The LANDFIRE Program developed a rich suite of consistent spatial data sets for the entire United States. These spatial data sets were designed for very large landscape, regional and national applications.  Two of these spatial layers are particularly unique and interesting, Departure and Uncharacteristic Vegetation.  Click on the link for an interactive map that allows you to explore these two products.

Departure is a metric that indicates how different the current composition and structure of vegetation is from estimated historical conditions.  This metric is identical to Fire Regime Condition Class (FRCC) in LANDFIRE (V1.0), and is generally called FRCC in the fire literature (link to FRCC in LANDFIRE).  A departure value is computed for each unique historical vegetation type (called Biophysical Settings or BpS) within an Ecological Subsection. The higher the departure index value for a BpS, the greater the estimated difference between current and historic in that Ecological Subsection. Departure is a landscape scale metric, so care must be taken when zooming in too closely on this data.  Small areas within a landscape may be close to current conditions, but the landscape as a whole may be quite departed.

Uncharacteristic vegetation is an important part of estimated departure from historic conditions since by definition it was either not present or very rare in the past.  Uncharacteristic vegetation generally has two forms---Native and Exotic.  Uncharacteristic Native vegetation are local species that are invading areas/locations they were not traditionally located in, or they have a structure that was likely unknown in the past. An example of the first is the Pinyon-Pine/Juniper type invading sagebrush, and an example of the second could be Longleaf Pine with excessive canopy closure. Uncharacteristic Exotic vegetation is just another name for an invasive species, such as Cheatgrass in the Great Basin.  Note that limited information was available for mapping invasive species, and invasive ground cover of less than 20% may not have been identified from  the satellite imagery consistently.