Andrew T. Hudak
I am a Research Forester with the
USFS Rocky Mountain Research Station in
Moscow, Idaho.
I am also affiliated with the Departments of Forest Resources and Rangeland Ecology and Management in the College of Natural Resources at the University of Idaho.
Landscape, Fire and Vegetation Ecology; Remote Sensing of Vegetation Structure; Forest and Rangeland Ecosystem Management
1. Characterizing forest fire burn severity, both remotely and on the ground, to produce improved fire mapping, for rapid response by Burned Area Eemergency Response (BAER) teams, and better understanding of the controls on burn severity patterns across different forest types in the USA. This project is funded through the interagency Joint Fire Science Program and an important objective is to cooperate safely with the Incident Command on active wildfires. A more comprehensive description of this burn severity project is available at the website of University of Idaho collaborators.
2. Assessing fuel loads across forest edges in Idaho. Fuel loadings in the overstory, understory, and forest floor vary according to distance from the forest edge, stand age, species composition, management history, and topographic position in the landscape. Field data will be linked statistically with remotely sensed imagery and other environmental data to map fuel characteristics across the landscape. Our study areas are along a dry-wet precipitation gradient and include University of Idaho Experimental Forest, Boise Basin Experimental Forest, Priest River Experimental Forest, Deception Creek Experimental Forest, Spokane Indian Reservation, and Couer d' Alene Indian Reservation. This project is funded through the interagency Joint Fire Science Program and is part of a larger endeavor to compare the effects of climate and management on the distribution of forest fuels; parallel work is proceeding in the dry and wet forests of Puerto Rico and Alaska.
3. Application of lidar remote sensing for precision forest management. Lidar, similar to radar, is an active remote sensing laser technology used to measure the height of the ground, the top of the canopy, and the intervening canopy layers. It has tremendous potential as a tool for precision forest management. Current efforts are focused on relating lidar with plot validation data. This project is funded by the Agenda 2020 program to promote mutually beneficial research partnerships between public forest management agencies and private industry.
4. Lidar remote sensing is best suited for characterizing forest canopy structure, while hyperspectral remote sensing is better suited for capturing forest health. Wildfires pose a significant to life and property, and fuel treatment activities have been promoted by the Healthy Forests Initiative, so improved techniques to map fuels by combining the strengths of multiple remote sensors is warranted. This project is funded by the Agenda 2020 program to promote mutually beneficial research partnerships between public forest management agencies and private industry.
5. Relating spatially-discrete forest inventory plot data to spatially-continuous Landsat and environmental data for mapping forest structural variables at the regional scale using imputation. Collaborators at the Moscow Forestry Sciences Laboratory have developed the Most Similar Neighbor imputation model, while collaborators at the Corvallis Forestry Sciences Laboratory have developed the Gradient Nearest Neighbor imputation method. My objective is to compare the utility of these imputation approaches for mapping a variety of forest structural variables across western Oregon.
6. Structural maps such as those produced in items 1, 2 and 3 above serve as valuable spatial inputs into ecological process models such as the Forest Vegetation Simulator.
7. Exploring the human-environmental interactions that determine fire and vegetation patterns in rangelands. Fire suppression as a result of decades of overgrazing has caused woody plant encroachment across much of the global savannas. Natural (e.g. edaphic) and human (e.g. management) factors interact to determine savanna vegetation patterns, which are related to historic fire patterns through mutual feedbacks. This research is funded by a grant from the National Science Foundation's Biocomplexity in the Environment program. Work to date has been centered on Madikwe Game Reserve in South Africa.
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