Detecting landslide-dammed lakes on Sentinel-2 imagery and monitoring their spatio-temporal evolution following the Kaikoura earthquake in New Zealand

Landslide-dammed lakes pose a risk for upriver and downriver communities and infrastructure. The 2016 Kaikoura earthquake affected the northeastern region of the South Island in New Zealand, triggering numerous landslides that dammed river courses leading to the formation of hundreds of dammed lakes. Detecting and monitoring landslide-dammed lakes is important for disaster management. Satellite remote sensing imagery is often complementary to field acquisitions to obtain an overview of large and remote areas and thus can be exploited to monitor landslide-dammed lakes. Yet, the strengths and limitations of freely available multi-temporal satellite imagery for landslide-dammed lake assessment remain largely unexplored. This study aimed at automatically mapping landslide-dammed lakes caused by the 2016 Kaikoura earthquake and monitoring their evolution using time series of Sentinel-2 imagery and the computing capabilities of the Google Earth Engine. Our approach combined dynamic thresholding, change detection, and connected component analysis. Landslide-dammed lakes larger than 300 m(2) and located on relatively flat terrain were detected with reasonable accuracy, while lakes located in steeply incised valleys were detected less frequently. Despite the challenging topographical and environmental characteristics of the study area, we were able to detect landslide-dammed lake candidates at a regional scale. Temporal monitoring of the evolution of the landslide-dammed lake area revealed four distinct patterns: 1) constant, 2) increasing, 3) decreasing, and 4) variable. Our approach contributes to the understanding of the utility and limitations of temporal and spatial monitoring of landslide-dammed lakes, their potential cascading hazards and their interactions.