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 m2 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.

Glacial Steady State Topography Controlled by the Coupled Influence of Tectonics and Climate.

Glaciers and rivers are the main agents of mountain erosion. While in the fluvial realm empirical relationships and their mathematical description, such as the stream power law, improved the understanding of fundamental controls on landscape evolution, simple constraints on glacial topography and governing scaling relations are widely lacking. We present a steady state solution for longitudinal profiles along eroding glaciers in a coupled system that includes tectonics and climate. We combined the shallow ice approximation and a glacial erosion rule to calculate ice surface and bed topography from prescribed glacier mass balance gradient and rock uplift rate. Our approach is inspired by the classic application of the stream power law for describing a fluvial steady state but with the striking difference that, in the glacial realm, glacier mass balance is added as an altitude-dependent variable. From our analyses we find that ice surface slope and glacial relief scale with uplift rate with scaling exponents indicating that glacial relief is less sensitive to uplift rate than relief in most fluvial landscapes. Basic scaling relations controlled by either basal sliding or internal deformation follow a power law with the exponent depending on the exponents for the glacial erosion rule and Glen's flow law. In a mixed scenario of sliding and deformation, complicated scaling relations with variable exponents emerge. Furthermore, a cutoff in glacier mass balance or cold ice in high elevations can lead to substantially larger scaling exponents which may provide an explanation for high relief in high latitudes.

Tectonic control on the persistence of glacially sculpted topography.

One of the most fundamental insights for understanding how landscapes evolve is based on determining the extent to which topography was shaped by glaciers or by rivers. More than 10(4) years after the last major glaciation the topography of mountain ranges worldwide remains dominated by characteristic glacial landforms such as U-shaped valleys, but an understanding of the persistence of such landforms is lacking. Here we use digital topographic data to analyse valley shapes at sites worldwide to demonstrate that the persistence of U-shaped valleys is controlled by the erosional response to tectonic forcing. Our findings indicate that glacial topography in Earth's most rapidly uplifting mountain ranges is rapidly replaced by fluvial topography and hence valley forms do not reflect the cumulative action of multiple glacial periods, implying that the classic physiographic signature of glaciated landscapes is best expressed in, and indeed limited by, the extent of relatively low-uplift terrain.

Glaciated valleys in Europe and western Asia.

In recent years, remote sensing, morphometric analysis, and other computational concepts and tools have invigorated the field of geomorphological mapping. Automated interpretation of digital terrain data based on impartial rules holds substantial promise for large dataset processing and objective landscape classification. However, the geomorphological realm presents tremendous complexity and challenges in the translation of qualitative descriptions into geomorphometric semantics. Here, the simple, conventional distinction of V-shaped fluvial and U-shaped glacial valleys was analyzed quantitatively using multi-scale curvature and a novel morphometric variable termed Difference of Minimum Curvature (DMC). We used this automated terrain analysis approach to produce a raster map at a scale of 1:6,000,000 showing the distribution of glaciated valleys across Europe and western Asia. The data set has a cell size of 3 arc seconds and consists of more than 40 billion grid cells. Glaciated U-shaped valleys commonly associated with erosion by warm-based glaciers are abundant in the alpine regions of mid Europe and western Asia but also occur at the margins of mountain ice sheets in Scandinavia. The high-level correspondence with field mapping and the fully transferable semantics validate this approach for automated analysis of yet unexplored terrain around the globe and qualify for potential applications on other planetary bodies like Mars.

Multi-scale curvature for automated identification of glaciated mountain landscapes.

Erosion by glacial and fluvial processes shapes mountain landscapes in a long-recognized and characteristic way. Upland valleys incised by fluvial processes typically have a V-shaped cross-section with uniform and moderately steep slopes, whereas glacial valleys tend to have a U-shaped profile with a changing slope gradient. We present a novel regional approach to automatically differentiate between fluvial and glacial mountain landscapes based on the relation of multi-scale curvature and drainage area. Sample catchments are delineated and multiple moving window sizes are used to calculate per-cell curvature over a variety of scales ranging from the vicinity of the flow path at the valley bottom to catchment sections fully including valley sides. Single-scale curvature can take similar values for glaciated and non-glaciated catchments but a comparison of multi-scale curvature leads to different results according to the typical cross-sectional shapes. To adapt these differences for automated classification of mountain landscapes into areas with V- and U-shaped valleys, curvature values are correlated with drainage area and a new and simple morphometric parameter, the Difference of Minimum Curvature (DMC), is developed. At three study sites in the western United States the DMC thresholds determined from catchment analysis are used to automatically identify 5 × 5 km quadrats of glaciated and non-glaciated landscapes and the distinctions are validated by field-based geological and geomorphological maps. Our results demonstrate that DMC is a good predictor of glacial imprint, allowing automated delineation of glacially and fluvially incised mountain landscapes.