NLCD Land Cover, New York, 2016

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Identification_Information

Citation:
Citation_Information:
Originator: U.S. Geological Survey
Publication_Date: 201901
Title: NLCD Land Cover, New York, 2016
Edition: 2016
Geospatial_Data_Presentation_Form: raster digital data
Series_Information:
Series_Name: National Land Cover Database
Issue_Identification: 2016 Land Cover
Publication_Information:
Publication_Place: Sioux Falls, SD
Publisher: U.S. Geological Survey
Other_Citation_Details: References: Yang, L., et al. (2018). "A new generation of the United States National Land Cover Database: Requirements, research priorities, design, and implementation strategies." ISPRS Journal of Photogrammetry and Remote Sensing 146: 108-123.
Online_Linkage: https://cugir.library.cornell.edu/catalog/cugir-009031
Online_Linkage: https://doi.org/10.5066/P937PN4Z
Online_Linkage: https://www.mrlc.gov/data
Online_Linkage: https://www.mrlc.gov/data-services-page
Description:
Abstract: The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2016. The NLCD 2016 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2016 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2016: a streamlined process for assembling and preprocessing Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2016 production. The performance of the developed strategies and methods were tested in twenty World Reference System-2 path/row throughout the conterminous U.S. An overall agreement ranging from 71% to 97% between land cover classification and reference data was achieved for all tested area and all years. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2016 operational mapping.
Questions about the NLCD 2016 land cover product can be directed to the NLCD 2016 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
Purpose: The goal of this project is to provide the Nation with complete, current, and consistent public domain information on its land use and land cover.
Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2016
Currentness_Reference: ground condition
Status:
Progress: In work
Maintenance_and_Update_Frequency: Every 2-3 years
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -80.035674
East_Bounding_Coordinate: -70.516586
North_Bounding_Coordinate: 45.847774
South_Bounding_Coordinate: 40.086452
Keywords:
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: Land cover
Theme_Keyword: Land use
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Category
Theme_Keyword: ImageryBaseMapEarthCover
Theme_Keyword: Environment
Theme:
Theme_Keyword_Thesaurus: CUGIR Category
Theme_Keyword: landcover
Theme_Keyword: environment
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: New York
Access_Constraints: None
Use_Constraints: None
Point_of_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: U.S. Geological Survey
Contact_Position: Customer Service 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: USA
Contact_Voice_Telephone: (605) 594-6151
Contact_Electronic_Mail_Address: custserv@usgs.gov
Browse_Graphic:
Browse_Graphic_File_Name: https://cugir-data.s3.amazonaws.com/00/90/31/preview.png
Browse_Graphic_File_Description: preview of the dataset
Browse_Graphic_File_Type: PNG
Data_Set_Credit: U.S. Geological Survey
Security_Information:
Security_Classification_System: None
Security_Classification: Unclassified
Security_Handling_Description: N/A
Native_Data_Set_Environment: Microsoft Windows 10; ESRI ArcCatalog 10.5.1

Data_Quality_Information

Attribute_Accuracy:
Attribute_Accuracy_Report: A formal accuracy assessment has not been conducted for NLCD 2016 Land Cover, NLCD 2016 Land Cover Change, or NLCD 2016 Impervious Surface products.
Quantitative_Attribute_Accuracy_Assessment:
Attribute_Accuracy_Value: Unknown
Attribute_Accuracy_Explanation: This document and the described land cover map are considered "provisional" until a formal accuracy assessment is completed. The U.S. Geological Survey can make no guarantee as to the accuracy or completeness of this information, and it is provided with the understanding that it is not guaranteed to be correct or complete. Conclusions drawn from this information are the responsibility of the user.
Logical_Consistency_Report: The NLCD 2016 final seamless products include: 1) NLCD 2016 Land Cover; 2) NLCD 2016 Impervious Surface; 3) NLCD 2016 Land Cover Change Index.
Completeness_Report: This NLCD product is the version dated January, 2019.
Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report: N/A
Vertical_Positional_Accuracy:
Vertical_Positional_Accuracy_Report: N/A
Lineage:
Process_Step:
Process_Description: NLCD 2016 Land Cover Process Step

National Land Cover Database (NLCD) land cover data is fundamentally based on the analysis of Landsat data. Approximately 3,608 Landsat scenes are required for NLCD 2016 (this total does not include additional scenes needed for cloud/shadow fill). Using automated scripts, Landsat scenes were selected for seven target years: 2001, 2003, 2006, 2008, 2011, 2013, and 2016. All scenes with cloud cover less than 20 percent were downloaded and one cloud-free, leaf-on image was selected for each path/row in each year. In addition, one leaf-off image was added for 2016 only.

If no cloud-free images were available for the target year, then an alternate cloud-free image was selected either one year before or one year after the target. If there was still significant cloud cover, then up to three fill images were selected and applied in a process to remove clouds, cloud shadow, smoke, or other artifacts.

Other input datasets include: NLCD 2001, 2006, and 2011; 3D Elevation Program (3DEP) digital elevation data; Coastal Change Analysis Program (C-CAP) land cover; Cropland Data Layer (CDL); National Wetlands Inventory (NWI); Soil Survey Geographic (SSURGO) Database; and State Soil Geographic (STATSGO2) Database. SSURGO (with STATSGO2 to fill in gaps) was the basis for a hydric soils data layer used in training data assembly.

NLCD 2016 is produced by modeling land cover change over seven intervals between 2001 and 2016, with consistent change trajectories built into the process. The first set of models in this process are for multi-spectral change detection. The Multi-Index Integrated Change Analysis (MIICA) model outputs a change map between two dates of imagery. Five spectral indices are also calculated, and a disturbance map is produced by the Vegetation Change Tracker (VCT) software. The MIICA outputs, the five spectral indices, and the 1986 to 2016 disturbance map are the inputs to the training dataset assembly stage.

A set of models was developed to assemble a training dataset for each land cover class for each of the seven target years. The training dataset models were built with Landsat images and derived indices, spectral change products, trajectory analysis, and ancillary data: NLCD 2001, 2006, and 2011; C-CAP land cover; CDL; NWI; a cultivated cropland 2008 to 2016 dataset; and a hydric soils dataset. Image segmentation was performed on the Landsat scenes, and the resulting image objects were used to mitigate noise in the training data. The final output of this stage is training data for each of the seven target years, for input into the initial land cover classification stage.

For each of the seven target years of Landsat data, two percent of all available training data per path/row was drawn from the data as training samples, and one percent was drawn as validation samples. The C5 decision tree classification software was run on the training samples to generate a set of rules, and the decision rules were applied to generate a land cover classification for each of the seven target years.

The C5 software was run with four sets of independent variables: the 1986 to 2016 disturbance year data derived from VCT; the set of Landsat images; compactness indices from image segmentation; and a DEM and its derivatives. The classifier was run twice, once with all land cover classes processed and the 1986 to 2016 disturbance year data included, and again with two classes - Urban and Water - omitted from the classification and the disturbance year data not included in processing.
The two classifications were integrated with ancillary data and the segmentation polygons to produce seven initial land cover maps.

A post-classification refinement process was developed to correct classification errors in each target year, check for consistency of land cover labels over time, and improve spatial coherence of land cover distribution. Refinement was conducted class-by-class in hierarchical order: (1) Water, (2) Wetlands, (3) Forest and forest transition, (4) Permanent snow, (5) Agricultural lands, and (6) Persistent shrubland and herbaceous. Models were developed for refinement of each class and each type of confusion. For example, confusion between coniferous forest and water, both spectrally "dark" could be corrected by reclassifying water to coniferous forest where slope was greater than 2 percent. Confusion between forest and cropland could be mitigated with CDL data, and so forth.

The final integration step resolved class label issues pertinent to local environments (such as coastal areas), and, for land cover classes other than Water and Developed, ensured that all pixels in a segmentation object were in the same class. Pixel-based and object-based land cover labels were checked for differences, which were reconciled by a rule-based model. Water and Developed classes kept pixel values intact even in areas that were smaller than segmentation objects. Change trajectories for each class were checked for consistency through the seven target years.
Source_Used_Citation_Abbreviation: Landsat ETM, Landsat TM, DEM, USGS/EROS
Process_Date: 2016
Source_Produced_Citation_Abbreviation: USGS National Land Cover Database
Process_Step:
Process_Description: CUGIR staff clipped data to New York state boundary
Process_Date: 20190607

Spatial_Data_Organization_Information

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

Spatial_Reference_Information

Horizontal_Coordinate_System_Definition:
Planar:
Map_Projection:
Map_Projection_Name: Albers Conical Equal Area
Albers_Conical_Equal_Area:
Standard_Parallel: 29.5
Standard_Parallel: 45.5
Longitude_of_Central_Meridian: -96.0
Latitude_of_Projection_Origin: 23.0
False_Easting: 0.0
False_Northing: 0.0
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: row and column
Coordinate_Representation:
Abscissa_Resolution: 30.0
Ordinate_Resolution: 30.0
Planar_Distance_Units: meters
Geodetic_Model:
Horizontal_Datum_Name: North American Datum of 1983
Ellipsoid_Name: Geodetic Reference System 80
Semi-major_Axis: 6378137.0
Denominator_of_Flattening_Ratio: 298.257222

Entity_and_Attribute_Information

Entity_Type:
Entity_Type_Label: None
Entity_Type_Definition: NLCD Land Cover Layer
Entity_Type_Definition_Source: National Land Cover Database
Attributes:
Name Description Values
ObjectID Internal feature number Sequential unique whole numbers that are automatically generated.
Count A nominal integer value that designates the number of pixels that have each value in the file; histogram column in ERDAS Imagine raster attributes table Integer
Value Land Cover Class Code Value. coded values
Red Red color code for RGB. The value is arbitrarily assigned by the display software package, unless defined by user. 0 to 100 Percentage
Green Green color code for RGB. The value is arbitrarily assigned by the display software package, unless defined by user. 0 to 100 Percentage
Blue Blue color code for RGB. The value is arbitrarily assigned by the display software package, unless defined by user. 0 to 100 Percentage
Opacity A measure of how opaque, or solid, a color is displayed in a layer. 0 to 100 Percentage
Overview_Description:
Entity_and_Attribute_Overview: Land Cover Class RGB Color Value Table
Entity_and_Attribute_Detail_Citation: Attributes defined by USGS and ESRI.
Value Red Green Blue
0 0.00000000000 0.00000000000 0.00000000000
11 0.27843137255 0.41960784314 0.62745098039
12 0.81960784314 0.86666666667 0.97647058824
21 0.86666666667 0.78823529412 0.78823529412
22 0.84705882353 0.57647058824 0.50980392157
23 0.92941176471 0.00000000000 0.00000000000
24 0.66666666667 0.00000000000 0.00000000000
31 0.69803921569 0.67843137255 0.63921568628
41 0.40784313726 0.66666666667 0.38823529412
42 0.10980392157 0.38823529412 0.18823529412
43 0.70980392157 0.78823529412 0.55686274510
51 0.64705882353 0.54901960784 0.18823529412
52 0.80000000000 0.72941176471 0.48627450980
71 0.88627450980 0.88627450980 0.75686274510
72 0.78823529412 0.78823529412 0.46666666667
73 0.60000000000 0.75686274510 0.27843137255
74 0.46666666667 0.67843137255 0.57647058824
81 0.85882352941 0.84705882353 0.23921568628
82 0.66666666667 0.43921568628 0.15686274510
90 0.72941176471 0.84705882353 0.91764705882
95 0.43921568628 0.63921568628 0.72941176471
Overview_Description:
Entity_and_Attribute_Overview: N/A
Entity_and_Attribute_Detail_Citation: Attribute accuracy is described, where present, with each attribute defined in the Entity and Attribute Section.

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: 31.80
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 Service 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: USA
Contact_Voice_Telephone: (605) 594-6151
Contact_Electronic_Mail_Address: custserv@usgs.gov
Distribution_Liability: Although these data have been processed successfully on a computer system at the USGS, no warranty expressed or implied is made by the USGS regarding the use of the data on any other system, nor does the act of distribution constitute any such warranty. Data may have been compiled from various outside sources. Spatial information may not meet National Map Accuracy Standards. This information may be updated without notification. The USGS shall not be liable for any activity involving these data, installation, fitness of the data for a particular purpose, its use, or analyses results.
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Format_Name: ERDAS
Format_Version_Number: Imagine 2016
Format_Specification: .img
Transfer_Size: 1012.0
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://www.mrlc.gov
Access_Instructions: The URL https://www.mrlc.gov provides a download interface that allows for data downloads. The download page allows the customer to download a zipped file that can be saved on the customer's computer. The file can then be unzipped and imported into various user software applications.
Fees: None
Technical_Prerequisites: ESRI ArcMap Suite and/or Arc/Info software, and supporting operating systems.

Metadata_Reference_Information

Metadata_Date: 20190607
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