County-level land cover patterns for the conterminous United States for the 2020 RPA Assessment

This data publication includes the status and trends of the areas of land cover classes, forest fragmentation classes, and landscape mosaic classes from 2001 to 2016 at the county level, for the conterminous United States (CONUS). Land cover is reported in ten classes representing an aggregation of the original 17 classes defined by the original land cover map producers. Forest fragmentation is reported in six classes representing the fragmentation of the forest land cover class, as calculated for each of six scales of analysis via a moving window (spatial convolution) algorithm. Landscape mosaics are reported in 19 classes plus one water class, representing the juxtaposition of agriculture and/or developed land cover with all other land cover, as calculated at one scale of analysis via a moving window algorithm. Land cover is presented in four data files comprising transition tables (to and from different land cover classes), at the county level, for the time periods 2001-2006, 2006-2011, 2011-2016, and 2001-2016. Forest fragmentation is reported in one data file containing county-level fragmentation class area totals in 2001, 2006, 2011, and 2016. One landscape mosaic data file contains transition tables at the county level for all land area for the time period 2001-2016, to and from mosaic classes and/or water. A second landscape mosaic data file contains similar transition tables, at the county level, for the forest area only for the time period 2001-2016; in this file an additional non-mosaic, non-water class called nonforest is included such that forest area changes (losses and gains) can be evaluated in relation to their original and final mosaic classes.
These data support the landscape pattern analyses reported in Chapter 4 (Land Resources) of the 2020 Resources Planning Act (RPA) Assessment (https://www.fs.usda.gov/research/inventory/rpaa).
These data were published on 03/08/2023. Metadata updated on 10/17/2023 to include reference to published RPA Assessment. Examples of metrics, analysis scales, and data summaries are available for a similar but more comprehensive analysis conducted for the 2010 RPA Assessment (Riitters 2011). A rationale for the choices of pattern metrics and analysis procedures is available (Riitters 2019). The use of these data in the 2020 RPA Assessment is illustrated in a more comprehensive format in Riitters and Robertson (2021), Riitters et al. (2020), and Homer et al. (2020). An additional example application which includes a treatment of transition matrices as finite-state, discrete-time Markov chains can be found in Riitters et al. (2009).