GNN Mapping of Existing Vegetation, Pacific Coast States

Major funders and collaborators

Project summary

This project involves developing detailed maps of existing forest vegetation and land cover across all land ownerships in the Pacific Coast States (Oregon, Washington, and parts of California). A five-year mapping cycle is planned, but is funding-dependent. The mapping is integrated with ongoing sample-based forest inventories conducted by the Forest Inventory and Analysis program (FIA) at the PNW Station, and Current Vegetation Survey of Region 6, USDA Forest Service, and the BLM in western Oregon. For each of our modeling regions, we are using gradient imputation (Gradient Nearest Neighbor, or GNN; 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 FIA field plots with satellite imagery and mapped environmental data. A suite of fine-scale plot variables is imputed to each pixel in a digital map, and regional maps can be constructed for many of the same vegetation attributes available for FIA plots. Nonforest areas are mapped using ancillary data such as the National Land Cover Data, and maps of Ecological Systems developed in a related LEMMA project as they become available. All GNN map products are grid-based at 30-m spatial resolution.

This project began in fall 2005, and we plan to map approximately one half-state per year (see our mapping schedule). The mapping work is organized geographically around mapping regions that correspond approximately to ecoregions. Modeling regions would be re-mapped with updated imagery and plot data every five years. We have focused activity in the first year on developing plot and spatial databases to support modeling and mapping across all of Oregon and Washington. The Forest Service’s Remote Sensing Applications Center (RSAC) is acquiring, pre-processing, and mosaicking the Landsat ETM satellite imagery used in mapping.

Research is an important component of this project. We are addressing research questions on: (1) statistical methods for spatial prediction; (2) landscape characterization (environmental and disturbance factors influencing patterns and dynamics of ecological communities); and (3) scaling and linking of vegetation maps to models of stand and landscape dynamics for regional analysis of management and disturbance effects.

The project is being conducted by the LEMMA team (PNW Research Station and Oregon State University) at the Corvallis Lab, in close collaboration with the Western Wildlands Environmental Threats Assessment Center, the Interagency Mapping and Assessment Project (IMAP), Northwest Forest Plan Effectiveness Monitoring, the Remote Sensing Applications Center, and Forest Inventory and Analysis at the PNW Research Station.

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