Mapping causal agents of disturbance in boreal and arctic ecosystems of North America using time series of Landsat data

• Published in: Remote sensing of environment Vol. 272; p. 112935
• Main Authors: Zhang, Yingtong, Woodcock, Curtis E., Chen, Shijuan, Wang, Jonathan A., Sulla-Menashe, Damien, Zuo, Zhenpeng, Olofsson, Pontus, Wang, Yetianjian, Friedl, Mark A.
• Format: Journal Article
• Language: English
• Published: New York Elsevier Inc 01-04-2022; Elsevier BV
• Subjects: ABoVE; Algorithms; Change detection; Confidence intervals; Disturbance; Disturbances; Domains; Drought; Ecosystems; Fire; Fire damage; Fires; Flooding; Forest ecosystems; Forest fires; Forest harvesting; Infestation; Information processing; Insects; Land cover; Land use; Landsat; Logging; Mapping; Pests; Polar environments; Remote sensing; Satellite observation; Seasonal variations; Statistical analysis; Tasseled Cap; Terrestrial ecosystems; Time series; North America; Logging; Insects; Time series; Disturbance; Landsat; Fire; Tasseled Cap; ABoVE
• ISSN: 0034-4257; 1879-0704
• DOI: 10.1016/j.rse.2022.112935

The arctic and boreal biomes are changing as temperatures increase, including changes in the type, frequency, intensity, and seasonality of disturbances. However, our understanding of the frequency, extent, and causes of disturbance events remains incomplete. Disturbances such as fire, forest harvest, drought, wind, flooding, and insects and pathogens occur at different frequencies and severities, posing challenges to characterize and assess them under a single framework. We used the Continuous Change Detection and Classification (CCDC) algorithm on all available Landsat observations from 1984 to 2014 to detect land cover and land condition change. We mapped the following causes of disturbances annually across the study domain of NASA's Arctic Boreal Vulnerability Experiment (ABoVE): fire, logging, and pest damage. Differences between Landsat Tasseled Cap (TC) values pre- and post-disturbance were used in a random forest classifier to map causal agents. For forested ecosystems, we mapped causal agents including fire, insect, and logging. In areas that were not forest before disturbance, only the fire class was mapped. The result shows that multidimensional spectral-temporal change information is useful for mapping the causes of disturbance in arctic and boreal biomes. We employed two rounds of post-processing and used the information obtained from the comparison between the map and reference data to improve the final map. The user's and producer's accuracies of an aggregated disturbance map were 94.6% (± 2.37%) and 89.3% (± 21.78%) (95% confidence intervals in parenthesis). When evaluating the causal agents, insect damage was found the most challenging to map and validate. We estimated that 10.8% of the ABoVE core domain was disturbed between 1987 and 2012, with a margin of error of 0.5% at the 95% confidence level. Rates of disturbance due to logging remained constant over time, while fires were more episodic, and insect damage was highest between 2005 and 2010. Overall, fires affected 8.8% of the study area, while logging was 1.4% and insect damage 0.6%. Our maps indicate that pest damage became a significant issue after 2000, but it was more severe for forest ecosystems in Western Canada than in Alaska.
•New methods using delta-TC metrics and CCDC to map causal agents of disturbance.•7.2% of the ABoVE core domain experienced disturbance between 1987 and 2012.•Pest damage caused 5.4% of the disturbance; fire was 81.8%; logging was 12.8%.•Improved final maps by learning from reference data stratified on a preliminary map.