A method for regionally mapping gravitationally deformed and loosened slopes using helicopter-borne electromagnetic resistivity data

Abstract

Earthquake-induced deep-seated landslides are prone to occur at gravitationally deformed and loosened slopes. These slopes need to be identified for landslide susceptibility mapping and landslide risk assessment. Surface morphology is an effective factor for finding the slopes, but is not effective for estimating the degree and the area of loosening. Subsurface geophysical investigations are quite useful for determining subsurface geological structures in regions where loosening has occurred. In this study, a method was developed for regionally mapping gravitationally deformed and loosened slopes as earthquake-induced deep-seated landslide susceptible zones by differentiating from sound bedrocks in flexural toppled slopes. Using the helicopter-borne electromagnetic resistivity data, ''average ruggedness of resistivity'' was proposed as an index parameter for differentiating the loosened zones. The estimated loosened zones were compared with observed geomorphological features during field survey, and it is shown that ''average ruggedness of resistivity'' is a useful parameter for regional mapping of earthquake-induced deep-seated landslide susceptible slopes.

Validation of an Index for Susceptibility to Earthquake-Induced Landslides Derived from Helicopter-Borne Electromagnetic Resistivity and Digital Elevation Data

“…This study attempts to validate the "index of susceptibility for earthquake-induced landslides" (ISEL) by using HEM resistivity data acquired before the 2016 Kumamoto earthquake. These data were processed using the same method as in Nonomura et al [32] and used to calculate the ISEL using the same method as in Nonomura and Hasegawa [33].…”

“…At each frequency, approximately 10 data points were obtained for every 8 m along the flight lines. The HEM data were processed using the same method as in Nonomura et al [32] in order to obtain resistivity data. The resistivity pixel size was 10 m.…”

“…To estimate looseness from resistivity data, the influence of lithology on the resistivity distribution must be minimized. Nonomura et al [32] proposed that the distribution of relatively higher resistivity, calculated by applying the concept of the openness to resistivity data [52], could be used to determine the looseness of rock masses. The localized distribution of resistivity within a given radial distance in one direction is defined as the "ruggedness of resistivity."…”

“…These must be excluded in order to extract data specific to bedrock looseness. Nonomura et al [32] analyzed HEM resistivity data to differentiate loosened slopes from sound bedrock and identify deep-seated landslide susceptible zones. From this, Nonomura et al [32] developed a parameter for estimating looseness named "average ruggedness of resistivity."…”

“…Nonomura et al [32] analyzed HEM resistivity data to differentiate loosened slopes from sound bedrock and identify deep-seated landslide susceptible zones. From this, Nonomura et al [32] developed a parameter for estimating looseness named "average ruggedness of resistivity." Nonomura and Hasegawa [33] validated the parameter's effectiveness in estimating the looseness of rock masses and proposed an index for earthquake-induced landslide (ISEL) susceptibility at the Kanagi landslide where a catastrophic, deep-seated landslide was triggered by the 1707 Hoei earthquake (M 8.6) [34,35].…”