Title:

Tree mortality and damage maps derived from high-resolution remote sensing data and Landsat time series algorithms

Author(s):

Bright, Benjamin C.; Meddens, Arjan J.H.; Hudak, Andrew T.; Hicke, Jeffrey A.

Publication Year:

2026

How to Cite:

These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the following citation:

Bright, Benjamin C.; Meddens, Arjan J.H.; Hudak, Andrew T.; Hicke, Jeffrey A. 2026. Tree mortality and damage maps derived from high-resolution remote sensing data and Landsat time series algorithms. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2026-0036

Abstract:

This data publication contains digital raster and vector maps of dead and damaged trees derived from high-resolution remote sensing data and Landsat time series algorithms for six different study areas in the western United States (2010-2021) where prevalent tree damage caused by biotic disturbance agents had occurred. Study area locations and primary disturbance agents were: 1) Stanley, ID, mountain pine beetle; 2) Chimney Park, WY, mountain pine beetle; 3) Hinsdale, CO, spruce beetle; 4) Elk City, ID, spruce beetle; 5) Klamath, OR, Armillaria root disease; and 6) Turah, MT, western spruce budworm. For each study area, high-resolution remote sensing data were used to map dead trees at high resolution (2 or 2.4 meters); these maps were then used to evaluate four Landsat time series algorithms that detect forest disturbance: 1) Landsat-based detection of Trends in Disturbance and Recovery (LandTrendr), 2) Continuous Change Detection and Classification (CCDC), 3) Meddens, and 4) Landscape Change Monitoring System (LCMS).

Keywords:

biota; geoscientificInformation; Ecology, Ecosystems, & Environment; Forest & Plant Health; Insects; Inventory, Monitoring, & Analysis; remote sensing; high-resolution imagery; Landsat time series; mapping; tree mortality; tree damage; forest insects; Idaho; Wyoming; Colorado; Oregon; Montana

Related publications:

• Bright, Benjamin C.; Hicke, Jeffrey A.; Hudak, Andrew T. 2012. Estimating aboveground carbon stocks of a forest affected by mountain pine beetle in Idaho using lidar and multispectral imagery. Remote Sensing of Environment. 124: 270-281. https://doi.org/10.1016/j.rse.2012.05.016 https://research.fs.usda.gov/treesearch/41572
• Bright, Benjamin C.; Hudak, Andrew T.; Meddens, Arjan J.H.; Egan, Joel M.; Jorgensen, Carl L. 2020. Mapping multiple insect outbreaks across large regions annually using Landsat time series data. Remote Sensing. 12(10): 1655. https://doi.org/10.3390/rs12101655 https://research.fs.usda.gov/treesearch/60281
• Bright, Benjamin C.; Meddens, Arjan J.H.; Hudak, Andrew T.; Hicke, Jeffrey A. 2026. Comparing Landsat time series algorithms for detecting differing levels of tree mortality. Forestry: An International Journal of Forest Research. 99(5): cpag074. https://doi.org/10.1093/forestry/cpag074
• More (5 total)

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