Contribution: canopy cover estimate (training/validation)
Source_Information:
Source_Citation:
Citation_Information:
Originator:
Publication_Date: unpublished material
Title: X-Coordinate
Geospatial_Data_Presentation_Form: raster digital data
Type_of_Source_Media: None
Source_Citation_Abbreviation: XCoord
Source_Contribution: east-west location (relative to 96.0 W longitude)
Source_Information:
Source_Citation:
Citation_Information:
Originator:
Publication_Date: 20110101
Title: NLCD 2006 Land Cover
Geospatial_Data_Presentation_Form: raster digital data
Publication_Information:
Publication_Place:
Publisher: U.S. Geological Survey
Type_of_Source_Media: None
Source_Citation_Abbreviation: NLCD06LC
Source_Contribution: land cover information
Source_Information:
Source_Citation:
Citation_Information:
Originator:
Publication_Date: 20030101
Title: NLCD2001 Percent Tree Canopy Cover
Geospatial_Data_Presentation_Form: raster digital data
Publication_Information:
Publication_Place:
Publisher: U.S. Geological Survey
Type_of_Source_Media: None
Source_Citation_Abbreviation: NLCD01TC
Source_Contribution: percent tree canopy cover
Source_Information:
Source_Citation:
Citation_Information:
Originator:
Publication_Date: 19950101
Title: Bailey's Ecoregion Sections
Geospatial_Data_Presentation_Form: raster digital data
Publication_Information:
Publication_Place:
Publisher: USDA Forest Service Rocky Mountain Research Station
Type_of_Source_Media: None
Source_Citation_Abbreviation: Bailey
Source_Contribution: ecosystem geography
Source_Information:
Source_Citation:
Citation_Information:
Originator:
Publication_Date: unknown
Title: Landsat 5 Multispectral Thematic Mapper Imagery
Geospatial_Data_Presentation_Form: raster digital data
Publication_Information:
Publication_Place:
Publisher: U.S. Geological Survey
Type_of_Source_Media: None
Source_Citation_Abbreviation: L5
Source_Contribution: spectral information
Source_Information:
Source_Citation:
Citation_Information:
Originator:
Publication_Date: unpublished material
Title: Y-Coordinate
Geospatial_Data_Presentation_Form: raster digital data
Type_of_Source_Media: None
Source_Citation_Abbreviation: YCoord
Source_Contribution: north-south location (relative to 23.0 N latitude)
Source_Information:
Source_Citation:
Citation_Information:
Originator:
Publication_Date: unpublished material
Title: Landsat 5 Multispectral Composite Imagery
Geospatial_Data_Presentation_Form: raster digital data
Type_of_Source_Media: None
Source_Citation_Abbreviation: L5Comp
Source_Contribution: spectral information
Process_Step:
Process_Description: Creation of Landsat derivatives. Spectral derivative images were calculated from the Landsat composite image for each WRS-2 path/row. NDMI (normalized difference moisture index), NDVI (normalized difference vegetation index), and the 6-band tasseled cap transformation (Crist and Kauth1986) were calculated following industry standards. Focal standard deviations (FSD) were also calculated for the composite image (all bands), NDMI, NDVI, and the tasseled cap derivative (all bands).
Source_Used_Citation_Abbreviation: L5Comp
Process_Date: 20130101
Source_Produced_Citation_Abbreviation: NDMI
Source_Produced_Citation_Abbreviation: NDMIFSD
Source_Produced_Citation_Abbreviation: TasCapFSD
Source_Produced_Citation_Abbreviation: NDVIFSD
Source_Produced_Citation_Abbreviation: L5FSD
Source_Produced_Citation_Abbreviation: TasCap
Source_Produced_Citation_Abbreviation: NDVI
Process_Step:
Process_Description: Creation of NLCD 2001 percent tree canopy cover derivative. Focal standard deviations (FSD) were calculated for the NLCD 2001 tree canopy data. The dataset was then subset to individual WRS-2 path/row boundaries for use in subsequent processes.
Source_Used_Citation_Abbreviation: NLCD01TC
Process_Date: 20130101
Source_Produced_Citation_Abbreviation: NLCD01TCFSD
Process_Step:
Process_Description: Creation of DEM derivatives. A CONUS-wide 30-m DEM, ortho-rectified to the 2001 NLCD percent tree canopy cover dataset, was provided by USGS for this project. Slope, aspect, and the sine and cosine of aspect were calculated for each pixel following industry standards. Focal standard deviations (FSD) were also calculated for the DEM and each derivative dataset. Each of these data layers was subset to individual WRS-2 path/row boundaries for use in subsequent processes.
Source_Used_Citation_Abbreviation: DEM
Process_Date: 20130101
Source_Produced_Citation_Abbreviation: AspSin
Source_Produced_Citation_Abbreviation: AspSinFSD
Source_Produced_Citation_Abbreviation: Slope
Source_Produced_Citation_Abbreviation: AspectFSD
Source_Produced_Citation_Abbreviation: AspCosFSD
Source_Produced_Citation_Abbreviation: DEMFSD
Source_Produced_Citation_Abbreviation: Aspect
Source_Produced_Citation_Abbreviation: SlopeFSD
Source_Produced_Citation_Abbreviation: AspCos
Process_Step:
Process_Description: Creation of Landsat composite. Fifteen Landsat 5 scenes were selected and processed for each WRS-2 path/row. Selected scenes were acquired between 2007 and 2011, with the majority evenly distributed between 2009, 2010 and 2011. The selection process favored scenes with minimal cloud cover and with MODIS-based NDVI values near the annual peak for the dominant forest cover type. Remaining clouds were removed using the Fmask tool (Zhu and Woodcock 2012). Six spectral bands (TM bands 1-5 and 7) within each scene were atmospherically corrected with dark object subtraction and transformed to surface reflectance (Chander et al. 2009; Chavez 1988). Each set of 15 6-band scenes was then combined to form a cloud-free composite image for the given path/row.
Source_Used_Citation_Abbreviation: L5
Process_Date: 20130101
Source_Produced_Citation_Abbreviation: L5Comp
Process_Step:
Process_Description: Creation of percent tree canopy cover dataset (main process). For practical reasons, the NLCD 2011 percent tree canopy cover (TCC 2011) CONUS dataset was created piecewise in 68 zones, called “mapping areas”. Each mapping area was based on the zones defined in Homer and Gallant (2001), but extended to include the footprint of all WRS-2 path/rows that intersected the given zone. Each mapping area included between 9 and 27 WRS-2 path/rows. The final dataset is a mosaic of TCC 2011 for all CONUS WRS-2 path/rows. Five major steps were employed to map tree canopy cover: collection of reference data, acquisition and/or creation of predictor layers, calibration of Random Forests™ regression models for each mapping area using reference data and predictor layers, application of those models to predict per-pixel tree canopy cover across the entire mapping area, and creation of the CONUS-wide mosaic. The methodology is described further below and in Coulston et al. (2012). Reference data, consisting of estimated tree canopy cover at each of 63,008 FIA plot locations, were generated via photographic interpretation of high spatial resolution images acquired by the National Agricultural Inventory Program (NAIP). The reference data were collected and supplied by the USDA Forest Service Forest Inventory and Analysis (FIA) program. The spatial distribution of the sample points follows the FIA systematic grid (Brand et al. 2000). Predictor layers included Landsat 5 Thematic Mapper composite imagery and spectral derivatives thereof (NDMI, NDVI, and tasseled cap); elevation data and spatial derivatives thereof (slope and aspect, as well as sine and cosine of aspect); NLCD 2001 percent tree canopy cover; NLCD 2006 land cover; Bailey's eco-regions; and the focal standard deviation of each of the preceding layers except for land cover and eco-regions. Explicit location data were also included as predictor layers. The processes for creating the derived layers are described separately (see related Process Steps). Modeling was carried out using the Random Forests™ (Breiman 2001) data mining technique as outlined in the Attribute Accuracy Report above. To minimize the root mean square error, variable importance information obtained from the Random Forests™ models was used to reduce the number of predictor variables. These reduced datasets were used for the final Random Forests™ modeling. The models developed for each mapping area were applied to individual WRS-2 path/rows within the mapping area, producing a 2-layered image. The first layer was the RandomForests™ estimate of tree canopy cover and the second layer was the standard error, which is the per-pixel square root of the variance of the Random Forests™ estimates from the individual trees. Since models were applied to each mapping area independently, there were multiple estimates for pixels in overlapping areas. For these pixels, the estimate with the lowest standard error was carried into the CONUS-wide mosaic.
Source_Used_Citation_Abbreviation: FIACC, L5Comp, L5FSD, NDMI, NDMIFSD, NDVI, NDVIFSD, TasCap, TasCapFSD, DEM, DEMFSD, Aspect, AspectFSD, AspCos , AspCosFSD, AspSin, AspSinFSD, Slope, SlopeFSD, Bailey, NLCD06LC, NLCD01TC, NLCD01TCFSD, XCoord, YCoord
Process_Date: 20140101
Process_Step:
Process_Description: CUGIR staff clipped data to New York state boundary.
Process_Date: 20180430

Spatial_Data_Organization_Information

Direct_Spatial_Reference_Method: Raster
Raster_Object_Information:
Raster_Object_Type: Grid Cell
Row_Count: 16989
Column_Count: 22610

Entity_and_Attribute_Information

Entity_Type:
Entity_Type_Label: nlcd2011_usfs_conus_canopy_analytical.img.vat
Attributes:
Name Description Values
OID Internal feature number. Sequential unique whole numbers that are automatically generated.
Value
Count
Red
Green
Blue
Opacity

Distribution_Information

Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: Albert R. Mann Library
Contact_Address:
Address_Type: mailing and physical
Address: Cornell University
City: Ithaca
State_or_Province: New York
Postal_Code: 14853
Contact_Voice_Telephone: 607-255-5406
Contact_Electronic_Mail_Address: mann-ref@cornell.edu
Distribution_Liability: Cornell University provides these geographic data "as is". Cornell University makes no guarantee or warranty concerning the accuracy of information contained in the geographic data. Cornell University further makes no warranty either expressed or implied, regarding the condition of the product or its fitness for any particular purpose. The burden for determining fitness for use lies entirely with the user. Although these files have been processed successfully on computers at Cornell University, no warranty is made by Cornell University regarding the use of these data on any other system, nor does the fact of distribution constitute or imply any such warranty.
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Format_Name: GeoTIFF
Format_Information_Content: zipped geotiff
File_Decompression_Technique: zip
Transfer_Size: 181.79
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Digital_Form:
Digital_Transfer_Information:
Format_Name: metadata
Format_Information_Content: FGDC XML metadata
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Digital_Form:
Digital_Transfer_Information:
Format_Name: HTML metadata
Format_Information_Content: FGDC HTML metadata
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Digital_Form:
Digital_Transfer_Information:
Format_Name: OGC:WMS
Format_Information_Content: WMS, from GeoServer
Digital_Transfer_Option:
Online_Option:
Fees: None

Distribution_Information

Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: U.S. Geological Survey
Contact_Position: Customer Services Representative
Contact_Address:
Address_Type: mailing and physical
Address: USGS/EROS
Address: 47914 252nd Street
City: Sioux Falls
State_or_Province: SD
Postal_Code: 57198-0001
Country: US
Contact_Voice_Telephone: 605-594-6151
Contact_TDD/TTY_Telephone: 605/594-6933
Contact_Facsimile_Telephone: 605-594-6589
Contact_Electronic_Mail_Address: custserv@usgs.gov
Hours_of_Service: 0800 - 1600 CT, M - F (-6h CST/-5h CDT GMT)
Contact_Instructions: The USGS point of contact is for questions relating to the data display and download from this web site. For questions regarding data content and quality, refer to: http://www.mrlc.gov/mrlc2k.asp or email: mrlc@usgs.gov
Resource_Description: Downloadable data
Distribution_Liability: See access and use constraints information.

Metadata_Reference_Information

Metadata_Date: 20190604
Metadata_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: Albert R. Mann Library
Contact_Address:
Address_Type: mailing and physical
Address: Albert R. Mann Library
City: Ithaca
State_or_Province: New York
Postal_Code: 14853
Country: USA
Contact_Voice_Telephone: 607-255-5406
Contact_Electronic_Mail_Address: mann-ref@cornell.edu
Metadata_Standard_Name: FGDC Content Standard for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998
Metadata_Time_Convention: local time