Fuel mapping is a complex and often multidisciplinary process, involving remote sensing, ground-based validation, statistical modelling, and knowledge-based systems. The scale and resolution of fuel mapping depend both on objectives and availability of spatial data layers. We demonstrate use of the Fuel Characteristic Classification System (FCCS) for fuel mapping at two scales and resolutions: the conterminous USA (CONUS) at 1 km resolution and the Wenatchee National Forest, in Washington State, at 25 m resolution. We focus on the classification phase of mapping — assigning a unique fuelbed to each mapped cell in a spatial data layer. Using a rule-based method, we mapped 112 fuelbeds onto 7.8 million 1 km cells in the CONUS, and mapped 34 fuelbeds onto 18 million 25 m cells in the Wenatchee National Forest. These latter 34 fuelbeds will be further subdivided based on quantitative spatial data layers representing stand structure and disturbance history. The FCCS maps can be used for both modelling and management at commensurate scales. Dynamic fuel mapping is necessary as we move into the future with rapid climatic and land-use change, and possibly increasing disturbance extent and severity. The rule-based methods described here are well suited for updating with new spatial data, to keep local, regional, and continental scale fuel assessments current and inform both research and management.
A stream classification system for the conterminous United States
