Luigi Lombardo

• PhD
• Professor (Associate) at University of Twente

Wildfires are frequently occurring hazards worldwide which are moving higher in elevation and threatening mountain regions. Each year, they result in substantial economic losses, fatalities, and carbon emissions. In addition, the interplay of climate change, land use changes, and socioeconomic factors is expected to increase the frequency and inten...

Systematic morphometric studies of submarine potential geohazard elements such as mud volcanism are still limited in the scientific literature. To fill this gap and contribute to the global geohazard databases, we present a comprehensive inventory of submarine mud volcanoes (MVs) considering their spatial location and characteristics. The “Global i...

Strong earthquakes in mountain landscapes can trigger widespread slope failures, initiating chains of multiple hydro-geomorphic hazards. These impacts disrupting ongoing response operations may be amplified by extreme post-seismic precipitation delivered by atmospheric rivers (ARs). However, to our knowledge, cases of ARs following major earthquake...

Assessing landslide risk is a fundamental requirement to plan suitable prevention actions. To date, most risk studies focus on individual slopes or catchments. Whereas regional, national or continental scale assessments are hardly available because of methodological and/or data limitations. In this contribution, we present an overview of all requir...

Spatiotemporal patterns of earth surface deformation are influenced by a combination of static and dynamic environmental characteristics specific to any landscape of interest. Nowadays, these patterns can be captured for larger areas using Inter-ferometric Synthetic-Aperture Radar (InSAR) technologies and yet, their spatial prediction has been poor...

Landslides are a common global geohazard that lead to substantial loss of life and socio-economic damage annually. Landslides are becoming more common due to climate change and anthropogenic disturbance, threatening sustainable development in vulnerable areas. Previous studies on fatal landslides have focussed on inventory development; spatial and...

Global warming exacerbates the frequency of extreme precipitation events and inevitably increases the risk of hydrogeological disasters such as landslides. Understanding the impact of climatic drivers, particularly precipitation, of landslides and the resulting damages is crucial for effective risk management and mitigation strategies. However, few...

Scientific advancements often emerge from pivotal discoveries and technological breakthroughs, expanding the frontiers of exploration. In geoscience, natural hazard studies have predominantly focused on terrestrial environments, while submarine settings remain relatively unexplored due to the scarcity of high-resolution data, particularly in deep-s...

Hydro-Morphological Processes (HMP, any natural phenomenon contained within the spectrum defined between debris flows and flash floods) are most likely to occur in small catchments , especially buffer zones along or near rivers. Rivers transfer matter and energy between hydrographic units, thus potentially affecting the occurrence of HMPs in nearby...

The geospatial community usually makes use of GIS environments to handle databases and pre-process their information. Actual analyses, especially data-driven ones, are performed outside GIS platforms. This interrupts the flow of information and the processing chain in a number of I/O operations that inevitably slow down the overall analytical proto...

Arctic permafrost is undergoing rapid changes due to climate warming in high latitudes. Retrogressive thaw slumps (RTS) are one of the most abrupt and impactful thermal-denudation events that change Arctic landscapes and accelerate carbon feedbacks. Their spatial distribution remains poorly characterised due to time-intensive conventional mapping m...

Shallow landslides are geomorphic hazards in mountainous terrains across the globe. Their occurrence can be attributed to the interplay of static and dynamic landslide controls. In previous studies, data-driven approaches have been employed to model shallow landslides on a regional scale, focusing on analyzing the spatial aspects and time-varying c...

Topographic amplification is caused by the interaction between seismic waves and rough terrains. It increases shaking levels on hilltops and could lead stable slopes to the brink of failure. However, its contribution to coseismic landslide occurrence is yet to be quantified over landscapes shaken by strong earthquakes. Here, we examine how topograp...

Landslide susceptibility maps serve as the basis for hazard and risk assessment, as well as risk-informed land use planning at various spatial scales. Researchers create these maps aiming to fulfil a variety of purposes, including infrastructure planning and restrictive land use zoning. These applications require accurate and specific information t...

The current study sets out to explore yearly landslide susceptibility dynamics on slopes regularly affected by fires. To do so, two yearly inventories have been generated, one for the landslides and one for the wildfires, for an area of approximately 2 km 2 and for a period of 24 years. It is important to stress that space-time data-driven models e...

At the time of its development, GeoSure was created using expert knowledge based on a thorough understanding of the engineering geology of the rocks and soils of Great Britain. The ability to use a data-driven methodology to develop a national-scale landslide susceptibility was not possible due to the relatively small size of the landslide inventor...

Landslide susceptibility shows the spatial likelihood of landslide occurrence in a specific geographical area and is a relevant tool for mitigating the impact of landslides worldwide. As such, it is the subject of countless scientific studies. Many methods exist for generating a susceptibility map, mostly falling under the definition of statistical...

The most adopted definition of landslide hazard combines spatial information about landslide location (susceptibility), threat (intensity), and frequency (return period). Only the first two elements are usually considered and estimated when working over vast areas. Even then, separate models constitute the standard, with frequency being rarely inve...

The new era of distant education and communication prompted the scientific community to indulge more in technology and make a virtue of virtual platforms, entailing prerequisites for raising technology literacy and encouraging interdisciplinary research and cross-boundary means of education. Game engines have long been known as a platform specifica...

Cryospheric hazards - in this case, thaw slumps (TS) and thermo-erosion gullies (TEG) - are phenomena typical of permafrost-dominated landscapes. Open datasets informing about their spatial, temporal and size distributions in the Arctic are still uncommon, as opposed to the systematic availability of this information for geomorphic processes in mid...

Delineating spatiotemporal variations in landslide susceptibility patterns is crucial for landslide prevention and management. In this study, we present a space–time modeling approach to predict the annual landslide susceptibility of the main island of Taiwan from 2004 to 2018. Specifically, we use a Bayesian version of the binomial generalized add...

There is an urgent need for accurate and effective Landslide Early Warning Systems (LEWS). Most LEWS are currently based on temporally-aggregated measures of rainfall derived from either in-situ measurements or satellite-based rainfall estimates. Relying on a summary metric of precipitation may not capture the complexity of the rainfall signal and...

For decades, solutions to regional scale landslide prediction have mostly relied on data-driven models, by definition, disconnected from the physics of the failure mechanism. The success and spread of such tools came from the ability to exploit proxy variables rather than explicit geotechnical ones, as the latter are prohibitive to acquire over bro...

Reduction in shear strength (RSS) of hillslope materials due to earthquakes have been rarely discussed numerically in regional scale analyses. Despite the limited literature, an empirical relationship between peak ground acceleration (PGA) and RSS was proposed based on Newmark's permanent-deformation analysis coupled with static limit equilibrium a...

Mean annual temperatures in the Arctic and subarctic have increased in recent decades, increasing the number of permafrost hazards. Retrogressive thaw slumps (RTSs), triggered by the thawing of ground ice in permafrost soil, have become more common in the Arctic. Many studies report an increase in RTS activity on a local or regional scale. In this...

Landslide spatial prediction using data-driven models has predominantly concentrated on predicting where landslides may occur. Nevertheless, few researchers have turned to jointly modeling how large and when landslides will be for a given terrain unit. This study proposes a data-driven model capable of estimating how large landslides may be, for th...

Regional debris-flow hazard assessments provide consistent information on potential hazards over large areas, often with limited available data. Different approaches to regional debris-flow hazard assessment include heuristic, empirical, statistical, or physically-based techniques. The resulting product is often a debris-flow susceptibility map tha...

Until now, a full numerical description of the spatio-temporal dynamics of a landslide could be achieved only via physically based models. The part of the geoscientific community in developing data-driven models has instead focused on predicting where landslides may occur via susceptibility models. Moreover, they have estimate when landslides may o...

Landslides are a common global geohazard that lead to substantial loss of life and socio-economic damage. Landslides are becoming more common due to extreme weather events and the impacts of anthropogenic disturbance, and thus, they are threatening sustainable development in many vulnerable areas. Previous studies on fatal landslides have focused o...

There is an urgent need for accurate and effective Landslide Early Warning Systems (LEWS). Most LEWS are currently based on a single temporally-aggregated measure of rainfall derived from either in-situ measurements or satellite-based rainfall estimates. Relying on a summary metric of precipitation may not capture the complexity of the rainfall sig...

The weakening of hillslopes during strong earthquakes increases landsliding rates in post-seismic periods. However, very few studies have addressed the amount of coseismic reduction in shear strength of hillslope materials. This makes estimation of post-seismic landslide susceptibility challenging. Here we propose a method to quantify the maximum s...

Seismic waves can shake mountainous landscapes, triggering thousands of landslides. Regional-scale landslide models primarily rely on shaking intensity parameters obtained by simplifying ground motion time-series into peak scalar values. Such an approach neglects the contribution of ground motion phase and amplitude and their variations over space...

The geoscientific community primarily focuses on predicting where landslides are likely to occur through data-driven susceptibility models. Recently, few researchers have turned to statistical estimation of landslide plani-metric area within a given terrain unit and exploration of the spatiotemporal distribution of landslide occurrence. However, th...

At the time of its development, GeoSure was created using expert knowledge based on a thorough understanding of the engineering geology of the rocks and soils of Great Britian. The ability to use a data-driven methodology to develop a national scale landslide susceptibility was not possible due to the relatively small size of the landslide inventor...

Landslide event inventories are one of the most critical datasets to increase knowledge on landslide occurrences. However, they are rarely available in various regions, especially in countries of the Global South. This study aims to generate rainfall-induced landslide event inventories and define the rainfall thresholds responsible for landslide oc...

The most adopted definition of landslide hazard combines spatial information about landslide location (susceptibility), threat (intensity), and frequency (return period). Only the first two elements are usually considered and estimated when working over vast areas. Even then, separate models constitute the standard, with frequency being rarely inve...

Supplementary material associated with the publication "Space-time data-driven modeling of precipitation-induced shallow landslides in South Tyrol, Italy" (https://doi.org/10.1016/j.scitotenv.2023.169166). The dynamic model predictions from 15th July to 15th August 2016 are presented as the animated GIF file Passeier_GIF.gif, which can be found on...

Understanding the dynamics between public disaster assistance, disaster damages, and social vulnerability at county-level is crucial for designing effective disaster mitigation strategies. This study utilized the Local Bivariate Moran Index (LBMI) and geographically weighted regression (GWR) models to examine spatial patterns and relationships betw...

Mountainous landscapes affected by strong earthquakes typically exhibit higher landslide susceptibility in post-seismic periods compared to pre-seismic conditions. This concept is referred to as the earthquake legacy effect, which needs to be better understood to develop an accurate post-seismic landslide hazard assessment. The earthquake legacy ef...

Shallow landslides represent potentially damaging processes in mountain areas worldwide. These geomorphic processes are usually caused by an interplay of predisposing, preparatory, and triggering environmental factors. At regional scales, data-driven methods have been used to model shallow landslides by addressing the spatial and temporal component...

Landslides can occur in different periods under different predisposing factors that are changed over time or no longer exist. We aim to address how discarding this important rule or assuming conditions to be intact can be detrimental in fast-evolving regions as it can easily mislead susceptibility models. Instead, this research prompts researchers...

This work pinpoints a discernible paradox in Landslide Hazard Assessment for Situational Awareness (LHASA): 1) simplicity in avoiding the intrinsic uncertainties stored in each part cascade through the entire computational process and diminish the value of a more inclusive and integrated analysis, and 2) including enough accessible and achievable c...

In this work, we investigate a slow-moving, large landslide (~20 km2) in the Chitral district in Northern Pakistan, near several villages. The slow-moving landslide was reported more than four decades ago but has never been examined afterward. Interferometric Synthetic Aperture Radar (InSAR) analyses, using Sentinel-1 data that span a period of six...

Shallow landslides represent potentially damaging processes in mountain areas worldwide. These geomorphic processes are usually caused by a combination of predisposing, preparatory, and triggering environmental factors. At regional scales, data-driven methods have been used to model shallow landslides by addressing the spatial and temporal componen...

This study aims to derive and evaluate new empirical rainfall thresholds as the basis for landslide early warning in Progo Catchment, Indonesia, using high-resolution rainfall datasets. Although attempts have been made to determine such thresholds for regions in Indonesia, they used coarse-resolution data and fixed rainfall duration that might not...

To accurately quantify landslide hazard in a region of Turkey, we develop new marked point-process models within a Bayesian hierarchical framework for the joint prediction of landslide counts and sizes. We leverage mark distributions justified by extreme-value theory, and specifically propose ‘sub-asymptotic’ distributions to flexibly model landsli...

Maps that attempt to predict landslide occurrences have essentially stayed the same since 1972. In fact, most of the geo-scientific efforts have been dedicated to improve the landslide prediction ability with models that have largely increased their complexity but still have addressed the same binary classification task. In other words, even though...

Recent wildfires in Australia have led to considerable economic loss and property destruction, and there is increasing concern that climate change may exacerbate their intensity, duration, and frequency. hazard quantification for extreme wildfires is an important component of wildfire management, as it facilitates efficient resource distribution, a...

The initial inception of the landslide susceptibility concept defined it as a static property of the landscape, explaining the proneness of certain locations to generate slope failures. Since the spread of data-driven probabilistic solutions though, the original susceptibility definition has been challenged to incorporate dynamic elements that woul...

Classifying a given landscape on the basis of its susceptibility to surface processes is a standard procedure in low to mid-latitudes. Conversely, these procedures have hardly been explored in periglacial regions. However, global warming is radically changing this situation and will change it even more in the future. For this reason, understanding...

Hydro-morphological processes (HMP, any natural phenomenon contained within the spectrum defined between debris flows and flash floods) pose a relevant threat to infrastructure, urban and rural settlements and to lives in general. This has been widely observed in recent years and will likely become worse as climate change will influence the spatio-...

The literature on landslide susceptibility is rich with examples that span a large number of topics. However, the component that pertains to the extension of the susceptibility framework toward space-time modeling is largely unexplored. This statement is even more valid when looking at the landslide risk context, where hardly any scientific contrib...

This study set out to derive empirical rainfall thresholds for landslides in the Progo Catchment, Indonesia, using high-resolution satellite-based precipitation products (SPPs) and rain gauge data. The SPPs are the gauge-adjusted version of the Global Satellite Mapping of Precipitation (GSMaP-GNRT) and the bias-corrected version of the Climate Pred...

Maps that attempt to predict landslide occurrences have essentially stayed the same since 1972. In fact, most of the geo-scientific efforts have been dedicated to improve the landslide prediction ability with models that have largely increased their complexity but still have addressed the same binary classification task. In other words, even though...

We develop a slope-unit based landslide susceptibility model using the benchmark dataset proposed in the session, located in Central Italy. As a result, we produce two susceptibility maps based on the two different landslide presence attribute fields included in the dataset. The proposed dataset is a subset of a much larger one, recently used to ob...

A R T I C L E I N F O Edited by Jing M. Chen Keywords: Hillslope deformation InSAR Prediction Line-of-sight velocity Multivariate regression Sentinel-1 Spatio-temporal model A B S T R A C T Spatiotemporal patterns of earth surface deformation are influenced by a combination of the geologic, topo-graphic, seismic, anthropogenic, meteorological and c...

Classifying a given landscape on the basis of its susceptibility to surface processes is a standard procedure in low to mid-latitudes. Conversely, these procedures have hardly been explored in periglacial regions, primarily because of the limited presence of human settlements and, therefore, the little need for risk assessment. However, global warm...

Strong earthquakes not only induce co-seismic mass wasting but also exacerbates the shear strength of hillslope materials and cause higher landslide susceptibility in the subsequent years following the earthquake. Previous studies have mainly investigated post-seismic landslide activity mainly by using landslide inventories. However, landslide inve...

This manuscript presents an analytical protocol based on explainable AI where the susceptibility to hydro-morphological processes is estimated per catchment at the continental scale. In doing so, we highlight the strength of this approach, for each covariate contribution can be queried and understood at the single mapping unit level. To further e...

The use of Artificial Neural Network (ANN) approaches has gained a significant role over the last decade in the field of predicting the distribution of effects triggered by natural forcing, this being particularly relevant for the development of adequate risk mitigation strategies. Among the most critical features of these approaches, there are the...