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The importance of characterizing, quantifying, and monitoring land cover, land use, and their changes has been widely recognized by global and environmental change studies. Since the early 1990s, three U.S. National Land Cover Database (NLCD) products (circa 1992, 2001, and 2006) have been released as free downloads for users. The NLCD 2006 also provides land cover change products between 2001 and 2006. To continue providing updated national land cover and change datasets, a new initiative in developing NLCD 2011 is currently underway. We present a new Comprehensive Change Detection Method (CCDM) designed as a key component for the development of NLCD 2011 and the research results from two exemplar studies. The CCDM integrates spectral-based change detection algorithms including a Multi-Index Integrated Change Analysis (MIICA) model and a novel change model called Zone, which extracts change information from two Landsat image pairs. The MIICA model is the core module of the change detection strategy and uses four spectral indices (CV, RCVMAX, dNBR, and dNDVI) to obtain the changes that occurred between two image dates. The CCDM also includes a knowledge-based system, which uses critical information on historical and current land cover conditions and trends and the likelihood of land cover change, to combine the changes from MIICA and Zone. For NLCD 2011, the improved and enhanced change products obtained from the CCDM provide critical information on location, magnitude, and direction of potential change areas and serve as a basis for further characterizing land cover changes for the nation. An accuracy assessment from the two study areas show 100% agreement between CCDM mapped no-change class with reference dataset, and 18% and 82% disagreement for the change class for WRS path/row p22r39 and p33r33, respectively. The strength of the CCDM is that the method is simple, easy to operate, widely applicable, and capable of capturing a variety of natural and anthropogenic disturbances potentially associated with land cover changes on different landscapes.

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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.

15The U.S. Geological Survey's Land Change Monitoring, Assessment, and Projection (LCMAP) initiative 16 is a new end-to-end capability to continuously track and characterize changes in land cover, use, and 17 condition to better support research and applications relevant to resource management and environmental 18 change. Among the LCMAP product suite, there are annual land cover maps that will be available to the 19 public. This paper describes an approach to optimize the selection of training and auxiliary data for 20 deriving the thematic land cover maps based on all available clear observations from Landsats 4-8. land cover classification, Landsat 40 community, data needs are changing and innovative products and mapping approaches to characterize 47 land cover are required to meet the community's appetite for science-quality, geospatial land cover data. 48The emergence of land change science has had a particularly significant influence on land cover mapping 49 and monitoring requirements. Driven by concerns about climate change and resource sustainability, 50 Rindfuss et al. (2004) and Turner et al. (2007) defined land change science as a framework to understand 51the interactions between people and nature that lead to changes in the type, magnitude, condition, and 52 location of land use and cover. Implicit is the need to use remote sensing, modeling, and synthesis to 53 understand and explain land change rates, causes, and consequences. Meeting the diverse needs of land 54 cover data users means that the data producers must transform traditional approaches into new strategies 55 that generate higher quality products with additional land cover variables, more detailed legends, and 56 more frequent geospatial information and statistics on change. 57The USGS response to the growing requirements for land use, cover, and condition data, information, and 58 knowledge is the Land Change Monitoring, Assessment, and Projection (LCMAP) initiative. LCMAP is 59 an end-to-end capability to continuously track and characterize changes in land cover, use, and condition 60 and translate such information into assessments of current and historical processes of cover and change 61 that can serve as the science foundation for research and applications relevant to resource management 62 and environmental change. As implied in the name, key elements include mapping and monitoring 63 change, analyzing and assessing the rates, causes, and consequences of change, and providing scenario-64 based projections of future land change. LCMAP continues the long-standing USGS commitment to land 65 cover research and development and represents the foundation for a Landsat-based Federal land 66 monitoring system. Furthermore, LCMAP will stimulate geographic research on understanding the 67 connections between human activity and natural systems, and ultimately represents an essential step 68 towards better understanding the combined impacts of climate and land use and land cover change. 69

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