In the database, the information defined for each article is the following: publication year (B1), author(s) (B2), article title (B3), and journal name (B4). The first article of our search was published in April 1984 (Keefer, 1984), and only 20 articles had been published on the topic until 1999 (Fig. 1). An increasing trend of the number of published articles can be noted in the following years, particularly from the late 2000s, with a peak in 2019 and 2020 (99 and 100 articles, respectively).

The 810 identified papers were published in 160 different peer-reviewed journals. The Geological Society of America Bulletin has published the lowest number of articles but for the longest period, considering that the first article and last article were published in 1984 and 2020, respectively (Fig. 2). Engineering Geology, Landslides, and Geomorphology have published the largest number of articles (i.e. 233, which represents 28.8 % of the total), covering a period from the mid-1990s–early 2000s until February 2021. Natural Hazards, Journal of Mountain Science, and Bulletin of the Engineering Geology and the Environment have published 105 papers (13.0 % of the total), while Natural Hazards and Earth System Sciences, Bulletin of the Seismological Society of America, Environmental Earth Sciences, Soil Dynamics and Earthquake Engineering, and Geosciences have published 118 papers (14.6 % of the total). It is worth noting that Geosciences has published the largest annual number of papers with 14 articles in a little more than 3 years (2018–February 2021).

Overall, 56.4 % of the articles in the literature database were published in the above-mentioned 11 journals, whose scopes include the analysis of natural hazards, geological and/or geotechnical engineering, and geomorphology. Among these journals, only two (Bulletin of the Seismological Society of America and Soil Dynamics and Earthquake Engineering) specifically deal with seismology and earthquake engineering.

The analysis of the database revealed that the average number of authors for each paper varied over the years. Excluding the first article by Keefer (1984), the papers published before 2000 were written, on average, by two to three authors. In more recent years, the number increased to four to five authors, which suggests a need for different expertise to perform the wide range of research activities related to EQTLs.

The articles collected in the database were classified into four categories considering the following main topics:

regional landslide analysis – articles focusing on the analysis of EQTLs over large areas;

The 810 identified papers describe ground effects related to 136 earthquakes. For each earthquake we collected a set of data using the ANSS Comprehensive Earthquake Catalog (ComCat), implemented by USGS (http://earthquake.usgs.gov/earthquakes/search/, last access: 1 October 2022) as the main source of information. In the catalogue, the available information depends on the date of occurrence. For earthquakes that occurred before 1900 (18 events), it was possible to attribute only a broad localization of the epicentre, an estimation of the date of occurrence, and the macroseismic intensity, which allows us to quantify the shaking level from observations of the effects on buildings, environment, and people (Masi et al., 2020). For earthquakes that occurred after 1900, it was instead possible to obtain more detailed information and it was possible to associate with each seismic event the data listed in Table 1: earthquake ID (D1), the name (D2), the time of occurrence (D3) in the format yy-mm-dd-hh:mm-ss UTC (coordinated universal time), and the country of occurrence (D4). A distinction was made between single and multiple events (D5): an earthquake was considered multiple when the seismicity near the main shock was characterized by at least 10 events with Mw (moment magnitude) ≥ 5. In the database we have also indicated the focal mechanism (D6). Specifically, the main deformation style of the earthquake-generating fault was defined using the Kaverina-type double-couple (DC) classification diagram (Kaverina et al., 1996), which considers seven different fault mechanisms: normal, normal–strike-slip, reverse, reverse–strike-slip, strike-slip, strike-slip–normal, and strike-slip–reverse. From the Global Centroid Moment Tensor Catalogue (GCMTC) (https://www.globalcmt.org/, last access: 1 October 2022), we retrieved the moment tensor solution (D7) for 97 out of 136 investigated earthquakes. We used the moment tensor solution as input for the FMC software (Álvarez-Gómez, 2019), which allows us to automatically generate a Kaverina-type DC classification diagram. In the cases where the moment tensor solution was missing, we defined the focal mechanism from the specific literature if available (D8). The different types of magnitude, i.e. ML – Richter local magnitude (D9), Ms – Richter surface-wave magnitude (D10), Mw – moment magnitude (D11), and the Mercalli–Cancani–Sieberg (MCS) intensity scale (D12), were also added into the database, together with the epicentre coordinates (latitude – D13 and longitude – D14) and the hypocentre depth (D15). For each record, we specified the source of information (D16). As mentioned above, most of the information is derived from the ANSS catalogue, but for several historical earthquakes, we used the National Centers for Environmental Information World Data System (NCEI WDS) Global significant Earthquake Database (https://www.ngdc.noaa.gov/hazel/view/hazards/earthquake/search, last access: 1 October 2022), which includes over 5700 earthquakes from 2150 BCE to the present.

The two most numerous sub-categories in the regional landslide analysis category (Fig. 3b) include articles which discuss “regional susceptibility/hazard assessment” (RSHA) analyses and “regional mapping” (RM) activities (47.0 % and 43.8 %, respectively). The third sub-category (“regional landslide descriptive statistics” – RLDS) presents statistical descriptions of EQTLs data and contains about a quarter of the articles (25.2 %). Two further sub-categories discuss “regional landslide comparison” (RLC) and “regional risk modelling” (RRM) and contain only few articles (11.9 % and 5.7 %, respectively).

In the sub-category RSHA (205 articles), many of the articles use and describe modified versions of the Newmark (1965) model (e.g. Jin et al., 2019) or statistical methods such as logistic regression (e.g. Polykretis et al., 2019), artificial neural networks (e.g. Tian et al., 2019), or fuzzy logic (e.g. Razifard et al., 2019). In the set of articles that introduce modified versions of the Newmark model, the EQTL scenario related to a specific seismic event usually implies the exceedance of pre-established co-seismic displacement thresholds (Romeo, 2000), while in the group of statistical models, the outcome generally consists in susceptibility maps resulting from the weighting of different environmental factors (e.g. slope angle, geology, vegetation cover, ground shaking intensity). In both cases the analysis of the EQTL phenomenon concerns almost exclusively the triggering stage, while propagation and deposition processes are seldom examined (e.g. Guo et al., 2014). In addition, no specific methodological variations are presented with respect to the investigated landslide type (e.g. rockfall, earthflows).

The high number of papers included in the RM sub-category (191 articles) highlights the importance of landslide inventories for analyses over large areas. In this respect, it is important to point out the presence of different online catalogues which report information on EQTLs for recent and historical earthquakes. At a global scale, it is worth mentioning the Open Repository of Earthquake-Triggered Ground-Failure Inventories (Tanyas et al., 2017), which reports EQTLs and liquefaction effect data for 363 earthquakes, or the Earthquake Environmental Effects Catalogue (Guerrieri et al., 2015), which collects information about environmental effects triggered by specific seismic events, whose intensity is expressed according to the ESI (Environmental Seismic Intensity) scale (Michetti et al., 2007).

Of the 191 RM articles, 81 can also be classified within the third sub-category RLDS, since they include not only a description of one or more EQTL inventories but also a statistical analysis of the features of the mapped landslides (e.g. Roback et al., 2018). Conversely, 66 other RM articles are exclusively focused on mapping procedures, which are performed with different methods and techniques such as field investigation (e.g. Martino et al., 2017), analysis of aerial imagery (e.g. Saito et al., 2018), and satellite data (e.g. Hu et al., 2019).

As regards the RLC and RRM sub-categories, the relatively low number of articles (52 and 25, respectively) suggests the high specificity of the themes. In the first case, the comparison between landslide inventories can be performed for evaluating potential differences among earthquakes occurring in the same area (e.g. Jibson et al., 2020) or for inferring general rules (Tanyaş and Lombardo, 2020) and/or correlations, e.g. magnitude vs. affected area (e.g. Marc et al., 2017) or ground motion vs. landslide size (e.g. Jibson and Tanyaş, 2020). In the case of RRM articles, the analyses are focused on specific anthropic elements such as buildings, roads, and railways (e.g. Vega and Hidalgo, 2016) or can be framed within a wider risk assessment (e.g. Martino et al., 2020).

The largest number of articles (153 out of 220) within the single-landslide analysis category (Fig. 3c) is included in the “single-failure modelling” (SFMD) group. These articles thoroughly investigate the triggering (e.g. Zhang et al., 2018) and/or the propagation process (e.g. Li et al., 2017) of single-landslide events induced by specific seismic inputs. Although different types of approaches have been proposed by the authors, e.g. laboratory experimental testing (e.g. Pu et al., 2020), numerical modelling still represents the most widely used technique. Over the years, numerous types of increasingly sophisticated models have been developed (Jibson, 2011), which have allowed the simulation of complex physical processes related to EQTLs, for example progressive slope failure induced by strain-softening behaviour (e.g. Islam et al., 2019), dynamic fragmentation (e.g. Zhao and Crosta, 2018), and pore-water pressure variation on the sliding surface (Huang et al., 2019).

The SFMD sub-category also comprises 39 out of 68 articles included in the second sub-category (“single-failure geotechnical characterization” – SFGTC). In fact, numerical modelling often requires a detailed definition of the geotechnical parameters of the landslide body, which can be measured directly in the field (e.g. Gratchev and Towhata, 2010) or estimated through laboratory tests and parametric analyses (e.g. Dang et al., 2016). It is important to specify that, in many cases, the authors defined the input parameters of the numerical model simply based on literature values referring to the same or a similar landslide event (e.g. Nian et al., 2020).

Similarly, as described for regional scale, “single-failure mapping” (SFMP) sub-category includes all those articles dealing with mapping of a single-landslide body (e.g. Bozzano et al., 2008). Within this sub-category it is also possible to find almost all the articles belonging to the single-failure geophysical characterization (SFGPC). This point suggests how geophysical investigations are often associated with the detailed reconstruction of the geometry of the landslide (e.g. Havenith et al., 2002).

As regards “single-landslide comparison” (SLC) and “single-failure impact/risk modelling” (SFIRM), we identified a relatively low number of articles (12 and 11, respectively), as in the case of regional-scale analyses. In the first instance, the comparison concerns landslides that occurred during the same earthquake (e.g. Nakamura et al., 2014) or in response to other events that occurred in different regions (e.g. Aydan, 2016). In SFIRM articles, the effects of an EQTL on human activities can be estimated after a specific event (ex post assessment, e.g. Cui et al., 2012) or a priori through the reconstruction of specific single-landslide risk scenarios (e.g. Mousavi et al., 2011).

As mentioned above, the category “not applicable” contains articles which address and discuss themes only partially related to EQTLs. Considering the not negligible number of articles (158), we performed their analysis and evaluation. On the contrary, we decided to disregard the “other” category, since the low number of articles (28) did not allow us to infer general aspects and significant commonalities.

The examination of the articles classified as not applicable led us to identify different sub-categories (Fig. 3d). The most numerous (“historical/Holocene landslides” – HHL) contains 53 articles (33.5 %) dealing with landslides that occurred in historical times (i.e. before 1900) and, more generally, during the Holocene. In the case of historical failures, only generic information about the triggering earthquake is available, while in the second one (landslides that occurred during the Holocene), it is often difficult to recognize with certainty the earthquake as a triggering factor. In these articles, the authors often use terms that refer to the possible nature of the landslide trigger, such as “was probably triggered” (Pérez-López et al., 2019) or “most likely triggered” (Lv et al., 2014). In this group, several authors also describe dating techniques, such as dendrochronological (e.g. Struble et al., 2020), lichenometric (e.g. Pérez-López et al., 2019), and isotopic analyses (e.g. Kojima et al., 2014). For landslide events that occurred in historical times, archival records often represent the main source of information (Koukouvelas et al., 2020). Back-analysis of such events was also used to assess the intensity and the location of historical earthquakes as described, for instance, by Rodríguez-Peces et al. (2011) for the 1755 Lisbon (Portugal) and 1884 Arenas del Rey (Spain) earthquakes.

Beyond the historical landslides, we also decided to include in the not applicable category all those articles dealing with landslides related to the geological hazard chain potentially resulting after an earthquake (Fan et al., 2019). In this respect, we identified three sub-categories:

water environment landslides (WEL) – this sub-category comprises 47 articles (29.7 %) specifically focused on the secondary effects of EQTLs in water environments, such as landslide-induced tsunamis (e.g. Takagi et al., 2019) and floods related to river landslide dams (e.g. Fan et al., 2012). In the case of historical earthquakes, EQTLs in water environments are generally used as evidence for confirming past tsunamis (e.g. Kitamura et al., 2020) and river damming events (e.g. Ehteshami-Moinabadi and Nasiri, 2019) or, more generally, the occurrence of one or multiple earthquakes in a specific area (e.g. Goto et al., 2010).

The analysis of “vegetation and EQTLs” (VAE) is addressed by 15 articles (9.5 %) and represents another sub-topic. These articles are focused on the stabilizing effect of vegetation recovery at landslide sites after earthquake events (Yang et al., 2018) or, conversely, on vegetation change/alteration induced by EQTLs (e.g. Cheng et al., 2012).

Finally, 21 articles were classified as fully not applicable (NA), since the topic addressed is not related to EQTLs, such as the dynamic response of slopes based on in situ monitoring systems (Moore et al., 2011; Lenti et al., 2015) or the evaluation of the hydrological response of landslide bodies under seismic loading (Beyabanaki et al., 2016; O'Brien et al., 2016).