U.S. Geological Survey
201901
NLCD 2006 Impervious Surface descriptor Conterminous United States
remote-sensing image
None
None
Sioux Falls, SD
U.S. Geological Survey
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.
https://doi.org/10.5066/P937PN4Z
https://www.mrlc.gov/data
https://www.mrlc.gov/data-services-page
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.
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.
Corner Coordinates (center of pixel, projection meters)
Upper Left Corner: -2493045 meters(X), 3310005 meters(Y)
Lower Right Corner: 2342655 meters(X), 177285 meters(Y)
2001
2016
ground condition
Every 5 years
-130.2328
-63.6722
52.8510
21.7423
ISO 19115 Topic Category
biota
biota
NGDA Portfolio Themes
NGDA
National Geospatial Data Asset
Land Use Land Cover Theme
None
Land cover
Image processing
GIS
U.S. Geological Survey (USGS)
digital spatial data
U.S. Department of Commerce, 1995, (Countries, dependencies, areas of special sovereignty, and their principal administrative divisions, Federal Information Processing Standard 10-4): Washington, D.C., National Institute of Standards and Technology
United States
U.S.
US
None
None
None
None
U.S. Geological Survey
Customer Service Representative
mailing and physical address
47914 252nd Street
Sioux Falls
SD
57198-0001
USA
605/594-6151
605/594-6589
custserv@usgs.gov
U.S. Geological Survey
None
Unclassified
N/A
Microsoft Windows 10; ESRI ArcCatalog 10.5.1
A formal accuracy assessment has not been conducted for NLCD 2016 Land Cover, NLCD 2016 Land Cover Change, or NLCD 2016 Impervious Surface products.
Unknown
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.
The NLCD 2016 final seamless products include: 1) NLCD 2016 Land Cover; 2) NLCD 2016 Impervious Surface; 3) NLCD 2016 Land Cover Change Index.
This NLCD product is the version dated January, 2019.
N/A
N/A
Defense Meteorological Satellite Program (DMSP) Nighttime Lights and Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night band Nighttime Lights have been applied by many researchers as a way to study such topics as population density and economic activity. These two datasets are used in the generation of training data for the new NLCD 2016 Impervious Surface for 2011 and 2016, respectively.
DMSP Nighttime Lights (for 2011) and VIIRS Day/Night band Nighttime Lights (for 2016) were superimposed on NLCD 2011 Impervious Surface data to exclude low density impervious areas outside urban and suburban centers, and ensure that only core urban areas were included in training data development. Two training datasets, one of larger extent, one smaller, were assembled by imposing two separate thresholds of nighttime lights imagery onto the NLCD 2011 Impervious Surface data layer.
Each of the two training datasets were used separately to build regression tree models for predicting percent impervious surface using 2011 Landsat imagery as predictive variables. These two sets of regression tree models were the basis of two 2011 initial impervious surface maps. The same two training datasets were used with 2016 Landsat imagery to create two sets of regression tree models and two 2016 initial impervious surface maps.
The two pairs of initial impervious surface maps - 2 each for 2011 and 2016 - were compared to remove false estimates caused by high reflectance in non-urban areas, as well as to retain 2011 impervious values unchanged from 2011 to 2016. An updated 2016 impervious surface map was generated.
The last step is a clean-up to correct mapping errors with automated processes and some hand editing. For example, false impervious estimates in mines and barren land were removed, and developed areas with low imperviousness, such as city parks and golf courses, were added.
Landsat ETM, Landsat TM, DEM, USGS/EROS
2016
USGS National Land Cover Database
The impervious descriptor layer defines which impervious layer pixels are roads and provides the best fit description for impervious pixels that are not roads. This should allow users extra flexibility for manipulating and categorizing impervious surface and the ability to more accurately identify new impervious growth for each year. The impervious descriptor information is generated from roads, urban areas, and energy production sites. Roads for 2011 and 2016 were derived from NAVSTREETS™ from HERE and a combination of Census Urban Area TIGER/Line Shapefiles, NLCD Impervious Surface, Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime lights, and hand edits for the entire United States. For the years 2006 and 2001, there is no comparable roads source, so the NAVSTREETS™-derived 2011 roads were edited to reflect how the roads should appear for these years. This was done using a combination of impervious change pixels and hand edits for the entire United States.
Energy production sites were generated by the Landfire project (a partner in the MRLC consortium) utilizing FrackTracker points. Landfire utilized a Landsat cloud-free composite for the target year, 2016. ERDAS' Spectral Angle Mapper (SAM) algorithm was used to classify gravel soil features typical of pads. Training plots were selected from the scene manually and used to establish a mean target signature. SAM was then used to measure similarity of all pixels in the scene against the target signature. A threshold was applied to minimize noise without losing data. Expert manual editing was then done to eliminate commission errors. Wind turbine locations were added from an external data source. Some wells could not be captured using spectral methods, especially single wells in isolated areas. The mapping methods prioritized areas with clusters of several well pads. Some wells were manually digitized and added to the layer if they were not captured with spectral methods. Manual editing was conservative and focused on capturing the maximum number of features without making commission errors. After the energy production areas were identified, the NLCD team used shape extraction features to isolate each site into a single feature, and linked these single features to the land cover disturbance map used to create the land cover change products. This linkage enabled the individual site features to be labeled with a date of change and subsequently represented with the correct year of change in the Impervious Surface product.
Landsat ETM, Landsat TM, DEM, USGS/EROS
2016
USGS National Land Cover Database
Raster
Grid Cell
104424
161190
1
Albers Conical Equal Area
29.5
45.5
-96.0
23.0
0.0
0.0
row and column
30.0
30.0
meters
WGS_1984
WGS 84
6378137.0
298.257223563
None
NLCD Impervious Surface Layer
National Land Cover Database 2016
ObjectID
Internal feature number
ESRI
Sequential unique whole numbers that are automatically generated.
Value
Percent Imperviousness
NLCD 2016
0
100
percentage
0.1
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
NLCD 2016
Integer
Red
Red color code for RGB slice by value for imperviousness image display purposes. The value is arbitrarily assigned by the display software package, unless defined by user. Standard user defined ramp for NLCD project is start color light gray, end color red.
NLCD 2016
0
100
CSS Color Value Percentage
0.1
Green
Green color code for RGB slice by value for imperviousness image display purposes. The value is arbitrarily assigned by the display software package, unless defined by user. Standard user defined ramp for NLCD project is start color light gray, end color red.
NLCD 2016
0
100
CSS Color Value Percentage
0.1
Blue
Blue color code for RGB slice by value for imperviousness image display purposes. The value is arbitrarily assigned by the display software package, unless defined by user. Standard user defined ramp for NLCD project is start color light gray, end color red.
NLCD 2016
0
100
CSS Color Value Percentage
0.1
Opacity
A measure of how opaque, or solid, a color is displayed in a layer.
NLCD 2016
0
100
Percentage
0.1
ValueImpervious Descriptor Layer definitionsNLCD 2016
1
Primary road in urban area : interstates and other major roads
Producer-defined
2
Primary road outside urban area : interstates and other major roads
Producer-defined
3
Secondary road in urban area : non-interstate highways
Producer-defined
4
Secondary road outside urban area : non-interstate highways
Producer-defined
5
Tertiary road in urban area : any two-lane road
Producer-defined
6
Tertiary road outside urban area : any two-lane road
Producer-defined
7
Thinned road in urban area : small tertiary roads that generally are not paved and have been removed from the landcover but remain as part of the impervious surface product. These roads have been separated in the western United States so that a better categorization of developed features is represented in the landcover
Producer-defined
8
Thinned road outside urban area : small tertiary roads that generally are not paved and have been removed from the landcover but remain as part of the impervious surface product. These roads have been separated in the western United States so that a better categorization of developed features is represented in the landcover
Producer-defined
9
Nonroad impervious surface in urban area
Producer-defined
10
Nonroad impervious surface outside urban area
Producer-defined
11
Energy production site in urban area : areas identified from the FrackTracker points and classified in coordination with the Landfire project
Producer-defined
12
Energy production site outside urban area : areas identified from the FrackTracker points and classified in coordination with the Landfire project
Producer-defined
Impervious Surface Attributes
Attributes defined by USGS and ESRI.
U.S. Geological Survey
Customer Service Representative
mailing and physical address
47914 252nd Street
Sioux Falls
SD
57198-0001
USA
605/594-6151
605/594-6589
custserv@usgs.gov
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.
ERDAS
Imagine 2016
.img
1012.0
https://www.mrlc.gov
None
ESRI ArcMap Suite and/or Arc/Info software, and supporting operating systems.
20181213
U.S. Geological Survey
Customer Services Representative
mailing and physical address
47914 252nd Street
Sioux Falls
SD
57198-0001
USA
605/594-6151
605/594-6589
custserv@usgs.gov
FGDC Content Standard for Digital Geospatial Metadata
FGDC-STD-001-1998
local time