The long-term goal of this project is to develop data critical to wildland fire modeling and response in the Northern Region of the US Forest Service. The project directly supports the Societal Benefit Area Ecological Forecasting, which in turn will support decisions that affect other Societal Benefit Areas such as Heath and Water Resources. Stage 1 investigates the feasibility of using earth observations tools to develop data and integration methods that will enhance the value of two existing decision support tools. This stage focuses on a specific data need: accurate and precise mapping of whitebark pine (Pinus albicaulis) and spruce-fir (Picea Engelmannii/Abies lasiocarpa) forests. Whitebark pine is a keystone species that has been massively impacted across its range by insects and disease, and is warranted but precluded for listing under the Endangered Species Act. Climate change threatens the probability of its persistence across its range. Certain types of spruce-fir forests are critical habitat for the federally listed Canada lynx (Lynx Canadensis). Although they co-occur, fire prescriptions for the two forest types are sometimes in direct conflict. Therefore, Northern Region staff require vegetation models that can support decisions about immediate fire response, near-term vegetation treatments and prescribed fire, and long-term climate change scenario planning. This feasibility study will explore the following questions 1) does sufficient data exist to develop precise and accurate maps of whitebark pine? 2) Can whitebark regeneration be mapped with the same methods used to map mature trees? 3) Can seed tree sites be mapped using object-oriented image classification of high-resolution imagery? 4) Can the methods used to map a single species be used to map spruce-fir forests associations? 5) How well can this mapping be combined with downscaled climate models to predict mountain pine beetle infestation, and fire probability and severity under different climate change scenarios?