Filippo Catani

Filippo Catani
University of Padova | UNIPD · Department of Geosciences

PhD Engineering Geology; MSc Geology and Geochemistry; BSc Computer Sciences
Building up the Machine Intelligence & Slope Stability Laboratory at the University of Padova - work in progress ...

About

218
Publications
87,225
Reads
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7,107
Citations
Introduction
Latest interests in research: landslide hazard, machine learning applied to geohazards, monitoring and modelling of basin-scale surface processes, natural hazards, applications of remote sensing to landslide studies, oil & gas environmental impact and risk, surface monitoring in open-pit mines, scaling processes in geomorphology.
Additional affiliations
December 2020 - present
University of Padova
Position
  • Professor
April 2016 - present
UNESCO Chair on Prevention and Sustainable Management of Geo-Hydrological Hazards
Position
  • Chair
November 2014 - November 2020
University of Florence
Position
  • Professor (Associate)
Education
October 1994 - February 1998
Politecnico di Milano
Field of study
  • Engineering Geology
October 1985 - November 1989
University of Florence
Field of study
  • Geology

Publications

Publications (218)
Article
Full-text available
1] Catchment modeling in areas dominated by active geomorphologic processes, such as soil erosion and landsliding, is often hampered by the lack of reliable methods for the spatial estimation of soil depth. In a catchment, soil thickness h can vary as a function of many different and interplaying factors, such as underlying lithology, climate, grad...
Article
Full-text available
Despite the large number of recent advances and developments in landslide susceptibility mapping (LSM) there is still a lack of studies focusing on specific aspects of LSM model sensitivity. For example, the influence of factors such as the survey scale of the landslide conditioning variables (LCVs), the resolution of the mapping unit (MUR) and the...
Article
Full-text available
The magnitude of mass movements, which may be expressed by their dimension in terms of area or volume, is an important component of intensity together with velocity. In the case of slow-moving deep-seated landslides, the expected magnitude is the prevalent parameter for defining intensity when assessed as a spatially distributed variable in a given...
Article
Full-text available
Strong earthquakes, especially on mountain slopes, can generate large amounts of unconsolidated deposits, prone to remobilization by aftershocks and rainstorms. Assessing the hazard they pose and what drives their movement in the years following the mainshock has not yet been attempted, primarily because multi-temporal landslide inventories are lac...
Article
Full-text available
The recent development of mobile surveying platforms and crowdsourced geoinformation has produced a huge amount of non-validated data that are now available for research and application. In the field of risk analysis, with particular reference to landslide hazard, images generated by autonomous platforms (such as UAVs, ground-based acquisition syst...
Article
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Landslides are affected not only by their own environmental factors, but also by the neighborhood environmental factors and the landslide clustering effect, which are represented as the neighborhood characteristics of modelling spatial datasets in landslide susceptibility prediction (LSP). This study aims to innovatively explore the neighborhood ch...
Article
Full-text available
To perform landslide susceptibility prediction (LSP), it is important to select appropriate mapping unit and landslide-related conditioning factors. The efficient and automatic multi-scale segmentation (MSS) method proposed by the authors promotes the application of slope units. However, LSP modeling based on these slope units has not been performe...
Preprint
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...
Preprint
Full-text available
The uncertainty of non-landslide sample selection has a crucial influence on the landslide susceptibility prediction (LSP), which has not been thoroughly studied. In this study, a novel framework based on slope unit-based machine learning models is proposed to solve this issue. First, slope units are extracted by the multi-scale segmentation method...
Conference Paper
Full-text available
Multiple landslide events are one of the most critical natural hazards. Landslide occurrences have become more frequent in recent decades because of rapid urbanization and climate change, causing widespread failures throughout the world. Extreme landslide events can cause severe damages to both human lives and infrastructures. Hence, there is a gro...
Conference Paper
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Early warning for complex landslides is a difficult task since their evolution could depend on the combination of various predisposing and triggering geological (e.g. rock type, water circulation) and climatic factors (e.g. rainfall, snowmelt). Depending on the type of phenomenon, the temporal evolution of a landslide can be monitored in several wa...
Conference Paper
Full-text available
Landslide inventories are essential for landslide susceptibility mapping, hazard modelling, and further risk mitigation management. For decades, experts and organisations worldwide have preferred manual visual interpretation of satellite and aerial images. However, there are various problems associated with manual inventories, such as manual extrac...
Conference Paper
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In sub-Saharan Africa, artisanal and small-scale mining (ASM) represents a source of subsistence for a significant number of individuals. While 40 million people officially work in ASM across 80 countries, more than 150 million rely indirectly upon ASM. However, because ASM is often illegal, and uncontrolled, the materials employed in the excavatio...
Conference Paper
Full-text available
Landslide susceptibility maps are often not validated after significant landslide events. In this work, we analyse the impact of the Vaia windstorm on landslide activity in Belluno province (Veneto Region, NE, Italy). The storm hit the area on October 27-30, 2018, causing 8,679 ha of damaged forests and widespread landslides. As shown in the case o...
Conference Paper
Full-text available
Frequent and extreme meteorological events can lead to an increase in landslide hazard. A multi-temporal inventory plays an essential role in monitoring slope processes over time and forecasting future evolution. In recent years, the province of Belluno (Veneto Region, NE Italy) was affected by two relevant and intense meteorological phenomena that...
Article
Full-text available
In the domain of landslide risk science, landslide susceptibility mapping (LSM) is very important, as it helps spatially identify potential landslide-prone regions. This study used a statistical ensemble model (frequency ratio and evidence belief function) and two machine learning (ML) models (random forest and XGBoost; eXtreme Gradient Boosting) f...
Article
Full-text available
Landslide hazard mapping is essential for disaster reduction and mitigation. The hazard map produced by the spatiotemporal probability analysis is usually static with false-negative and false-positive errors due to limited data resolution. Here we propose a new method to obtain dynamic landslide hazard maps over the Wushan section of the Three Gorg...
Article
Full-text available
Landslides represent a serious worldwide hazard, especially in Italy, where exposure to hydrogeological risk is very high; for this reason, a landslide quantitative risk assessment (QRA) is crucial for risk management and for planning mitigation measures. In this study, we present and describe a novel methodological approach of QRA for slow-moving...
Article
Full-text available
One of the main constraints in assessing shallow landslide hazards through physically based models is the need to characterize the geotechnical parameters of the involved materials. Indeed, the quantity and quality of input data are closely related to the reliability of the results of every model used, therefore data acquisition is a critical and t...
Article
Full-text available
Multiple landslide events are common around the globe. They can cause severe damage to both human lives and infrastructures. Although a huge quantity of research has been shaped to address rapid mapping of landslides by optical Earth Observation (EO) data, various gaps and uncertainties are still present when dealing with cloud obscuration and 24/7...
Article
Full-text available
The Three Gorges Hydropower Station is the largest hydropower station worldwide with the impoundment of the 660-km long reservoir. More than 500 landslides have been triggered by the reservoir water level fluctuation since the first impoundment in 2003. The classification of the reservoir affected landslide (seepage-driven and buoyancy-driven lands...
Article
Full-text available
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...
Article
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A promised potential of spaceborne interferometric synthetic aperture radars (InSAR) is a capability for regularly monitoring ground deformation with millimeter accuracy, for timely forecasting of impending natural hazards such as landslides. The main limitation in InSAR being actually capable of unleashing this potential for hazard prediction is t...
Article
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The patterns and controls of the transient enhanced landsliding that follows strong earthquakes remain elusive. Geostatistical models can provide clues on the underlying processes by identifying relationships with a number of physical variables. These models do not typically consider thermal information, even though temperature is known to affect t...
Article
Full-text available
Nowadays, several systems to set up landslide inventories exist although they rarely rely on automated or real-time updates. Mass media can provide reliable info about natural hazard events with a relatively high temporal and spatial resolution. The news publication about a natural disaster inside newspaper or crowd-sourcing platforms allows a fast...
Article
In this letter, we use deep-learning convolutional neural networks (CNNs) to compare the landslide mapping and classification performances of optical images (from Sentinel-2) and SAR images (from Sentinel-1). The training, validation and test zones used to independently evaluate the performance of the CNN1on different datasets are located in the ea...
Conference Paper
Full-text available
Several territorial landslide early warning systems in different parts of the world are based on empirical rainfall thresholds for landslide triggering. The calculation of such thresholds, using rainfall measurements gathered from rain gauges, has been examined frequently, especially considering uncertainties, modeling complexity, spatial assumptio...
Preprint
Full-text available
In the domain of landslide risk science, landslide susceptibility mapping (LSM) is very important as it helps spatially identify potential landslide-prone regions. This study used a statistical ensemble model (Frequency Ratio and Evidence Belief Function) and two machine learning (ML) models (Random Forest and XG-Boost) for LSM in the Belluno provi...
Article
Full-text available
The concept of climate change has grown in recent decades, influencing the scientific community to conduct research on meteorological parameters and their variabilities. Research on global warming, as well as on its possible economic and environmental consequences, has spread over the last 20 years. Diffused changes in trends have been stated by se...
Chapter
In the attempt of mitigating landslide risks, the capability of quantitatively assessing hazard, that is the probability of occurrence of a possibly damaging event in time and space, is fundamental. In this chapter, we will briefly review the main operational methods for the prediction and the forecasting of the time of occurrence of mass movements...
Preprint
To join the Scientists Adoption Academy [ scadacademy.com ] +++++++++++++++++++++ Abstract: Regional calculation of the spatial rainfall threshold that triggers landslides has been examined frequently, especially in light of uncertainties, modeling complexity, spatial assumptions, and analytical tools. Installed rainfall stations that are spatia...
Article
Full-text available
Multi-Temporal Satellite Interferometry (MTInSAR) is gradually evolving from being a tool developed by the scientific community exclusively for research purposes to a real operational technique that can meet the needs of different users involved in geohazard mitigation. This work aims at showing the innovative operational use of satellite radar int...
Preprint
Full-text available
In this letter, we use deep-learning convolution neural networks (CNNs) to assess the landslide mapping and classification performances on optical images (from Sentinel-2) and SAR images (from Sentinel-1). The training and test zones used to independently evaluate the performance of the CNNs on different datasets are located in the eastern Iburi su...
Article
Full-text available
Landslide susceptibility maps (LSM) define the spatial probability of landslide occurrence based on the spatial distribution of predisposing factors. In this work, a LSM is produced for Norther Tuscany (3100 km2) with a Random Forest algorithm. The element of novelty is the use, besides 15 state-of-the-art parameters, of some newly proposed paramet...
Conference Paper
In the last decades, extreme meteorological events, such as wind disturbances, have increased their frequency and their strength due to the effects of the climate changes and are expected to further intensify in the future. The strong winds combined with heavy rain modify the water-soil interaction and the soil mechanics raising the landslides haza...
Chapter
Physically-based models employed for landslide forecasting are extremely sensitive to the use of geological information and a standard, universally accepted method to input maps containing information of geological interest into the models still has never been established. In this study, we used the information contained in a geo-database aimed to...
Chapter
The UNESCO Chair on Prevention and Sustainable Management of Geo-Hydrological Hazards, Department of earth Sciences, University of Florence has been a member of the International Consortium on Landslides (ICL) since 2002 and was designated as one of World Centres of Excellence (WCoE) for Landslide Risk Reduction four times for 2008–2011, 2011–2014,...
Chapter
Full-text available
Landslide dams may collapse within few hours/days after their formation resulting in destructive flooding wave. Due to the limited time available since their formation, forecasting tools able to assess the damming susceptibility over large areas are more advisable for prevention and setting up mitigation measures. A semi-automated GIS-based methodo...
Chapter
In this work we exploited Sentinel-1 satellite radar images processed by means of Persistent Scatterers Interferometry (PSI) techniques for the evaluation of landslide geohazard and impact on a mountainous region. In particular, we used PSI data as starting point in a working chain whose final goal is the estimation of the potential worth of loss o...
Article
Full-text available
Landslides are a common natural hazard that causes casualties and unprecedented economic losses every year, especially in vulnerable developing countries. Considering the high cost of in-situ monitoring equipment and the sparse coverage of monitoring points, the Sentinel-1 images and Interferometric Synthetic Aperture Radar (InSAR) technique were u...
Article
Full-text available
The intensity-duration (I-D) threshold is considered an effective indicator for landslides triggered by short-term high-intensity rainfall and long-term low-intensity rainfall. However, previous studies have not considered the influence of antecedent rainfall. Herein, we analyzed hourly rainfall data for 613 shallow landslides that occurred from 19...
Article
Full-text available
From a geological standpoint, northern Pakistan is one of the most active and unstable areas in the world. As a consequence, many massive landslides have occurred in the area in historical times that have destroyed infrastructure, blocked the Hunza River, and damaged the Karakoram Highway repeatedly. However, despite the high frequency of large mag...
Article
Full-text available
Landslide susceptibility maps are widely used in landslide hazard management. Although many models have been proposed, mapping unit definition is a matter that still needs to be fully examined. In the literature, the most reported mapping units are pixels and slope units, while in this work, developed in the Rio de Janeiro region (Brazil), the use...
Conference Paper
Full-text available
In the middle of the 20th century, one of the largest open pit mining facilities in the world was established at Grasberg on top of the main Papuan ridge. In time, this expanded to become the most notable man-made landscape feature on the entire island. Mining operations are supported by a large array of workshops and facilities, scattered from the...
Article
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Soil sealing is the destruction or covering of natural soils by totally or partially impermeable artificial material. ISPRA (Italian Institute for Environmental Protection Research) uses different remote sensing techniques to monitor this process and updates yearly a national-scale soil sealing map of Italy. In this work, for the first time, we tri...
Article
Full-text available
Soil organic matter (SOM) represents a main fraction of superficial soil characterized by a mechanical-hydrological behaviour different from that of the inorganic fractions. In this study, a method to measure the SOM content was applied to 27 selected sites in Tuscany (central Italy) characterized by the presence of soil types common in the region:...
Article
Full-text available
A complete landslide dam hazard management incorporates two assessment phases: the damming probability and the breach hazard. A prompt evaluation of the dam stability is crucial during the emergency to mitigate its consequences, but a reliable risk assessment can be realized only after the event has occurred, when the available time is very short....
Article
Full-text available
Strong winds may uproot and break trees and represent a major natural disturbance for European forests. Wind disturbances have intensified over the last decades globally and are expected to further rise in view of the effects of climate change. Despite the importance of such natural disturbances, there are currently no spatially explicit databases...
Article
Full-text available
The literature about landslide susceptibility mapping is rich of works focusing on improving or comparing the algorithms used for the modeling, but to our knowledge, a sensitivity analysis on the use of geological information has never been performed, and a standard method to input geological maps into susceptibility assessments has never been esta...
Article
Full-text available
Multi-Temporal Interferometric Synthetic Aperture Radar (MTInSAR) data offer a valuable support to landslide mapping and to landslide activity estimation in mountain environments, where in situ measures are sometimes difficult to gather. Nowadays, the interferometric approach is more and more used for wide-areas analysis, providing useful informati...