GNN Mapping of Existing Vegetation for NWFP Effectiveness Monitoring

Major funders and collaborators

Project summary

For this project we developed detailed maps of existing forest vegetation and land cover across the area covered by the Northwest Forest Plan (NWFP) in Washington, Oregon, and California. We used Gradient Nearest Neighbor (GNN) imputation (Ohmann and Gregory 2002) to map detailed vegetation composition and structure for areas of forest and woodland. GNN uses multivariate gradient modeling to integrate data from field plots with satellite imagery and mapped environmental data. The mapping is integrated with ongoing forest inventories conducted by the Forest Inventory and Analysis program (FIA) (PNW Research Station, USDA FS), Current Vegetation Survey (Region 6, USDA FS, and BLM in western Oregon), and Region 5 (USDA FS) forest inventory. A suite of fine-scale plot variables is imputed to each pixel in the GNN digital map, and regional maps can be constructed for many of the same vegetation attributes available for the plots. Areas of nonforest are masked out using ancillary data. All GNN map products are grid-based at 30-m spatial resolution.

Maps were developed for each modeling region for two dates: 1996 and 2006 in Oregon and Washington, and 1994 and 2007 in California. The primary research component of this project focused on techniques for developing temporally consistent maps using nearest neighbors methods. The GNN map products are being used in assessing changes in late-successional and old-growth forest, and habitat for the northern spotted owl, marbled murrelet, and aquatic species, as part of Effectiveness Monitoring for the NWFP.