Remote Mapping of Earthquake-Triggered Ground Failure in a Subarctic Region: Case Study of the November 2018 Anchorage, Alaska M 7.1 Earthquake

Abstract:

Ground failure inventories, which document the location and extent of failures triggered by an earthquake, are important datasets because they inform ground failure hazard and susceptibility models. Inventories can be created using field observations, but this approach can be challenging if the affected landscape is large or inaccessible after an earthquake. Remote sensing data can be used to help overcome these limitations. The effectiveness of remotely sensed data to create inventories is dependent on a variety of factors, such as the extent of coverage, timing, and quality of the imagery, as well as environmental factors such as atmospheric interference (e.g., clouds, water vapor) or snow and vegetation cover.

With these challenges in mind, we combine a diverse set of remote sensing data and techniques to create a ground failure inventory for the 2018 M 7.1 Anchorage, AK earthquake. This event presents us with the opportunity to test the performance and reliability of different remote sensing data products and techniques in an environment not typically hospitable to remotely sensed mapping. The earthquake occurred during late autumn at 61.2 N latitude, so the lack of sunlight, persistent cloud cover and recent snow cover that occurred after the earthquake made remote mapping challenging for this event. Fortunately, field observations were made by USGS scientists the week following the event. Using these observations as ground truth, we test a variety of image differencing techniques using lidar and optical data as well as a suite of radar techniques. We evaluate the effectiveness of the methods with widely used accuracy metrics to determine which are most successful at capturing ground failure features. This work will help inform mappers on which techniques will be most effective in subarctic environments.