Public and private forest ownership in the conterminous United States circa 2009: distribution of six ownership types - geospatial dataset

This data publication contains raster data depicting the spatial distribution of forest ownership types in the conterminous United States circa 2009. The data are a modeled representation of forest land by ownership type, and include three types of public ownership: federal, state, and local, as well as three types of private: family (includes individuals and families), corporate, and other private (includes conservation and natural resource organizations, unincorporated partnerships and associations, and Native American tribal lands).The data are designed for strategic analyses at a national or regional scale which require spatially explicit information regarding the extent, distribution, and prevalence of the ownership types represented. The data are not recommended for tactical analyses on a sub-regional scale, or for informing local management decisions. Furthermore, map accuracies vary considerably and thus the utility of these data can vary geographically under different ownership patterns.A corresponding Research Map (RMAP) has been produced to cartographically portray this dataset (Hewes et al. 2014). An associated data publication (Nelson et al. 2010) also protrays ownership types of the conterminous United States, but it primarily depicts National Forest and other public on the public side, and percent in corporate ownership on the private side. This new data publication depicts public (federal, state, and local) and private (family, corporate, and other private) ownership types. Original metadata date was 06/11/2014. Minor updates to one of the references that has now been published was done on 09/05/2014. Additional minor metadata updates completed on 12/14/2016 and 02/06/2017. On 07/23/2020 a new version of these data became available (Sass et al. 2020) and on 09/10/2025 an even newer version was published (Harris et al. 2025). On 03/19/2026, "circa 2009" was added to the title to help prevent confusion with related data publications along with a few minor updates to URLs, etc.