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Open AccessArticle

Overall Methodology Design for the United States National Land Cover Database 2016 Products

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ASRC Federal Data Solutions, Contractor to the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, Work Performed under USGS Contract 140G0119C0001, Sioux Falls, SD 57198, USA
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USGS EROS Center, Sioux Falls, SD 57198, USA
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Stinger Ghaffarian Technologies (SGT), Contractor to the USGS EROS Center, Work Performed under USGS Contract G15PC00012, Sioux Falls, SD 57198, USA
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Department of Natural Resources and the Environment, University of Connecticut, Storrs, CT 06269, USA
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Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(24), 2971; https://doi.org/10.3390/rs11242971
Received: 18 November 2019 / Revised: 5 December 2019 / Accepted: 7 December 2019 / Published: 11 December 2019
The National Land Cover Database (NLCD) 2016 provides a suite of data products, including land cover and land cover change of the conterminous United States from 2001 to 2016, at two- to three-year intervals. The development of this product is part of an effort to meet the growing demand for longer temporal duration and more frequent, accurate, and consistent land cover and change information. To accomplish this, we designed a new land cover strategy and developed comprehensive methods, models, and procedures for NLCD 2016 implementation. Major steps in the new procedures consist of data preparation, land cover change detection and classification, theme-based postprocessing, and final integration. Data preparation includes Landsat imagery selection, cloud detection, and cloud filling, as well as compilation and creation of more than 30 national-scale ancillary datasets. Land cover change detection includes single-date water and snow/ice detection algorithms and models, two-date multi-index integrated change detection models, and long-term multi-date change algorithms and models. The land cover classification includes seven-date training data creation and 14-run classifications. Pools of training data for change and no-change areas were created before classification based on integrated information from ancillary data, change-detection results, Landsat spectral and temporal information, and knowledge-based trajectory analysis. In postprocessing, comprehensive models for each land cover theme were developed in a hierarchical order to ensure the spatial and temporal coherence of land cover and land cover changes over 15 years. An initial accuracy assessment on four selected Landsat path/rows classified with this method indicates an overall accuracy of 82.0% at an Anderson Level II classification and 86.6% at the Anderson Level I classification after combining the primary and alternate reference labels. This methodology was used for the operational production of NLCD 2016 for the Conterminous United States, with final produced products available for free download. View Full-Text
Keywords: national land cover database; land cover change; Landsat; ancillary data; hierarchical postprocessing; temporal/spatial context; pixel/object-based information integration national land cover database; land cover change; Landsat; ancillary data; hierarchical postprocessing; temporal/spatial context; pixel/object-based information integration
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MDPI and ACS Style

Jin, S.; Homer, C.; Yang, L.; Danielson, P.; Dewitz, J.; Li, C.; Zhu, Z.; Xian, G.; Howard, D. Overall Methodology Design for the United States National Land Cover Database 2016 Products. Remote Sens. 2019, 11, 2971.

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