TY - GEN A1 - Marc, Odin A1 - Meunier, Patrick A1 - Hovius, Niels T1 - Prediction of the area affected by earthquake-induced landsliding based on seismological parameters T2 - Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe N2 - We present an analytical, seismologically consistent expression for the surface area of the region within which most landslides triggered by an earthquake are located (landslide distribution area). This expression is based on scaling laws relating seismic moment, source depth, and focal mechanism with ground shaking and fault rupture length and assumes a globally constant threshold of acceleration for onset of systematic mass wasting. The seismological assumptions are identical to those recently used to propose a seismologically consistent expression for the total volume and area of landslides triggered by an earthquake. To test the accuracy of the model we gathered geophysical information and estimates of the landslide distribution area for 83 earthquakes. To reduce uncertainties and inconsistencies in the estimation of the landslide distribution area, we propose an objective definition based on the shortest distance from the seismic wave emission line containing 95% of the total landslide area. Without any empirical calibration the model explains 56% of the variance in our dataset, and predicts 35 to 49 out of 83 cases within a factor of 2, depending on how we account for uncertainties on the seismic source depth. For most cases with comprehensive landslide inventories we show that our prediction compares well with the smallest region around the fault containing 95% of the total landslide area. Aspects ignored by the model that could explain the residuals include local variations of the threshold of acceleration and processes modulating the surface ground shaking, such as the distribution of seismic energy release on the fault plane, the dynamic stress drop, and rupture directivity. Nevertheless, its simplicity and first-order accuracy suggest that the model can yield plausible and useful estimates of the landslide distribution area in near-real time, with earthquake parameters issued by standard detection routines. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 557 KW - 2008 Wenchuan earthquake KW - main Himalayan thrust KW - 2010 Haiti earthquake KW - strong ground motion KW - spatial-distribution KW - rupture process KW - 1994 Northridge KW - complex rupture KW - 1988 Saguenay KW - denali fault Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-418285 SN - 1866-8372 IS - 557 ER - TY - GEN A1 - Marc, Odin A1 - Hovius, Niels T1 - Amalgamation in landslide maps BT - effects and automatic detection T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Inventories of individually delineated landslides are a key to understanding landslide physics and mitigating their impact. They permit assessment of area–frequency distributions and landslide volumes, and testing of statistical correlations between landslides and physical parameters such as topographic gradient or seismic strong motion. Amalgamation, i.e. the mapping of several adjacent landslides as a single polygon, can lead to potentially severe distortion of the statistics of these inventories. This problem can be especially severe in data sets produced by automated mapping. We present five inventories of earthquake-induced landslides mapped with different materials and techniques and affected by varying degrees of amalgamation. Errors on the total landslide volume and power-law exponent of the area–frequency distribution, resulting from amalgamation, may be up to 200 and 50%, respectively. We present an algorithm based on image and digital elevation model (DEM) analysis, for automatic identification of amalgamated polygons. On a set of about 2000 polygons larger than 1000 m2, tracing landslides triggered by the 1994 Northridge earthquake, the algorithm performs well, with only 2.7–3.6% incorrectly amalgamated landslides missed and 3.9–4.8% correct polygons incorrectly identified as amalgams. This algorithm can be used broadly to check landslide inventories and allow faster correction by automating the identification of amalgamation. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 485 KW - 2008 Wenchuan earthquake KW - size distributions KW - mountain belt KW - sediment KW - erosion KW - Taiwan KW - model Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-408075 SN - 1866-8372 IS - 485 ER -