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Geological Survey Jon Dewitz remote-sensing image None None A new generation of the United States National Land Cover Database: Requirements, research priorities, design, and implementation strategies USGS_NLCD_Imperviousness_2011 <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>USGS NLCD Imperviousness 2011. The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. 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 2019. The NLCD 2019 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 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on 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 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details. Disclaimer: This product is for informational purposes only and may not be suitable for legal, engineering, or surveying purposes. It does not represent an official survey and represents only the approximate relative location of features and boundaries. Mapping may not necessarily reflect on-the-ground conditions. This product and those involved in its production make no claims as to the accuracy or reliability of the data, and neither assumes, nor will accept liability for their use.</SPAN></P></DIV></DIV></DIV> USGS NLCD Imperviousness 2011. 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. U.S. Geological Survey U.S. Geological Survey Customer Service Representative 605/594-6151 605/594-6589 47914 252nd Street Sioux Falls SD 57198-0001 US custserv@usgs.gov Common Geographic Areas United States ISO 19115 Topic Category imageryBaseMapsEarthCover biota NGDA Portfolio Themes Land Use Land Cover Theme NGDA National Geospatial Data Asset USGS Thesaurus GIS Image processing Land cover digital spatial data U.S. Geological Survey (USGS) 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 Land Use Land Cover Theme GIS imageryBaseMapsEarthCover Image processing Land cover biota NGDA digital spatial data United States United States U.S. US U.S. Geological Survey (USGS) National Geospatial Data Asset Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. None. Please see 'Distribution Info' for details. None N/A <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>None. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations.</SPAN></P></DIV></DIV></DIV> A new generation of the United States National Land Cover Database: Requirements, research priorities, design, and implementation strategies 2018-12-01 ISPRS Journal of Photogrammetry and Remote Sensing 146: 108-123. Yang, L., et al. publication https://doi.org/10.1016/j.isprsjprs.2018.09.006 -130.2328 -63.6722 21.7423 52.851 ground condition 2001-01-01 2019-01-01 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) Version 6.2 (Build 9200) ; Esri ArcGIS 10.9.1.28388 1 -107.249941 -93.321062 36.706972 25.373245 See https://www.mrlc.gov/data for the full list of products available. This NLCD product is the version dated June 4, 2021. A formal accuracy assessment has not been conducted for NLCD 2019 Land Cover, NLCD 2019 Land Cover Change, or NLCD 2019 Impervious Surface products. A 2016 accuracy assessment publication can be found here: James Wickham, Stephen V. Stehman, Daniel G. Sorenson, Leila Gass, Jon A. Dewitz., Thematic accuracy assessment of the NLCD 2016 land cover for the conterminous United States: Remote Sensing of Environment, Volume 257, 2021, 112357, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2021.112357. 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. Unknown N/A N/A The Nighttime Lights of the World data set was complied from Defense Meteorological Satellite Program (DMSP) data spanning October 1994 - March 1995. Defense Meteorological Satellite Program (DMSP) Nighttime Lights Defense Meteorological Satellite Program (DMSP) 2011-01-01 National Geophysical Data Center (NGDC), now part of NOAA National Centers for Environmental Information (NCEI) raster digital data https://sos.noaa.gov/datasets/nighttime-lights/ ground condition 1994-01-01 1995-01-01 Landsat Analysis Ready Data (ARD) Analysis Ready Data: Enabling Analysis of the Landsat Archive Landsat ARD 2018-08-28 Hankaui K. Zhang John L. Dwyer Calli B. Jenkerson Leo Lymburner David P. Roy Brian Sauer publication https://www.usgs.gov/core-science-systems/nli/landsat/us-landsat-analysis-ready-data?qt-science_support_page_related_con=0#qt-science_support_page_related_con https://doi.org/10.3390/rs10091363 ground condition 2018-01-01 Landsat Operational Land Imager (OLI) Statistical relative gain calculation for Landsat 8 Landsat OLI 2017-01-01 Jon Dewitz U.S. Geological Survey raster digital data 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/P96HHBIE ground condition 2001-01-01 2016-01-01 Landsat Enhanced Thematic Mapper Plus (ETM+) Landsat-7 ETM+ radiometric calibration status Landsat ETM+ 2016-09-19 Dennis L. Helder Julia A. Barsi Md. Obaidul Haque Brian L. Markham Simon J. Hook Jeffrey S. Czapla-Myers John R. Schott publication https://www.usgs.gov/core-science-systems/nli/landsat/landsat-7?qt-science_support_page_related_con=0#qt-science_support_page_related_con https://doi.org/10.1117/12.2238625 ground condition 1999-01-01 2020-01-01 Landsat Thematic Mapper (TM) Landsat—Earth Observation Satellites Landsat TM 2020-04-08 U.S. Geological Survey publication https://www.usgs.gov/core-science-systems/nli/landsat/landsat-5?qt-science_support_page_related_con=0#qt-science_support_page_related_con https://doi.org/10.3133/fs20153081 ground condition 1984-01-01 2013-01-01 Landsat Multispectral Scanner (MSS) Landsat—Earth Observation Satellites Landsat MSS 2020-04-08 U.S. Geological Survey publication https://www.usgs.gov/core-science-systems/nli/landsat/landsat-5?qt-science_support_page_related_con=0#qt-science_support_page_related_con https://doi.org/10.3133/fs20153081 ground condition 1984-01-01 2013-01-01 Landsat Thermal Infrared Sensor (TIRS) Landsat-8 TIRS thermal radiometric calibration status Landsat TIRS 2017-01-01 Ron Morfitt Nina G. Raqueno Brian L. Markham Matthew Montanaro Julia A. Barsi Simon Hook John R. Schott Aaron Gerace publication https://www.usgs.gov/core-science-systems/nli/landsat/landsat-8?qt-science_support_page_related_con=0#qt-science_support_page_related_con https://doi.org/10.1117/12.2276045 ground condition 2013-01-01 2020-01-01 Digital Elevation Module (DEM) NLCD 2016 Impervious Surface Conterminous United States DEM 2019-01-01 U.S. Geological Survey Jon Dewitz raster digital data 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/P96HHBIE ground condition 2001-01-01 2016-01-01 The VIIRS Nighttime Imagery (Day/Night Band, Enhanced Near Constant Contrast) layer shows the Earth’s surface and atmosphere using a sensor designed to capture low-light emission sources, under varying illumination conditions. Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night band Nighttime Lights Visible Infrared Imaging Radiometer Suite (VIIRS) 2016-01-01 NASA/NOAA raster digital data https://earthdata.nasa.gov/worldview/worldview-image-archive/the-day-night-band-enhanced-near-constant-contrast-of-viirs observed 2016-01-01 United States Geological Survey (USGS) National Land Cover Database (NLCD) NLCD 2016 Land Cover Conterminous United States USGS National Land Cover Database 2019-01-01 Jon Dewitz U.S. Geological Survey raster digital data 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/P96HHBIE ground condition 2001-01-01 2016-01-01 These two sets of regression tree models were the basis of two 2011 initial impervious surface maps. 2019-01-01 Jon Dewitz U.S. Geological Survey, CORE SCIENCE SYSTEMS GEOGRAPHER 605-594-2715 47914 252Nd Street Sioux Falls SD 57198 US dewitz@usgs.gov Visible Infrared Imaging Radiometer Suite (VIIRS) Defense Meteorological Satellite Program (DMSP) USGS National Land Cover Database 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. 2019-01-01 Jon Dewitz U.S. Geological Survey, CORE SCIENCE SYSTEMS GEOGRAPHER 605-594-2715 47914 252Nd Street Sioux Falls SD 57198 US dewitz@usgs.gov Visible Infrared Imaging Radiometer Suite (VIIRS) Defense Meteorological Satellite Program (DMSP) USGS National Land Cover Database 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. 2019-01-01 Jon Dewitz U.S. Geological Survey, CORE SCIENCE SYSTEMS GEOGRAPHER 605-594-2715 47914 252Nd Street Sioux Falls SD 57198 US dewitz@usgs.gov Visible Infrared Imaging Radiometer Suite (VIIRS) Landsat OLI Landsat MSS Landsat TIRS Landsat TM Landsat ARD Defense Meteorological Satellite Program (DMSP) Landsat ETM+ DEM USGS National Land Cover Database The two pairs of initial impervious surface maps - 2 each for an earlier and later image (for example, 2004 was compared to 2001, 2006 to 2004, etc. up to 2019.), - were compared to remove false estimates caused by high reflectance in non-urban areas, as well as to retain impervious values unchanged from the earlier year. 2019-01-01 Jon Dewitz U.S. Geological Survey, CORE SCIENCE SYSTEMS GEOGRAPHER 605-594-2715 47914 252Nd Street Sioux Falls SD 57198 US dewitz@usgs.gov Visible Infrared Imaging Radiometer Suite (VIIRS) Defense Meteorological Satellite Program (DMSP) USGS National Land Cover Database Two training datasets, one of larger extent, one smaller to have different proportions of higher and lower relative impervious according to the extent of brighter and dimmer nighttime lighting, were assembled by imposing two separate thresholds of nighttime lights imagery onto the NLCD 2016 Impervious Surface data layer. Each of the two training datasets were used separately to build regression tree models for predicting percent impervious surface from zero to 100% using Landsat imagery from each respective year as predictive variables. 2019-01-01 Jon Dewitz U.S. Geological Survey, CORE SCIENCE SYSTEMS GEOGRAPHER 605-594-2715 47914 252Nd Street Sioux Falls SD 57198 US dewitz@usgs.gov Defense Meteorological Satellite Program (DMSP) Visible Infrared Imaging Radiometer Suite (VIIRS) USGS National Land Cover Database 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 2019 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. 2019-01-01 Jon Dewitz U.S. Geological Survey, CORE SCIENCE SYSTEMS GEOGRAPHER 605-594-2715 47914 252Nd Street Sioux Falls SD 57198 US dewitz@usgs.gov Visible Infrared Imaging Radiometer Suite (VIIRS) Defense Meteorological Satellite Program (DMSP) USGS National Land Cover Database 2 104424 161190 1 SDE_VAT_132 Product showing the attributes for the impervious cover throughout CONUS National Land Cover Database Table 102 OBJECTID OBJECTID OID 4 10 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. 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 2019 0 255 Red Integer 4 10 0 Count_ Count_ Double 8 38 8 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 2019 0 255 Blue Integer 4 10 0 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 2019 0 255 Green Integer 4 10 0 Value Percent Imperviousness. *while the file structure shows values in range from 0-255, the values of 0-100 are the only real populated values, in addition to a background value of 127. NLCD 2019 127 Background value Producer defined 0 100 percentage 0.1 Value Integer 4 10 0 Opacity A measure of how opaque, or solid, a color is displayed in a layer. NLCD 2019 0 1 0.01 Opacity Integer 4 10 0 Impervious Surface Attributes Attributes defined by USGS and ESRI. dataset Pixel 40235 41251 30.000000 30.000000 8 1 Upper Left TRUE LZ77 1 pixel codes SDR TRUE row and column 30.000000 30.000000 20220209