C.J. Van Westen

• PhD Eng. Geology, TUDelt
• Professor (Full) at University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC)

Landslides are geomorphic hazards in mountainous terrains across the globe, driven by a complex interplay of static and dynamic controls. Data‐driven approaches have been employed to assess landslide occurrence at regional scales by analyzing the spatial aspects and time‐varying conditions separately. However, the joint assessment of landslides in...

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...

The Heifangtai loess terrace in Gansu Province (China) suffered from frequent irrigation-induced landslides. In the past 50 years, the perennial channel irrigation has resulted in 210 slope failures within a small area of 9 km2. The landslide activity is particularly linked with the cultivation of vegetables, which need more frequent channel irriga...

Coastal communities are confronted with a growing incidence of climate-induced flooding, necessitating adaptation measures for resilience. In this paper, we introduce a framework that integrates an urban digital twin with a geospatial dashboard to allow visualization of the vulnerabilities within critical infrastructure across a range of spatial an...

The increasing frequency of disasters, alongside the recent COVID-19 pandemic, climate emergency, and ongoing/new crises including conflicts and their disproportionate impacts on many communities, all point towards the cascading, multidimensional, and systemic nature of risks. In the wake of this ever-changing risk landscape, it is paramount to ado...

Investigating the preferential flow path of a debris flow is crucial for quantifying the risk and developing mitigation strategies. Here, we examined 66 debris flows from the Western Ghats in India employing Rapid Mass Movement Simulation (RAMMS)::Debris Flow software to understand the kinematics of run-out. Our analysis revealed that the debris fl...

Mapping landslide-depleted source areas is pivotal for refining predictive models and volume estimations, yet these critical regions are often conflated with the landslide runouts, leading to sub-optimal assessments. The source areas are typically the regions where the actual failure occurs, providing crucial information on the initiation mechanism...

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...

Volcanic environments present complex multi-hazard scenarios where primary volcanic activity can trigger cascading hazards or where multiple hazards can occur simultaneously, leading to cascading and compounding impacts on communities and ecosystems. Stromboli, one of the most active volcanoes globally, exemplifies these challenges with its frequen...

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...

Given the destructive nature of hurricanes in tropical regions, pre-disaster evacuation has emerged as a critical approach for hurricane preparedness. Nevertheless, the compounding effects of natural hazards and the outbreak of infectious diseases, such as Covid-19, significantly challenge hurricane evacuation management. To investigate emergency r...

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...

Mapping landslide-depleted source areas is pivotal for refining predictive models and volume estimations, yet these critical regions are often conflated with the landslide runouts, leading to sub-optimal assessments. The source areas are typically the regions where the actual failure occurs, providing crucial information on the initiation mechanism...

A growing number of studies have linked the incidence of leptospirosis with the occurrence of flood events. Nevertheless, the interaction between flood and leptospirosis has not been extensively studied to understand the influence of flood attributes in inducing new cases. This study reviews leptospirosis cases in relation to multiple flood occurre...

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...

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...

Typhoons are recurring meteorological phenomena in the southeastern coastal area of China, frequently triggering debris flows and other forms of slope failures that result in significant economic damage and loss of life in densely populated and economically active regions. Accurate prediction of typhoon-triggered debris flows and identification of...

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...

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...

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...

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...

A growing number of studies have linked the incidence of leptospirosis with the occurrence of flood events. Nevertheless, the interaction between flood and leptospirosis has not been extensively studied. This study reviews leptospirosis case in relation to different flood occurrences in Kerala, India. Leptospirosis data were obtained for three year...

Purpose: Landslides are hazardous mass movements that can be induced by various factors such as lithology, morphology, soil properties, hydrology, and seismicity. To mitigate their impacts, we need to understand their failure mechanisms in diverse contexts and scenarios as this would allow us to improve existing predictive models that generally gro...

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...

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-...

Typhoons are recurrent meteorological phenomena in the South-eastern coastal area of China. They often trigger debris flows and other types of slope failure which cause significant economic damage and loss of life in an area with dense population and high economic activities. Accurate prediction of Typhoon-triggered debris flows and determination o...

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...

Mapping landslides in space has gained a lot of attention over the past decade with good results. Current methods are primarily used to generate event inventories, but multi-temporal (MT) inventories are rare, even with manual landslide mapping. Here, we present an innovative deep learning strategy employing transfer learning. This allows our Atten...

Shallow landslides are frequently occurring hazards in mountainous landscapes all over the world. These processes are caused by a combination of static (i.e., predisposing factors: topography, material properties) and dynamic controls (i.e., preparatory and triggering factors: heavy rainfall, snow-melt). Data-driven methods have been used to model...

Repeated temporal mapping of landslides is essential for investigating changes in landslide movements, legacy effects of the landslide triggering events, and susceptibility changes in the area. However, in order to perform such investigations, multi-temporal (MT) inventories of landslides are required. The traditional approach of visual interpretat...

Ground motion simulations solve wave equations in space and time, thus producing detailed estimates of the shaking time series. This is essentially uncharted territory for geomorphologists, for we have yet to understand which ground motion (synthetic or not) parameter, or combination of parameters, is more suitable to explain the coseismic landslid...

As the Third Pole of the Earth and the Water Tower of Asia, the Tibetan Plateau (TP) nurtures large numbers of glacial lakes, which are sensitive to global climate change. These lakes modulate the freshwater ecosystem in the region but concurrently pose severe threats to the valley population by means of sudden glacial lake outbursts and consequent...

Mapping of landslides over space has seen an increasing attention and good results in the last decade. While current methods are chiefly applied to generate event-inventories, whereas multi-temporal (MT) inventories are rare, even using manual landslide mapping. Here, we present an innovative deep learning strategy which employs transfer learning t...

The current status of technological advancement does not allow to generate complete flood simulations in real-time for large geographic areas. This hinders warning-systems, interactive planning tools and detailed forecasts and as a consequence the population cannot be quickly or reliably informed of where large masses of water will flow. Our novel...

Co-seismic landslides are triggered by strong ground shaking in mountainous areas, resulting in threats to human activity and infrastructure. Methods for physically-based modelling of co-seismic landslide triggering play an important role in disaster prevention and mitigation. Current approaches, however, focus on direct and full failure of sloping...

In order to develop reliable models, the geoscientific community requires high-resolution data sets. However, the collection of such data is a persistent challenge due to the limitations of resources. The concept of super-resolution, a method from the field of machine learning, can be used to predict a high-resolution version of a low-resolution da...

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-...

Small Island Developing States (SIDS) are acknowledged as particularly vulnerable to extreme climate events; however, the realities for transport infrastructure and bridges are still poorly studied. Assessing bridges in this context can be challenging due to data scarcity, a lack of local standards, and uncertainty due to climate change. While brid...

Landslide susceptibility assessment using data-driven models has predominantly focused on predicting where landslides may occur and not on how large they might be. The spatio-temporal evaluation of landslide susceptibility has only recently been addressed, as a basis for predicting where and when landslides might occur. The present study combines t...

The 2008 Wenchuan earthquake lead to various complex multi-hazard chains that included seismically triggered landslide initiation, landslide runout, river damming, dam breaching, and flooding. The modeling of the interactions between such hazardous processes is challenging due to the complexity and uncertainty. Here we present an event-based physic...

The mapping and characterisation of building footprints is a challenging task due to inaccessibility and incompleteness of the required data, thus hindering the estimation of loss caused by natural and anthropogenic hazards. Major advancements have been made in the collaborative mapping of buildings with platforms like OpenStreetMap, however, many...

Land use and land cover changes (LULCCs) in mountainous areas may increase the susceptibility to landslides due to modifications of topography, vegetation, and material characteristics. Understanding the relation between LULCCs and landslide occurrences is important for landslide prevention and land resources management. In this study, these change...

Landslides of the slide-type movement represent a potential threat to people and infrastructure in mountain areas all over the world. At regional scales, data-driven models are typically used to assess landslide susceptibility, i.e., to map where landslides are more or less likely to occur. Such assessments frequently serve as basic input for lands...

Portraying spatiotemporal variations in landslide susceptibility patterns is crucial for landslide prevention and management. In this study, we implement a space-time modeling approach to predict the landslide susceptibility on a yearly basis across the main island of Taiwan, from 2004 to 2018. We use a Bayesian version of a binomial generalized ad...

Repeated temporal mapping of landslides is essential for investigating changes in landslide movements, legacy effects of the landslide triggering events, and susceptibility changes in the area. However, in order to perform such investigations, multi-temporal (MT) inventories of landslides are required. The traditional approach of visual interpretat...

Understanding the effects of snowmelt in terms of large slope deformation in high mountainous areas could come from the use of Interferometric Synthetic Aperture Radar (InSAR) techniques. In this work, we investigate a slow moving, extremely large landslide (~20 km2) in the Chitral region in Northern Pakistan, which threatens several villages. Our...

For decades, a full numerical description of the spatio-temporal dynamics of a landslide could be achieved only via physics-based models. The part of the geomorphology community focusing on data-driven model has instead focused on predicting where landslides may occur via susceptibility models. Moreover, they have estimated when landslides may occu...

Climatically-induced natural hazards are a threat to communities. They can cause life losses and heavy damage to infrastructure, and due to climate change, they have become increasingly frequent. This is especially the case in tropical regions, where major hurricanes have consistently appeared in recent history. Such events induce damage due to the...

Super Resolution is a method for artificially increasing the imaging system's resolution by post processing without having to collect new datasets. It is mostly developed and used in computer graphics by the computer science community for image and video enhancement due to its capacity to add spatial variations in the data and perform better than c...

Shallow landslides of the slide-type movement represent potentially damaging events in mountain areas all over the world. These geomorphic processes are caused by a combination of predisposing factors (e.g., hillslope material), preparatory conditions (e.g., prolonged snow-melt), and triggers (e.g., heavy rainfall). Data-driven methods have been us...

Hazardous surface processes such as floods and mass movements are often induced by a common trigger such as extreme precipitation. The relationship between the intensity of the trigger and the surface hazard is generally assumed to be monotonically increasing (increasing precipitation never decreases hazard intensity). The validity of this assumpti...

Event-based landslide inventories are essential sources to broaden our understanding of the causal relationship between triggering events and the occurring landslides. Moreover, detailed inventories are crucial for the succeeding phases of landslide risk studies like susceptibility and hazard assessment. The openly available inventories differ in t...

The 2008 Wenchuan earthquake lead to various complex multi-hazard chains that included seismically-triggered landslide initiation, landslide run-out, river damming, dam breaching and flooding. The modelling of the interactions between such hazardous processes is challenging due to the complexity and uncertainty. Here we present an event-based physi...

Mapping existing landslides is a fundamental prerequisite to build any reliable susceptibility model. From a series of landslide presence/absence conditions and associated landscape characteristics, a binary classifier learns how to distinguish potentially stable and unstable slopes. In data rich areas where landslide inventories are available, add...

Climatically-induced natural hazards are a threat to communities. They can cause life losses and heavy damage to infrastructure, and due to climate change, they have become increasingly frequent. This is especially in tropical regions, where major hurricanes have consistently appeared in recent history. Such events induce damage due to the high win...

Transportation networks are severely affected by natural hazards, including landslides. The prioritization of maintenance works is required to preserve the efficiency and functionality of road infrastructure. To overcome the subjectivity of traditional visual inspections for road pavement condition assessment, advanced (semi-)automatic approaches h...

Earthquakes increase landslide susceptibility in post-seismic periods. The time required for restoring pre-earthquake susceptibility levels is defined as landslide recovery time. Overall, stronger earthquakes are associated with relatively long recovery times in the literature. However, the seismic effect does not explain the whole process. This pa...

Earthquakes do not only trigger landslides in co-seismic phases but also elevate post-seismic landslide susceptibility either by causing a strength reduction in hillslope materials or by producing co-seismic landslide deposits, which are prone to further remobilization under the external forces generated by subsequent rainfall events. However, we s...

Floods are frequent hydro-meteorological hazards which cause losses in many parts of the world. In hilly and mountainous environments, floods often contain sediments which are derived from mass movements and soil erosion. The deposited sediments cause significant direct damage, and indirect costs of clean-up and sediment removal. The quantification...

Mass movements such as debris flows and landslides differ in behaviour due to their material properties and internal forces. Models employ generalized multi-phase flow equations to adaptively describe these complex flow types. Such models commonly assume unstructured and fragmented flow, where internal cohesive strength is insignificant. In this wo...

This paper discusses approaches to evaluate how landslide risk might change over time. Multi-hazard risk assessment (MHRA) is the quantitative estimation of the spatial distributions of potential losses for an area, of multiple natural hazards with different hazard interactions, with multiple event probabilities, for multiple types of elements-at-r...

This document is a training manual, for a course on „Changing Multi-Hazard Risk Assessment for Decision making“. It is accompanied by a GIS dataset and an Open Source and a simple to use GIS system (ILWIS). It is aimed for a course of 10 -13 days. The training material is freely available and can be used in other courses, as long as you cite the re...

Data set belonging to the tutorial, for a course on „Changing Multi-Hazard Risk Assessment for Decision making“. It is accompanied by a tutorial text and an Open Source and a simple to use GIS system (ILWIS). It is aimed for a course of 10 -13 days. The training material is freely available and can be used in other courses, as long as you cite the...

The application of physically-based approaches for slope failure analysis at a catchment scale remains a difficult challenge, and several new models have been proposed in recent years. The assumptions of these models vary significantly. Tools such as random ellipsoid sampling provide detailed assessment of failure probability but due to numerical c...

The vast majority of statistically-based landslide susceptibility studies assumes the slope instability process to be time-invariant under the definition that “the past and present are keys to the future”. This assumption may generally be valid. However, the trigger, be it a rainfall or an earthquake event, clearly varies over time. And yet, the te...