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Over the last 2 decades, the topic of earthquake-triggered landslides (EQTLs) has shown increasing relevance in the scientific community. This interest is confirmed by the numerous articles published in international, peer-reviewed journals. In this work we present a database containing a selection of articles published on this topic from 1984 to 2021. The articles were selected through a systematic search on the Clarivate™ Web of Science™ Core Collection online platform and were catalogued into a web-based GIS (web-GIS), which was specifically designed to show different types of information. After a general analysis of the database, for each article the following aspects were identified: the bibliometric information (e.g. author(s), title, publication year), the relevant topic and sub-topic category (or categories), and the earthquake(s) addressed. The analysis allowed us to infer general information and statistics on EQTLs (e.g. relevant methodological approaches over time and in relation to the scale of investigation, most studied events), which can be useful to obtain a spatial distribution of the articles and a general overview of the topic.

Ischia Island is a volcano-tectonic horst in the Phlegrean Volcanic District, Italy. We investigated rockfalls in Ischia using STONE, a three-dimensional model for simulating trajectories for given detachment locations of blocks. We propose methodological advances regarding the use of high-resolution LiDAR elevation data, the localization of possible detachments sources, and the inclusion of scenario-based seismic shaking as a trigger for rockfalls. We demonstrated that raw LiDAR data are useful to distinguish areas covered by tall vegetation, allowing realistic simulation of trajectories. We found that the areas most susceptibile to rockfalls are located along the N, N-W and S-W steep flanks of Mt. Epomeo, the S and S-W coast, and the sides of some steep exposed hydrographic channels located in the southern sector of the island. A novel procedure for dynamic activation of sources depending on ground shaking, in the event of an earthquake, helped inferring a seismically-triggered source map and the corresponding rockfall trajectories, for a scenario with 475 y return time. Thus, we obtained preliminary rockfall suceptibility in Ischia both in a “static” (trigger-independent) scenario, and in a seismic shaking triggering scenario. They must not be considered a risk map, but a starting point for a detailed field analysis.

Information on soil properties is crucial for soil preservation, the improvement of food security, and the provision of ecosystem services. In particular, for the African continent, spatially explicit information on soils and their ability to sustain these services is still scarce. To address data gaps, infrared spectroscopy has achieved great success as a cost-effective solution to quantify soil properties in recent decades. Here, we present a mid-infrared soil spectral library (SSL) for central Africa (CSSL) that can predict key soil properties, allowing for future soil estimates with a minimal need for expensive and time-consuming wet chemistry. Currently, our CSSL contains over 1800 soil samples from 10 distinct geoclimatic regions throughout the Congo Basin and along the Albertine Rift. For the analysis, we selected six regions from the CSSL, for which we built predictive models for total carbon (TC) and total nitrogen (TN) using an existing continental SSL (African Soil Information Service, AfSIS SSL; n=1902) that does not include central African soils. Using memory-based learning (MBL), we explored three different strategies at decreasing degrees of geographic extrapolation, using models built with (1) the AfSIS SSL only, (2) AfSIS SSL combined with the five remaining central African regions, and (3) a combination of AfSIS SSL, the remaining five regions, and selected samples from the target region (spiking). For this last strategy we introduce a method for spiking MBL models. We found that when using the AfSIS SSL only to predict the six central African regions, the root mean square error of the predictions (RMSEpred) was between 3.85–8.74 and 0.40–1.66 g kg−1 for TC and TN, respectively. The ratio of performance to the interquartile distance (RPIQpred) ranged between 0.96–3.95 for TC and 0.59–2.86 for TN. While the effect of the second strategy compared to the first strategy was mixed, the third strategy, spiking with samples from the target regions, could clearly reduce the RMSEpred to 3.19–7.32 g kg−1 for TC and 0.24–0.89 g kg−1 for TN. RPIQpred values were increased to ranges of 1.43–5.48 and 1.62–4.45 for TC and TN, respectively. In general, predicted TC and TN for soils of each of the six regions were accurate; the effect of spiking and avoiding geographical extrapolation was noticeably large. We conclude that our CSSL adds valuable soil diversity that can improve predictions for the Congo Basin region compared to using the continental AfSIS SSL alone; thus, analyses of other soils in central Africa will be able to profit from a more diverse spectral feature space. Given these promising results, the library comprises an important tool to facilitate economical soil analyses and predict soil properties in an understudied yet critical region of Africa. Our SSL is openly available for application and for enlargement with more spectral and reference data to further improve soil diagnostic accuracy and cost-effectiveness.

Stabilization of soil organic carbon (SOC) against microbial decomposition depends on several soil properties, including the soil weathering stage and the mineralogy of parent material. As such, tropical SOC stabilization mechanisms likely differ from those in temperate soils due to contrasting soil development. To better understand these mechanisms, we investigated SOC dynamics at three soil depths under pristine tropical African mountain forest along a geochemical gradient from mafic to felsic and a topographic gradient covering plateau, slope and valley positions. To do so, we conducted a series of soil C fractionation experiments in combination with an analysis of the geochemical composition of soil and a sequential extraction of pedogenic oxides. Relationships between our target and predicting variables were investigated using a combination of regression analyses and dimension reduction. Here, we show that reactive secondary mineral phases drive SOC properties and stabilization mechanisms together with, and sometimes more strongly than, other mechanisms such as aggregation or C stabilization by clay content. Key mineral stabilization mechanisms for SOC were strongly related to soil geochemistry, differing across the study regions. These findings were independent of topography in the absence of detectable erosion processes. Instead, fluvial dynamics and changes in soil moisture conditions had a secondary control on SOC dynamics in valley positions, leading to higher SOC stocks there than at the non-valley positions. At several sites, we also detected fossil organic carbon (FOC), which is characterized by high C/N ratios and depletion of N. FOC constitutes up to 52.0 ± 13.2 % of total SOC stock in the C-depleted subsoil. Interestingly, total SOC stocks for these soils did not exceed those of sites without FOC. Additionally, FOC decreased strongly towards more shallow soil depths, indicating decomposability of FOC by microbial communities under more fertile conditions. Regression models, considering depth intervals of 0–10, 30–40 and 60–70 cm, showed that variables affiliated with soil weathering, parent material geochemistry and soil fertility, together with soil depth, explained up to 75 % of the variability of SOC stocks and Δ14C. Furthermore, the same variables explain 44 % of the variability in the relative abundance of C associated with microaggregates vs. free-silt- and-clay-associated C fractions. However, geochemical variables gained or retained importance for explaining SOC target variables when controlling for soil depth. We conclude that despite long-lasting weathering, geochemical properties of soil parent material leave a footprint in tropical soils that affects SOC stocks and mineral-related C stabilization mechanisms. While identified stabilization mechanisms and controls are similar to less weathered soils in other climate zones, their relative importance is markedly different in the tropical soils investigated.

The African Tropics are hotspots of modern-day land use change and are, at the same time, of great relevance for the cycling of carbon (C) and nutrients between plants, soils, and the atmosphere. However, the consequences of land conversion on biogeochemical cycles are still largely unknown as they are not studied in a landscape context that defines the geomorphic, geochemical, and pedological framework in which biological processes take place. Thus, the response of tropical soils to disturbance by erosion and land conversion is one of the great uncertainties in assessing the carrying capacity of tropical landscapes to grow food for future generations and in predicting greenhouse gas fluxes from soils to the atmosphere and, hence, future earth system dynamics. Here we describe version 1.0 of an open-access database created as part of the project “Tropical soil organic carbon dynamics along erosional disturbance gradients in relation to variability in soil geochemistry and land use” (TropSOC). TropSOC v1.0 (Doetterl et al., 2021, https://doi.org/10.5880/fidgeo.2021.009) contains spatially and temporally explicit data on soil, vegetation, environmental properties, and land management collected from 136 pristine tropical forest and cropland plots between 2017 and 2020 as part of monitoring and sampling campaigns in the eastern Congo Basin and the East African Rift Valley system. The results of several laboratory experiments focusing on soil microbial activity, C cycling, and C stabilization in soils complement the dataset to deliver one of the first landscape-scale datasets to study the linkages and feedbacks between geology, geomorphology, and pedogenesis as controls on biogeochemical cycles in a variety of natural and managed systems in the African Tropics. The hierarchical and interdisciplinary structure of the TropSOC database allows linking of a wide range of parameters and observations on soil and vegetation dynamics along with other supporting information that may also be measured at one or more levels of the hierarchy. TropSOC's data mark a significant contribution to improve our understanding of the fate of biogeochemical cycles in dynamic and diverse tropical African (agro-)ecosystems. TropSOC v1.0 can be accessed through the Supplement provided as part of this paper or as a separate download via the websites of the Congo Biogeochemistry Observatory and GFZ Data Services where version updates to the database will be provided as the project develops.

The increasing availability of free-access satellite data represents a relevant opportunity for the analysis and assessment of natural hazards. The systematic acquisition of spaceborne imagery allows for monitoring areas prone to geohydrological disasters, providing relevant information for risk evaluation and management. In cases of major landslide events, for example, spaceborne radar data can provide an effective solution for the detection of slope failures, even in cases with persistent cloud cover. The information about the extension and location of the landslide-affected areas may support decision-making processes during emergency responses. In this paper, we present an automatic procedure based on Sentinel-1 Synthetic Aperture Radar (SAR) images, aimed at facilitating the detection of landslides over wide areas. Specifically, the procedure evaluates changes of radar backscattered signals associated with land cover modifications that may be also caused by mass movements. After a one-time calibration of some parameters, the processing chain is able to automatically execute the download and preprocessing of images, the detection of SAR amplitude changes, and the identification of areas potentially affected by landslides, which are then displayed in a georeferenced map. This map should help decision makers and emergency managers to organize field investigations. The process of automatization is implemented with specific scripts running on a GNU/Linux operating system and exploiting modules of open-source software. We tested the processing chain, in back analysis, on an area of about 3000 km2 in central Papua New Guinea that was struck by a severe seismic sequence in February–March 2018. In the area, we simulated a periodic survey of about 7 months, from 12 November 2017 to 6 June 2018, downloading 36 Sentinel-1 images and performing 17 change detection analyses automatically. The procedure resulted in statistical and graphical evidence of widespread land cover changes that occurred just after the most severe seismic events. Most of the detected changes can be interpreted as mass movements triggered by the seismic shaking.

The use of remotely piloted aircraft systems (RPASs) in geosciences is often aimed at the acquisition of an image sequence to produce digital models and orthophotographs of the topographic surface. The technology can be applied for rockfall hazard and risk assessment. To study rockfalls, an approach consists in the application of numerical models for the computation of rockfall trajectories. Data required for such simulations include digital terrain models, location of the instability source areas, and the mechanical properties of the terrain. In this article, we present an analysis of the earthquake-triggered rockfall that occurred along the SP18 in Villanova di Accumoli (Lazio, central Italy) during the seismic sequence that started on 24 August 2016. A survey with a multicopter was carried out to obtain a surface model of the terrain and identify and characterize the source areas and other instable blocks in areas not accessible in the field. The investigated area extends for 6500 m2 and was covered by 161 photographs that were used to obtain an orthophoto with a ground resolution of 2.5 cm and a digital surface model with a ground resolution of 20 cm × 20 cm, which was processed and fused with GNSS real-time kinematic data. To obtain a map of potential rockfall trajectories, we run the numerical model STONE, using as origin of the boulders both source areas mapped in the field and pixels with a slope angle above a selected threshold. Results showed that only the part of the road SP18 already affected by the rockfall was exposed to further rockfall impacts. In particular, it was observed that 29.2 % (i.e. 12 123) of the 41 500 simulated trajectories may potentially reach or cross this tract of the road. Based on these data, limited protection measures were suggested. The combined use of RPAS data, fused with ground GPS points, an accurate geomorphological survey, and terrain static and dynamic parameters from the literature allows fast, low-cost, and replicable rockfall numerical modelling useful for emergency response and adoption of proper protection measures.

In the paper we analyse a multi-date landslide inventory prepared for a mountainous area affected by several landslide types with different degrees of activity, we attempt to quantify the uncertainties associated to the mapping, we measure the evolution of morphological indicators and estimate landslide activity and temporal occurrence. The inventory, covering the period 1956–2010, is prepared for the middle section of the Ubaye valley (southern French Alps) based on the analysis of multi-source documents (geomorphological maps, historical reports of landslide events, field surveys, orthophotographs and SAR (synthetic aperture radar) satellite images). The uncertainties derived from the expert interpretation of different sources of information, the landslide morphological features and the affected land covers are taken into account in relation to the source documents. Morphological indicators are calculated to describe quantitatively the evolution of the landslides (length, area, relative elevation, runout distance). Frequency–area density functions are computed to estimate the changes in the landslide distributions and a Poisson model is used to estimate the probability of reactivation of the observed landslides and the occurrence of new failures. The proposed multi-date inventory and the associated statistics provide additional information to the event catalogue managed by the local policy makers.

For a 277 km2 study area in the Flemish Ardennes, Belgium, a landslide inventory and two landslide susceptibility zonations were combined to obtain an optimal landslide susceptibility assessment, in five classes. For the experiment, a regional landslide inventory, a 10 m × 10 m digital representation of topography, and lithological and soil hydrological information obtained from 1:50 000 scale maps, were exploited. In the study area, the regional inventory shows 192 landslides of the slide type, including 158 slope failures occurred before 1992 (model calibration set), and 34 failures occurred after 1992 (model validation set). The study area was partitioned in 2.78×106 grid cells and in 1927 topographic units. The latter are hydro-morphological units obtained by subdividing slope units based on terrain gradient. Independent models were prepared for the two terrain subdivisions using discriminant analysis. For grid cells, a single pixel was identified as representative of the landslide depletion area, and geo-environmental information for the pixel was obtained from the thematic maps. The landslide and geo-environmental information was used to model the propensity of the terrain to host landslide source areas. For topographic units, morphologic and hydrologic information and the proportion of lithologic and soil hydrological types in each unit, were used to evaluate landslide susceptibility, including the depletion and depositional areas. Uncertainty associated with the two susceptibility models was evaluated, and the model performance was tested using the independent landslide validation set. An heuristic procedure was adopted to combine the landslide inventory and the susceptibility zonations. The procedure makes optimal use of the available landslide and susceptibility information, minimizing the limitations inherent in the inventory and the susceptibility maps. For the established susceptibility classes, regulations to link terrain domains to appropriate land rules are proposed.

Since 1857 more than 600 rock falls, rock slides, debris slides, and debris flows have been documented in Yosemite National Park, with rock falls in Yosemite Valley representing the majority of the events. On 26 December 2003, a rock fall originating from west of Glacier Point sent approximately 200 m3 of rock debris down a series of joint-controlled ledges to the floor of Yosemite Valley. The debris impacted talus near the base of Staircase Falls, producing fragments of flying rock that struck occupied cabins in Curry Village. Several years later on 9 June 2007, and again on 26 July 2007, smaller rock falls originated from the same source area. The 26 December 2003 event coincided with a severe winter storm and was likely triggered by precipitation and/or frost wedging, but the 9 June and 26 July 2007 events lack recognizable triggering mechanisms. We investigated the geologic and hydrologic factors contributing to the Staircase Falls rock falls, including bedrock lithology, weathering, joint spacing and orientations, and hydrologic processes affecting slope stability. We improved upon previous geomorphic assessment of rock-fall hazards, based on a shadow angle approach, by using STONE, a three-dimensional rock-fall simulation computer program. STONE produced simulated rock-fall runout patterns similar to the mapped extent of the 2003 and 2007 events, allowing us to simulate potential future rock falls from the Staircase Falls detachment area. Observations of recent rock falls, mapping of rock debris, and simulations of rock fall runouts beneath the Staircase Falls detachment area suggest that rock-fall hazard zones extend farther downslope than the extent previously defined by mapped surface talus deposits.

A high resolution Digital Elevation Model with a ground resolution of 2 m×2 m (DEM2) was obtained for the Collazzone area, central Umbria, through weighted linear interpolation of elevation points acquired by Airborne Lidar Swath Mapping. Acquisition of the elevation data was performed on 3 May 2004, following a rainfall period that resulted in numerous landslides. A reconnaissance field survey conducted immediately after the rainfall period allowed mapping 70 landslides in the study area, for a total landslide area of 2.7×105 m2. Topographic derivative maps obtained from the DEM2 were used to update the reconnaissance landslide inventory map in 22 selected sub-areas. The revised inventory map shows 27% more landslides and 39% less total landslide area, corresponding to a smaller average landslide size. Discrepancies between the reconnaissance and the revised inventory maps were attributed to mapping errors and imprecision chiefly in the reconnaissance field inventory. Landslides identified exploiting the Lidar elevation data matched the local topography more accurately than the same landslides mapped using the existing topographic maps. Reasons for the difference include an incomplete or inaccurate view of the landslides in the field, an unfaithful representation of topography in the based maps, and the limited time available to map the landslides in the field. The high resolution DEM2 was compared to a coarser resolution (10 m×10 m) DEM10 to establish how well the two DEMs captured the topographic signature of landslides. Results indicate that the improved topographic information provided by DEM2 was significant in identifying recent rainfall-induced landslides, and was less significant in improving the representation of stable slopes.

The autumn of 2004 was particularly wet in Umbria, with cumulative rainfall in the period from October to December exceeding 600 mm. On 4–6 December and on 25–27 December 2004, two storms hit the Umbria Region producing numerous landslides, which were abundant near the town of Orvieto where they affected volcanic deposits and marine sediments. In this work, we document the type and abundance of the rainfall-induced landslides in the Orvieto area, in south-western Umbria, we study the rainfall conditions that triggered the landslides, including the timing of the slope failures, we determine the geotechnical properties of the failed volcanic materials, and we discuss the type and extent of damage produced by the landslides. We then use the recent event landslide information to test a geomorphological assessment of landslide hazards and risk prepared for the village of Sugano, in the Orvieto area. Based on the results of the test, we update the existing landslide hazards and risk scenario for extremely rapid landslides, mostly rock falls, and we introduce a new landslide scenario for rapid and very rapid landslides, including soil slides, debris flows and debris avalanches.

We present the results of the application of a recently proposed model to determine landslide hazard. The model predicts where landslides will occur, how frequently they will occur, and how large they will be in a given area. For the Collazzone area, in the central Italian Apennines, we prepared a multi-temporal inventory map through the interpretation of multiple sets of aerial photographs taken between 1941 and 1997 and field surveys conducted in the period between 1998 and 2004. We then partitioned the 79 square kilometres study area into 894 slope units, and obtained the probability of spatial occurrence of landslides by discriminant analysis of thematic variables, including morphology, lithology, structure and land use. For each slope unit, we computed the expected landslide recurrence by dividing the total number of landslide events inventoried in the terrain unit by the time span of the investigated period. Assuming landslide recurrence was constant, and adopting a Poisson probability model, we determined the exceedance probability of having one or more landslides in each slope unit, for different periods. We obtained the probability of landslide size, a proxy for landslide magnitude, by analysing the frequency-area statistics of landslides, obtained from the multi-temporal inventory map. Lastly, assuming independence, we determined landslide hazard for each slope unit as the joint probability of landslide size, of landslide temporal occurrence, and of landslide spatial occurrence.

Rock slides and rock falls are the most frequent types of slope movements in Yosemite National Park, California. In historical time (1857–2002) 392 rock falls and rock slides have been documented in the valley, and some of them have been mapped in detail. We present the results of an attempt to assess rock fall hazards in the Yosemite Valley. Spatial and temporal aspects of rock falls hazard are considered. A detailed inventory of slope movements covering the 145-year period from 1857 to 2002 is used to determine the frequency-volume statistics of rock falls and to estimate the annual frequency of rock falls, providing the temporal component of rock fall hazard. The extent of the areas potentially subject to rock fall hazards in the Yosemite Valley were obtained using STONE, a physically-based rock fall simulation computer program. The software computes 3-dimensional rock fall trajectories starting from a digital elevation model (DEM), the location of rock fall release points, and maps of the dynamic rolling friction coefficient and of the coefficients of normal and tangential energy restitution. For each DEM cell the software calculates the number of rock falls passing through the cell, the maximum rock fall velocity and the maximum flying height. For the Yosemite Valley, a DEM with a ground resolution of 10 × 10 m was prepared using topographic contour lines from the U.S. Geological Survey 1:24 000-scale maps. Rock fall release points were identified as DEM cells having a slope steeper than 60°, an assumption based on the location of historical rock falls. Maps of the normal and tangential energy restitution coefficients and of the rolling friction coefficient were produced from a surficial geologic map. The availability of historical rock falls mapped in detail allowed us to check the computer program performance and to calibrate the model parameters. Visual and statistical comparison of the model results with the mapped rock falls confirmed the accuracy of the model. The model results are compared with a previous map of rockfall talus and with a geomorphic assessment of rock fall hazard based on potential energy referred to as a shadow angle approach, recently completed for the Yosemite Valley. The model results are then used to identify the roads and trails more subject to rock fall hazard. Of the 166.5 km of roads and trails in the Yosemite Valley 31.2% were found to be potentially subject to rock fall hazard, of which 14% are subject to very high hazard.

The Umbria Region of Central Italy has a long history of mass movements. Landslides range from fast moving rock falls and debris flows, most abundant in mountain areas, to slow moving complex failures extending up to several hectares in the hilly part of the Region. Despite landslides occurring every year in Umbria, their impact remains largely unknown. We present an estimate of the impact of slope failures in the Umbria region based on the analysis of a catalogue of historical information on landslide events, a recent and detailed regional landslide inventory map, and three event inventories prepared after major landslide triggering events. Emphasis is given to the impact of landslides on the population, the transportation network, and the built-up areas. Analysis of the available historical information reveals that 1488 landslide events occurred at 1292 sites in Umbria between 1917 and 2001. In the same period 16 people died or were missing and 31 people were injured by slope movements. Roads and railways were damaged by slope failures at 661 sites, and 281 built-up areas suffered landslide damage. Three event inventories showing landslides triggered by high intensity rainfall events in the period 1937–1941, rapid snow melting in January 1997, and earthquakes in September–October 1997, indicate the type, abundance and distribution of damage to the population, the built-up areas and the transportation network caused by typical landslide-triggering events. Analysis of a geomorphological landslide inventory map reveals that in some of the municipalities in the region total landslide area exceeds 25%. Of the more than 45 700 landslide areas shown in the geomorphological inventory map, 4115 intersect a road or railway, and 6119 intersect a built-up area. In these areas slope failures can be expected during future landslide triggering events.

Identification and mapping of landslide deposits are an intrinsically difficult and subjective operation that requires a great effort to minimise the inherent uncertainty. For the Staffora Basin, which extends for almost 300 km2 in the northern Apennines, three landslide inventory maps were independently produced by three groups of geomorphologists. In comparing each map with the others, large positional discrepancies arise (in the range of 55–65%). When all three maps are overlain, the locational mismatch of landslide deposit polygons increases to over 80%. To assess the impact of these errors on predictive models of landslide hazard, for the study area discriminant models were built up from the same set of geological-geomorphological factors as predictors, and the occurrence of landslide deposits within each terrain-unit, derived from each inventory map, as dependent variable. The comparison of these models demonstrates that statistical modelling greatly minimises the impact of input data errors which remain, however, a major limitation on the reliability of landslide hazard maps.

We present a geomorphological method to evaluate landslide hazard and risk. The method is based on the recognition of existing and past landslides, on the scrutiny of the local geological and morphological setting, and on the study of site-specific and historical information on past landslide events. For each study area a multi-temporal landslide inventory map has been prepared through the interpretation of various sets of stereoscopic aerial photographs taken over the period 1941–1999, field mapping carried out in the years 2000 and 2001, and the critical review of site-specific investigations completed to solve local instability problems. The multi-temporal landslide map portrays the distribution of the existing and past landslides and their observed changes over a period of about 60 years. Changes in the distribution and pattern of landslides allow one to infer the possible evolution of slopes, the most probable type of failures, and their expected frequency of occurrence and intensity. This information is used to evaluate landslide hazard, and to estimate the associated risk. The methodology is not straightforward and requires experienced geomorphologists, trained in the recognition and analysis of slope processes. Levels of landslide hazard and risk are expressed using an index that conveys, in a simple and compact format, information on the landslide frequency, the landslide intensity, and the likely damage caused by the expected failure. The methodology was tested in 79 towns, villages, and individual dwellings in the Umbria Region of central Italy.

No abstract available.