. Severe mountain pine beetle (MPB) epidemics can degrade ecosystem services and
socioeconomic assets. Mapping outbreak progression provides tools to mitigate damages and
analyze MPB attack processes. Current time-series methods for mapping disturbance focus
on extent rather than severity. Infestation severity, defined by within-pixel percentage, is
more robust for answering a variety of ecologic questions. We develop a time-series regression
approach to map infestation severity from 2005 to 2015 in the U.S. Central Rocky Mountains.
Covariates include spectral data from all available dates of Landsat imagery, topographic data,
and US Forest Service aerial detection survey (ADS) polygons. We collect model reference data
by interpreting National Agricultural Imagery Program images. Validation against a randomly
selected subset of the data results in no statistical difference between predicted and observed
severity. The mean absolute deviation is 7.7% with a root-mean-square error of 9.9%.
Average (maximum) severity increased from 9.4% (49.7%) in 2005 to 17.6% (58.8%) in
2015. Our raster maps identify widespread, lower severity infestation absent from the ADS.
Our maps can improve mitigation efforts by allowing managers to: address low-severity
infestations before they intensify, monitor intensifying infestations within previously identified
outbreak extents, and combine infestation severity with other forest metrics.