Skip to main content
U.S. flag

An official website of the United States government

Mapping mountain pine beetle mortality through growth trend analysis of time-series landsat data

June 18, 2014

Disturbances are key processes in the carbon cycle of forests and other ecosystems. In recent decades, mountain pine beetle (MPB; Dendroctonus ponderosae) outbreaks have become more frequent and extensive in western North America. Remote sensing has the ability to fill the data gaps of long-term infestation monitoring, but the elimination of observational noise and attributing changes quantitatively are two main challenges in its effective application. Here, we present a forest growth trend analysis method that integrates Landsat temporal trajectories and decision tree techniques to derive annual forest disturbance maps over an 11-year period. The temporal trajectory component successfully captures the disturbance events as represented by spectral segments, whereas decision tree modeling efficiently recognizes and attributes events based upon the characteristics of the segments. Validated against a point set sampled across a gradient of MPB mortality, 86.74% to 94.00% overall accuracy was achieved with small variability in accuracy among years. In contrast, the overall accuracies of single-date classifications ranged from 37.20% to 75.20% and only become comparable with our approach when the training sample size was increased at least four-fold. This demonstrates that the advantages of this time series work flow exist in its small training sample size requirement. The easily understandable, interpretable and modifiable characteristics of our approach suggest that it could be applicable to other ecoregions.

Citation Information

Publication Year 2014
Title Mapping mountain pine beetle mortality through growth trend analysis of time-series landsat data
DOI 10.3390/rs6065696
Authors Lu Liang, Yanlei Chen, Todd J. Hawbaker, Zhi-Liang Zhu, Peng Gong
Publication Type Article
Publication Subtype Journal Article
Series Title Remote Sensing
Series Number
Index ID 70112906
Record Source USGS Publications Warehouse
USGS Organization Geosciences and Environmental Change Science Center