Forest Inventory and Analysis (FIA)

LF and FIA have been partners since LF was chartered in 2004. They formalized the relationship with a data sharing agreement in 2005. Much of the success of the LF program is due in part to FIA data.

National Gap Analysis Program (GAP)

In 2014, LF entered into a Memorandum of Understanding (MOU) with GAP to produce national-scale land cover, vegetation, fuel, and fire products.

As a result of the MOU, LF and GAP coordinated their work in a Joint Activities Report to improve scientific consistency and production efficiency.

The programs are working together on Remap strategy prototypes and will soon team up on Remap production.

GAP and LF’s partnership with the North American Bird Conservation Initiative (NABCI), as described in the article, Coming Together for an All-Lands Dataset to Support Wildfire and Wildlife Conservation Planning, will result in land cover data being more detailed and thematically richer.

Natural Resources Conservation Service – National Resources Inventory (NRCS – NRI)

In 2009, the United States Department of Agriculture (USDA) NRCS and LF collaborated on a Pilot Project to assess the usefulness of NRCS NRI Program rangeland plot data. The assessment involved a remap of LF's Existing Vegetation Type (EVT) layer in a region of Montana.

LF and NRCS established a formal working relationship with a Memorandum of Understanding (MOU) in 2015, from which additional plot data became available as part of the NRI.

National Land Cover Database (NLCD)

Three programs – NLCD, GAP and LF - collaborated in 2015 to compare NLCD 2011 and LF 2010 products. The purpose of the Vegetation Classification Crosswalk was to help users understand similarities and differences between the products and select appropriate data sets for their applications.

Forest Service (FS) Rocky Mountain Research Station (RMRS)

LF products are designed to facilitate national- and regional-level strategic planning and support fire and fuel management activities. These same characteristics provide the research community with an ideal data set for a number of research applications within the USFS RMRS.