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The LCMAP project has generated an integrated suite of annual land cover and land surface change products for the Conterminous United States based on time series data from the Landsat record from 1985–2017. LCMAP Collection 1.0 Science Products are based on the USGS implementation of the Continuous Change Detection and Classification (CCDC) algorithm.
The need for improved understanding and management of land surface change requires increased understanding of the basic drivers of change, identification of potential consequences of change on human and natural systems, and greater insight into the impacts and feedbacks of climate change. The geospatial community requires a new generation of monitoring data and information to meet this need across a wide range of applications. Land cover and land change products need to span larger geographic extents, over longer time periods, at higher spatial resolutions, and provide more systematic and consistent information on change than ever before.
LCMAP Science Products are developed by applying time-series modeling to U.S. Landsat Analysis Ready Data (ARD) to detect land surface change. An application of the Continuous Change Detection and Classification (CCDC, Zhu and Woodcock 2014) was developed by the LCMAP Science Team at the USGS Earth Resources Observation and Science (EROS) Center (Brown et al., 2020). LCMAP Collection 1.0 Science Products include ten annual products for the years 1985–2017. The final year of products in the dataset, 2017, are considered provisional for the initial release (see LCMAP Science Product Guide for more information). There are five land surface change products, produced directly from CCDC time series models, and five land cover products, produced by the classification of the time series models.
LCMAP Collection 1.0 Science Products are processed to 30-meter spatial resolution in an Albers Equal Area Conic (AEA) projection using the World Geodetic System 1984 (WGS84) datum and gridded to the Landsat ARD tiling scheme.
LCMAP Collection 1.0 Science Products are available for the conterminous United States from 1985–2017, with 2017 considered provisional status. Products are available via EarthExplorer, the LCMAP Viewer, and the CONUS Mosaic download site.
LCMAP Collection 1.0 Science Products available for download through EarthExplorer include ten individual products for a single year packaged and delivered in a single .tar file. The .tar packages “untar” (unzip) into ten individual Georeferenced Tagged Image File Format (GeoTIFF) (.tif) files for each product and an Extensible Markup Language (XML) (.xml) metadata file. Additional product specifications are located in the LCMAP Science Product Guide.
The 10 annual science products are available for download through the LCMAP Viewer. The LCMAP Viewer allows users to draw a bounding box in the viewer for an area of interest to download the products, metadata, and animated graphics.
CONUS Mosaic Download Site
The 10 annual science products are available to download as mosaics of the conterminous United States (CONUS) from 1985-2017. The CONUS level science products are available through this download portal.
Please see the LCMAP Data Access page for more information.
The five land surface change products available through EarthExplorer (SCTIME, SCMAG, SCLAST, SCSTAB, and SCMQA) and the SCMAG product available through the LCMAP Viewer do not have color ramps applied to them. For the EarthExplorer-distributed products, ESRI *.lyr files (compatible with ArcGIS) and *.txt files (compatible with QGIS) with the default LCMAP color ramps are provided below. For the LCMAP Viewer products, the appropriate .lyr file is included in the zip file with a README file that details how to apply the color ramps.
A validation assessment of the LCMAP Collection 1.0 annual land cover products was conducted with an independently collected reference data set. Validation analysis directly compared reference labels with annual LCMAP land cover map attributes by cross tabulation. The results of that assessment are available for download on ScienceBase as confusion matrices for land cover agreement and land cover change agreement. Overall CONUS land cover agreement across all years was found to be 82.5%. Annual and regional accuracies are also reported. For more information on the independent reference data set, see the LCMAP Reference Data webpage.
For individual product caveats and constraints, see the LCMAP Collection 1.0 Science Product Guide.
LCMAP Collection 1.0 Science Product Guide (SPG)
LCMAP Collection 1.0 Continuous Change Detection and Classification (CCDC) Algorithm Description Document (ADD)
LCMAP Collection 1.0 Data Format Control Book (DFCB)
LCMAP Reference Data Product Guide
LCMAP Science Products Digital Object Identifier (DOI): https://doi.org/10.5066/P9W1TO6E
There are no restrictions on the use of LCMAP Science Products. It is not a requirement of data use, but the following citation may be used in publication or presentation materials to acknowledge the USGS as a data source and to credit the original research.
LCMAP Collection 1.0 Science Products courtesy of the U.S. Geological Survey.
Brown, J.F., Tollerud, H.J., Barber, C.P., Zhou, Q., Dwyer, J.L., Vogelmann, J.E., Loveland, T.R., Woodcock, C.E., Stehman, S.V., Zhu, Z., Pengra, B.W., Smith, K., Horton, J.A., Xian, G., Auch, R.F., Sohl, T.L., Sayler, K.L., Gallant, A.L., Zelenak, D., Reker, R.R., and Rover, J., (2020). Lessons learned implementing an operational continuous United States national land change monitoring capability: The Land Change Monitoring, Assessment, and Projection (LCMAP) approach. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2019.111356
Zhu, Z., Woodcock, C.E. (2014). Continuous change detection and classification of land cover using all available Landsat data: Remote Sensing of Environment 144: 152–171. https://doi.org/10.1016/j.rse.2014.01.011.
Reprints, citations of papers or oral presentations based on USGS data are welcome to help the USGS stay informed of how data are being used. These can be sent to User Services at email@example.com
Dwyer, J., Roy, D., Sauer, B., Jenkerson, C., Zhang, H., and Lymburner, L. (2018). Analysis Ready Data: Enabling analysis of the Landsat archive. Remote Sensing. https://doi.org/10.3390/rs10091363
Foga, S., Scaramuzza, P.L., Guo, S., Zhu, Z., Dilley Jr, R.D., Beckmann, T., Schmidt, G.L., Dwyer, J.L., Joseph Hughes, M., and Laue, B., 2017. Cloud detection algorithm comparison and validation for operational Landsat data products. Remote Sensing of Environment, 194, 379-390, https://doi.org/10.1016/j.rse.2017.03.026