NLCD Tree Canopy (Cartographic), New York, 2011

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Identification_Information

Citation:
Citation_Information:
Publication_Date: 20140331
Title: NLCD Tree Canopy (Cartographic), 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 (Cartographic)
Publication_Information:
Publication_Place:
Publisher: U.S. Geological Survey
Other_Citation_Details: References: 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-009006
Larger_Work_Citation:
Citation_Information:
Publication_Date: 20140101
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) USFS percent tree canopy product 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 current, consistent, and seamless national land cover, percent tree canopy, and percent impervious cover at medium spatial resolution. This product is the cartographic version of the NLCD2011 percent 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). Tree canopy values range from 0 to 100 percent. The analytic tree canopy layer was produced using a Random Forests™ regression algorithm. The cartographic product is a filtered version of the regression algorithm output.
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/00/90/06/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 10.0.3.3600

Data_Quality_Information

Attribute_Accuracy:
Attribute_Accuracy_Report: No formal independent accuracy assessment of this product has been made. The Random Forests™ regression algorithm (Breiman 2001; Cutler et al. 2007) employed in creating this product 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 associated with the analytic version of this product.
Completeness_Report: This product is the cartographic version of the NLCD2011 USFS percent tree canopy product, version 1, dated 2014.
Lineage:
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: 20140331
Title: NLCD 2011 USFS Percent Tree Canopy
Geospatial_Data_Presentation_Form: raster digital data
Publication_Information:
Publication_Place:
Publisher: U.S. Geological Survey
Type_of_Source_Media: None
Source_Citation_Abbreviation: NLCD2011TC
Source_Contribution: percent tree canopy cover
Process_Step:
Process_Description: Creation of NLCD2011 USFS Percent Tree Canopy, cartographic version. The cartographic version of the percent tree canopy product is a filtered version of the corresponding analytic product, in which values less than a calculated uncertainty have been set to zero. In essence, the filtering process reduces errors of commission by eliminating values that are not significantly different from zero. A threshold value was determined for each of 68 geographic zones using data from 500 runs of the Random Forest™ algorithm on bootstrap samples. From these data, t-statistics were calculated. For each zone, the t-statistic at the 95th interval was selected as the threshold value. Threshold values ranged from 0.5 to 1.6. To create the cartographic layer, the product of the t-statistic threshold value and the standard error from the analytic layer was compared to the analytic percent tree canopy value. If the threshold-error product was greater than the percent tree canopy, the tree canopy value for that pixel was set to zero in the cartographic layer; otherwise, the percent tree canopy from the analytic layer was used.
Source_Used_Citation_Abbreviation: NLCD2006 LC, NLCD2011 TC
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_cartographic.img.vat
Attributes:
Name Description Values
OID Internal feature number. Sequential unique whole numbers that are automatically generated.
Value Percent tree canopy cover 0 to 100 Percent
Count

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: 78.59
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