Landsat-Based Monitoring of Landscape Dynamics in Arctic Permafrost Region

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Abstract

Ice-rich permafrost thaws as a result of Arctic warming, and the land surface collapses to form characteristic thermokarst landscapes. Thermokarst landscapes can bring instability to the permafrost layer, affecting regional geomorphology, hydrology, and ecology and may further lead to permafrost degradation and greenhouse gas emissions. Field observations in permafrost regions are often limited, while satellite imagery provides a valuable record of land surface dynamics. Currently, continuous monitoring of regional-scale thermokarst landscape dynamics and disturbances remains a challenging task. In this study, we combined the Theil-Sen estimator with the LandTrendr algorithm to create a process flow for monitoring thermokarst landscape dynamics in Arctic permafrost region on the Google Earth Engine platform. A robust linear trend analysis of the Landsat Tasseled Cap index time series based on the Theil-Sen estimator and Mann-Kendall test showed the overall trends in greenness, wetness, and brightness in northern Alaska over the past 20 years. Six types of disturbances that occur in thermokarst landscape were demonstrated and highlighted, including long-term processes (thermokarst lake expansion, shoreline retreat, and river erosion) and short-term events (thermokarst lake drainage, wildfires, and abrupt vegetation change). These disturbances are widespread throughout the Arctic permafrost region and represent hotspots of abrupt permafrost thaw in a warming context, which would destabilize fragile thermokarst landscapes rich in soil organic carbon and affect the ecological carbon balance. The cases we present provide a basis for understanding and quantifying specific disturbance analyses that will facilitate the integration of thermokarst processes into climate models.

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Chen, Y., Liu, A., & Cheng, X. (2022). Landsat-Based Monitoring of Landscape Dynamics in Arctic Permafrost Region. Journal of Remote Sensing (United States), 2022. https://doi.org/10.34133/2022/9765087

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