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Chávez-García, F.J., Natarajan, T., Cárdenas-Soto, M. et al. Landslide characterization using active and passive seismic imaging techniques: a case study from Kerala, India. Nat Hazards (2020).

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Martín Cárdenas-Soto at National Autonomous University of Mexico
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Abstract and Figures

The unusually intense precipitations of the 2018 monsoon triggered numerous landslides in the Western Ghats region, southwest of India. Although the landslides caused no casualties, significant damage to property and infrastructure was observed. We present, as a case study, the results of active and passive seismic prospecting at two of those landslides with the goal of characterizing them, in a first application of shallow seismic exploration to landslides in the region. Our deployments included both sites perturbed by the landslides and unperturbed slopes adjacent to them with the purpose of identifying possible structural differences between slopes that underwent landsliding from slopes that were not affected. We analyze seismic sections obtained using the multi-channel analysis of surface waves technique and compare the results with seismic noise analyzed using seismic interferometry. We show that different analyses give similar results. The lateral variations observed in the shear-wave velocity distribution below the different profiles are well correlated with dominant frequency determined from seismic noise horizontal-to-vertical spectral ratios. Our measurements were taken after the landslides occurred. In hindsight, our results suggest that soil thickness played a major role in the triggering of landslides.
a Location of the studied area (indicated by the black square) on the western side of southern India, in the Periyar basin, Kerala state. The blue lines indicate lakes and rivers. The brown circles indicate landslides that occurred during the monsoon season in 2018. b Detailed topography of the area inside the black square in a. The blue lines indicate the course of the Muthirappuzhayar river (marked M.R.) and subsidiary streams. The white circles show the location of the two measurement sites, S1 and S2
a Location of the studied area (indicated by the black square) on the western side of southern India, in the Periyar basin, Kerala state. The blue lines indicate lakes and rivers. The brown circles indicate landslides that occurred during the monsoon season in 2018. b Detailed topography of the area inside the black square in a. The blue lines indicate the course of the Muthirappuzhayar river (marked M.R.) and subsidiary streams. The white circles show the location of the two measurement sites, S1 and S2
… 
Location of the two studied landslides. The area affected by landslides is approximately indicated by the dashed yellow lines. The soil cover moved following the slope, to the East in a and to the south in b. The dash-dotted lines indicate roads, while the dashed blue lines show the course of the Muthirappuzhayar river (marked M.R.) or subsidiary streams. The short red lines along the roads indicate the locations of the seismic lines. The white circles on each profile show the location of the standalone seismographs (K1 and K4). The white star shows the location of the first source location, with an offset of 14 m in each case. a Site S1, showing the two deployments, marked S1_1 and S1_2. b Site S2. The seismograph K4 was first installed at the eastern end of S2 profile (location K4_W1) and was moved later to a second position close to its middle point (location K4_W2)
Location of the two studied landslides. The area affected by landslides is approximately indicated by the dashed yellow lines. The soil cover moved following the slope, to the East in a and to the south in b. The dash-dotted lines indicate roads, while the dashed blue lines show the course of the Muthirappuzhayar river (marked M.R.) or subsidiary streams. The short red lines along the roads indicate the locations of the seismic lines. The white circles on each profile show the location of the standalone seismographs (K1 and K4). The white star shows the location of the first source location, with an offset of 14 m in each case. a Site S1, showing the two deployments, marked S1_1 and S1_2. b Site S2. The seismograph K4 was first installed at the eastern end of S2 profile (location K4_W1) and was moved later to a second position close to its middle point (location K4_W2)
… 
Comparison of active and virtual source seismic sections obtained for the geophone line at deployment S1_1. a Seismic section recorded from hammer hits on a metal plate at the location of the first geophone (0 m distance). b Virtual source seismic section obtained from the cross-correlation of seismic noise recorded at all geophones with that recorded at the first geophone. The different frequency content of the traces in each plot provides complementary and independent information
Comparison of active and virtual source seismic sections obtained for the geophone line at deployment S1_1. a Seismic section recorded from hammer hits on a metal plate at the location of the first geophone (0 m distance). b Virtual source seismic section obtained from the cross-correlation of seismic noise recorded at all geophones with that recorded at the first geophone. The different frequency content of the traces in each plot provides complementary and independent information
… 
Results for P-wave tomography for the three measured profiles. a Profile S1_1, on top of the landslide at site S1. b Profile S1_2, on undisturbed ground. c Profile S2, at the second site, where the western part of the profile is located on the landslide (distances smaller than 24 m) and the eastern part on undisturbed ground (distances larger than 24 m). In all three cases, − 14 m distance corresponds to the location of the first active source (located to the south of profile S1_1, to the north of profile S1_2, and to the west of profile S2) and 0 m to the location of the first geophone. The letters on top of each figure indicate the approximate direction of the profile. The x axis runs right to left for profile S1_2 as the first active source was located 14 m north of the first geophone
Results for P-wave tomography for the three measured profiles. a Profile S1_1, on top of the landslide at site S1. b Profile S1_2, on undisturbed ground. c Profile S2, at the second site, where the western part of the profile is located on the landslide (distances smaller than 24 m) and the eastern part on undisturbed ground (distances larger than 24 m). In all three cases, − 14 m distance corresponds to the location of the first active source (located to the south of profile S1_1, to the north of profile S1_2, and to the west of profile S2) and 0 m to the location of the first geophone. The letters on top of each figure indicate the approximate direction of the profile. The x axis runs right to left for profile S1_2 as the first active source was located 14 m north of the first geophone
… 
Shear-wave velocity structure determined at the three studied sites using the CMPCC MASW method. The letters on top of each figure indicate the approximate direction of the profile. The distance axis is similar to that shown in Fig. 4, where 0 m corresponds to the first geophone and − 14 m to the location of the first active source. a Profile S1_1. b Profile S1_2. c Profile S2
+4
Shear-wave velocity structure determined at the three studied sites using the CMPCC MASW method. The letters on top of each figure indicate the approximate direction of the profile. The distance axis is similar to that shown in Fig. 4, where 0 m corresponds to the first geophone and − 14 m to the location of the first active source. a Profile S1_1. b Profile S1_2. c Profile S2
… 
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Vol.:(0123456789)
Natural Hazards (2021) 105:1623–1642
https://doi.org/10.1007/s11069-020-04369-y
1 3
ORIGINAL PAPER
Landslide characterization using active andpassive seismic
imaging techniques: acase study fromKerala, India
FranciscoJ.Chávez‑García1· ThulasiramanNatarajan2· MartínCárdenas‑Soto3·
KusalaRajendran4
Received: 6 June 2020 / Accepted: 5 October 2020 / Published online: 15 October 2020
© Springer Nature B.V. 2020
Abstract
The unusually intense precipitations of the 2018 monsoon triggered numerous landslides
in the Western Ghats region, southwest of India. Although the landslides caused no casu-
alties, significant damage to property and infrastructure was observed. We present, as a
case study, the results of active and passive seismic prospecting at two of those landslides
with the goal of characterizing them, in a first application of shallow seismic exploration to
landslides in the region. Our deployments included both sites perturbed by the landslides
and unperturbed slopes adjacent to them with the purpose of identifying possible structural
differences between slopes that underwent landsliding from slopes that were not affected.
We analyze seismic sections obtained using the multi-channel analysis of surface waves
technique and compare the results with seismic noise analyzed using seismic interferom-
etry. We show that different analyses give similar results. The lateral variations observed
in the shear-wave velocity distribution below the different profiles are well correlated with
dominant frequency determined from seismic noise horizontal-to-vertical spectral ratios.
Our measurements were taken after the landslides occurred. In hindsight, our results sug-
gest that soil thickness played a major role in the triggering of landslides.
Keywords Near surface geophysics· MASW· Seismic interferometry· Seismic
tomography
* Francisco J. Chávez-García
paco@pumas.ii.unam.mx
1 Instituto de Ingeniería, Universidad Nacional Autónoma de México, Ciudad Universitaria,
04510Coyoacán,CDMX, Mexico
2 Geodynamics Unit, Jawaharlal Nehru Centre forAdvanced Scientific Research, Bangalore560064,
India
3 Facultad de Ingeniería, Universidad Nacional Autónoma de México, Ciudad Universitaria,
04510Coyoacán,CDMX, Mexico
4 Center forEarth Science, Indian Institute ofSciences, CV Raman Rd, Bengaluru,
Karnataka560012, India
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
... Multichannel Analysis of Surface Waves (MASW), Seismic Refraction Tomography (SRT), signal-station HVSR, Electrical Resistivity Tomography (ERT), and Ground Penetrating Radar (GPR) are the most common methods applied in landslide investigation. All these methods have been used mainly for defining dimensions, geometry [23], slip surface [24], groundwater table [12], recharge pathways [25], rock fragments [26], degree of compaction [27], and in some cases, the velocity of seismic waves within the landslide body [28]; these static properties are also related to the dynamic properties estimated by time-lapse seismic methods, therefore useful for susceptibility landslide analysis and hazard and risk management. ...
... The ANb methods such as HVSR, ambient noise spectral and polarization analysis, and Ambient Noise Interferometry (ANI) have been gaining popularity [28,29,35]; these techniques are used for landslide site characterization and dynamics, as well as their vulnerability to different triggering factors such as earthquakes and rainfalls. The dV/V and modal parameters out of these techniques are related to the LS geometry and its elastic properties (stiffness and density) [40]. ...
... All the above-mentioned methods for impulse response construction based on ambient noise interferometry have their own merits and demerits, and their applications are dependent on the quality of data and the study objectives. A detailed review of ANI has been provided by the other authors, e.g., [35,63,64]; this technique has also been used in LS tomography, where cross-correlation is used to obtain the dispersion properties of Rayleigh waves which are then inverted to obtain velocity structures of LS mass [28]. ...
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... However, normal faulting mechanism with strike-slip component appears to the north of Assiut till Beni Suef city, [3]. An integrated interpretation of ERT, SSR, and GPR surveys should be performed at the site of KV57 to successfully investigate the groundwater aquifer and water table elevation and assist hazard mitigation; these techniques are well described in details in some recent references like [4][5][6]. ...
... There are red, yellow, brown and lemonade stones. Plaster strips run parallel to the bed planes [6], as shown in Fig. 14. This represents the sudden association of the Abu Hadd member in the Isna rock formation with the stone unit 1 of the Thebes limestone formation. ...
... -h crit is the minimum height of the cubical specimen of pillar material such that an increase in the specimen dimension will produce no further reduction in strength. suggestion of acceptable safety factors > 1. 6. Such values may be adequate for the excavation stability, [27] and [28]. ...
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... A summary of the historical background and various applications in science and engineering tasks are described by Larose et al. (2015) and Schuster (2014). For example, in the case of landslides, Seismic Interferometry has been used to identify the extent of the elastic properties contrast between the soft materials and the bedrock (Renalier et al., 2010;Pilz et al., 2013;Harba et al., 2019;Chávez-García et al., 2021). Additionally, the coda of the EGFs has allowed monitoring to detect velocity changes before the potential mass motions (Mainsant et al., 2012;Del Gaudio et al., 2013;Breton et al., 2021). ...
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Full-text available
  • Jan 2019
From 1 June to 29 August 2018, Kerala, a state in southwestern India, recorded 36% excess rainfall than normal levels, leading to widespread floods and landslides events and resulting in 445 deaths. In this study, satellite-based data were used to map the flood inundation in the districts of Thrissur, Ernakulam, Alappuzha, Idukki and Kottayam. Specifically, flood delineation was enabled with Sentinel-1A radar data of 21 August 2018 and was compared with an average pre-flood, water-cover map based on Modified Normalized Difference Water Index (MNDWI) that was developed using a January and February 2018 Sentinel-2A dataset. A 90% increase in water cover was observed during the August 2018 flood event. Low lying areas in the coastal plains of Kuttanad and the Kole lands of Thrissur, had marked a rise of up to 5 and 10 m of water, respectively, during this deluge. These estimates are conservative as that the flood waters had started receding prior to the August 21 Sentinel-1A imagery.
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Geophysical Monitoring of Moisture‐Induced Landslides: A Review
Article
Full-text available
Geophysical monitoring of landslides can provide insights into spatial and temporal variations of subsurface properties associated with slope failure. Recent improvements in equipment, data analysis, and field operations have led to a significant increase in the use of such techniques in monitoring. Geophysical methods complement intrusive approaches, which sample only a very small proportion of the subsurface, and walk‐over or remotely sensed data, which principally provide information only at the ground surface. In particular, recent studies show that advances in geophysical instrumentation, data processing, modeling, and interpretation in the context of landslide monitoring are significantly improving the characterization of hillslope hydrology and soil and rock hydrology and strength and their dynamics over time. This review appraises the state of the art of geophysical monitoring, as applied to moisture‐induced landslides. Here we focus on technical and practical uses of time‐lapse methods in geophysics applied to monitoring moisture‐induced landslide. The case studies identified in this review show that several geophysical techniques are currently used in the monitoring of subsurface landslide processes. These geophysical contributions to monitoring and predicting the evolution of landslide processes are currently underrealized. Hence, the further integration of multiple‐parametric and geotechnically coupled geophysical monitoring systems has considerable potential. The complementary nature of certain methods to map the distribution of subsurface moisture and elastic moduli will greatly increase the predictive and monitoring capacity of early warning systems in moisture‐induced landslide settings.
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Site effects using methods based on lateral homogeneity and laterally heterogeneous media: An impossible marriage?
Article
Full-text available
Site effect studies are currently mostly based on seismic noise measurements, processed using methods like horizontal-to-vertical spectral ratios (HVSR) to estimate dominant frequencies and maximum amplifications, or methods based on cross-correlation between stations like spatial autocorrelation (SPAC) and seismic interferometry. However, HVSR and SPAC assume that the underlying medium has a 1D structure and that seismic noise consists mostly of surface Rayleigh waves. We present a detailed analysis of seismic noise records at two sites in Euroseistest (Mygdonian basin, northern Greece) where two normal faults have created lateral heterogeneity in the subsoil structure. Site GRA is located near fault F3, with a larger throw than fault F2, close to site FRM. Our results show the effects of these irregularities. Dominant frequency results for both sites become spatially incoherent close to the fault. In the case of site GRA, a range of wavelengths is missing in the recorded seismic noise field. These effects extend up to some fraction of the affected wavelengths in the case of fault F3. The effect of lateral variations on seismic noise measurements will be lost in gross spatial averaging of the results or simply the failure of HVSR or SPAC methods will be observed.
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Detection of lateral discontinuities via surface waves analysis: A case study at a derelict industrial site
Article
  • Mar 2019
  • J APPL GEOPHYS
We applied a multi-offset surface wave analysis (MOPA) to detect subsoil lateral heterogeneities at a dismissed industrial site along the coast of the city of Trieste (Italy). The site is heavily contaminated and is undergoing characterization in view of possible remediation and re-use. Sea/land interactions and massive anthropic interventions make the site particularly complex. The main lateral heterogeneities consist of an extended buried quay, which also divides continental and marine sediments. We used seismic surface waves to define this contact, while also using supporting data from boreholes and geo-electrical surveys. A multi-offset phase and attenuation analysis was conducted on a few seismic lines, and produced clear evidence concerning the sought heterogeneities. Field data interpretation was corroborated also by ancillary information, and by synthetic modeling, that produced seismograms consistent with the recorded ones. In summary, the case study demonstrates how MOPA can be applied in a straightforward manner to define heterogeneities even at a very small spatial scale, and in complex environments such as derelict industrial sites.
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AN INVESTIGATION OF A LANDSLIDE-PRONE AREA BY MASW AND RESISTIVITY SURVEYS
Conference Paper
  • Mar 2016
In May 2014, a heavy rainfall caused a severe damage to the catchment of River Sava in Serbia and Bosnia and Herzegovina (BiH). The number of landslides exceeded 2000 in Serbia and BiH. This prompted an urgent investigation of the areas which have potential of further landslide. A project of geophysical investigation of these areas were initiated by Association of Geoscientists and Environmentalists of Serbia (AGES), supported by Geoscientists without Borders (GwB) of Society of Exploration Geophysicists (SEG). Over twenty students from three countries and more than ten technical professionals from six countries participated in the project. MASW and resistivity surveys were carried out in the Vrazici area in BiH in June 2015. Two survey lines were surveyed totaling about 120 meters along a slope of grassland and orchard. The MASW survey showed a clear increase of S-wave velocity from 250 to 350m/s at about 3 to 5m below the ground surface. This depth roughly corresponds to the resistivity boundary at 80 ohm-m. It is interpreted the interface between soft soils and relatively competent rock. The depth profiles of these boundaries show that the soft soils is thicker toward the lower part of the slope. This landslide can be classified as Varnes's classification “earth slide or earth flow”.
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Shear wave velocity profile estimation by integrated analysis of active and passive seismic data from small aperture arrays
Article
  • Apr 2016
  • J APPL GEOPHYS
We present an integrated approach for deriving the 1D shear wave velocity (Vs) information at few tens to hundreds of meters down to the first strong impedance contrast in typical sedimentary environments. We use multiple small aperture seismic arrays in 1D and 2D configuration to record active and passive seismic surface wave data at two selected geotechnical sites in Germany (Horstwalde & Löbnitz). Standard methods for data processing include the Multichannel Analysis of Surface Wave (MASW) methods that exploit the high frequency content in the active data and the sliding window frequency–wavenumber (f–k) as well as the spatial autocorrelation (SPAC) methods that exploit the low frequency content in passive seismic data. Applied individually, each of the passive methods might be influenced by any source directivity in the noise wavefield. The advantages of active shot data (known source location) and passive microtremor (low frequency content) recording may be combined using a correlation based approach applied to the passive data in the so called Interferometric Multichannel Analysis of Surface Waves (IMASW).
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