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Mapping forest vegetation for the continental United States using modified random forests imputation
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Mapping forest vegetation for the continental United States using modified random forests imputation

Presented by SERNW.

6/26/2018
When: Tuesday, June 26, 2018
9:00 AM Pacific
Where: United States
Contact: David Sabaj-Stahl

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Maps of the number, size, and species of trees in forests across the continental United States are desirable for many applications such as estimating terrestrial carbon resources, predicting tree mortality following wildfires, and for forest inventory. However, detailed mapping of trees for large areas is not feasible with current technologies, but statistical methods for matching the forest plot data with biophysical characteristics of the landscape offer a practical means to populate landscapes with a limited set of forest plot inventory data. We used a modified random forests approach with Landscape Fire and Resource Management Planning Tools (LANDFIRE) vegetation and biophysical predictors to impute plot data collected by the US Forest Service’s Forest Inventory Analysis (FIA) to the landscape at 30-m grid resolution. The main output of this project is a map of imputed plot IDs at 30 × 30 m spatial resolution for the western United States that can be linked to the FIA databases to produce tree-level maps or to map other plot attributes. The results showed good correspondence between the target LANDFIRE data and the imputed plot data, with an overall within-class agreement of 79% for forest cover, 96% for forest height, and 92% for vegetation group. 

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Dr. Karin Riley is a research ecologist with the United States Department of Agriculture Forest Service. Dr. Riley is affiliated with the USDAFS Station in Missoula, MT; the USDAFS Rocky Mountain Research Station (RMRS) in Ft. Collins, CO; and the associated Human Dimensions Science Program at the RMRS. Much of Dr. Riley's current research focuses on better understanding the relationship between climate and wildfire, and how this relationship might shift with climate change. In addition, she is interested in how spatial planning can be utilized to inform fire and landscape management options.

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