This page has only limited features, please log in for full access.

Dr. Francesca Ardizzone
Consiglio Nazionale delle Ricerche - Itituto di Ricerca per la Protezione Idrogeologica

Basic Info


Research Keywords & Expertise

0 geological
0 Implementation of geodatabase of geological
0 Geomorphological
0 And environmental data
0 Detection and mapping of landslides in different climatic

Fingerprints

Geomorphological
geological
Landslide risk assessment and mapping
Geological and geomorphological interpretation of ground deformation measured by satellites

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Science
Published: 27 June 2021 in Journal of Maps
Reads 0
Downloads 0

Landslide inventories provide the knowledge basis for many geomorphological applications and also planning and emergency management. Detailed landslide inventories should also be prepared where pre-existing inventories are available, as knowledge updates. In this paper, we present a new geomorphological landslide inventory for an area of the High Agri Valley, Southern Italian Apennines. The map was prepared through systematic interpretation of historical aerial photographs testing extensive use of anaglyph glasses in StereoPhoto Maker freeware. A total of 2124 landslides were classified based on the type of movement, estimated depth, estimated relative age and three levels of uncertainty, providing landslide attributes and map constraints useful for land planning and hazard studies. The map also documents the relationships between landslides and fluvial landforms of different generations, recording important information to investigate the geomorphological evolution of the area further. We expect that landslide mapping in similar environments will benefit from the workflow here presented.

ACS Style

F. Bucci; M. Santangelo; F. Fiorucci; F. Ardizzone; D. Giordan; M. Cignetti; D. Notti; P. Allasia; D. Godone; D. Lagomarsino; A. Pozzoli; E. Norelli; M. Cardinali. Geomorphologic landslide inventory by air photo interpretation of the High Agri Valley (Southern Italy). Journal of Maps 2021, 17, 376 -388.

AMA Style

F. Bucci, M. Santangelo, F. Fiorucci, F. Ardizzone, D. Giordan, M. Cignetti, D. Notti, P. Allasia, D. Godone, D. Lagomarsino, A. Pozzoli, E. Norelli, M. Cardinali. Geomorphologic landslide inventory by air photo interpretation of the High Agri Valley (Southern Italy). Journal of Maps. 2021; 17 (2):376-388.

Chicago/Turabian Style

F. Bucci; M. Santangelo; F. Fiorucci; F. Ardizzone; D. Giordan; M. Cignetti; D. Notti; P. Allasia; D. Godone; D. Lagomarsino; A. Pozzoli; E. Norelli; M. Cardinali. 2021. "Geomorphologic landslide inventory by air photo interpretation of the High Agri Valley (Southern Italy)." Journal of Maps 17, no. 2: 376-388.

Original paper
Published: 10 February 2021 in Natural Hazards
Reads 0
Downloads 0

Analyses of historical records of landslides and climate variables are useful tools to search for correlations between damaging landslide events and their triggers. In this work, we investigate the temporal and geographical relationships between two long-term historical series of catalogued landslide occurrences and daily rainfall data in Umbria, a central Italian region, from 1928 to 2001. Moreover, we search for changes in the frequency and density of landslides, and in the characteristics of the associated rainfall events. Using a consolidated approach, partially modified, we find that the rainfall events that have produced rainfall-induced landslides in Umbria changed in space and time during observation period and between two considered sub-periods (1928–1975 and 1976–2001). In particular, we find that: (i) the monthly distribution of landslides associated with rainfall events is quite different than that of all landslides in the regional catalogue; (ii) the spatial and temporal distribution of REL changed from the older (most events occurred in winter) to the recent period (most events occurred in autumn); (iii) the recent most rainfall events associated with landslides are characterized by a lower cumulated rainfall and a shorter duration, sign of an increased propensity of the regional territory to produce landslides over time.

ACS Style

S. L. Gariano; G. Verini Supplizi; F. Ardizzone; P. Salvati; C. Bianchi; R. Morbidelli; C. Saltalippi. Long-term analysis of rainfall-induced landslides in Umbria, central Italy. Natural Hazards 2021, 106, 2207 -2225.

AMA Style

S. L. Gariano, G. Verini Supplizi, F. Ardizzone, P. Salvati, C. Bianchi, R. Morbidelli, C. Saltalippi. Long-term analysis of rainfall-induced landslides in Umbria, central Italy. Natural Hazards. 2021; 106 (3):2207-2225.

Chicago/Turabian Style

S. L. Gariano; G. Verini Supplizi; F. Ardizzone; P. Salvati; C. Bianchi; R. Morbidelli; C. Saltalippi. 2021. "Long-term analysis of rainfall-induced landslides in Umbria, central Italy." Natural Hazards 106, no. 3: 2207-2225.

Journal article
Published: 30 January 2021 in International Journal of Disaster Risk Reduction
Reads 0
Downloads 0

Geo-hydrological risk reduction is a key issue for local governments in Italy. In this context, a collaboration was undertaken between multiple actors in the La Spezia municipality aimed at: (i) monitoring building characteristics, using specific and valuable indicators, and (ii) increasing the knowledge of geo-hydrological hazards across residents and local land planners (iii) implementing local emergency civil protection plan. An extensive mobile data collection was carried out through apps specifically developed for Android and IOS mobile devices. The digital forms were differentiated on the basis of the potential hazard: one of 46 fields and one of 125 fields designed for buildings respectively located in flood prone areas and in medium to very high landslide susceptibility areas. The digital version of the forms was designed using the Open Data Kit (ODK) and GISCloud client-server approach. All the collected data, including geospatial locations and images, were automatically sent to a central server, stored and organized in a database. Geospatial data-analysis and maps resulted useful in evaluating possible impacts to exposed buildings to potential geo-hydrological processes. The proposed public participation method for data-gathering increased the knowledge across residents providing a better understanding of the urban systems, of the buildings condition and their relation respect to the geo-hydrological risk. The method can be considered as part of the decision support systems for civil protection purposes to better planning geo-hydrological mitigation measures. The application of mobile technology for data collection can be effectively used when local government resources are limited.

ACS Style

Paola Salvati; Francesca Ardizzone; Mauro Cardinali; Federica Fiorucci; Federico Fugnoli; Fausto Guzzetti; Ivan Marchesini; Gianluca Rinaldi; Mauro Rossi; Michele Santangelo; Ivan Vujica. Acquiring vulnerability indicators to geo-hydrological hazards: An example of mobile phone-based data collection. International Journal of Disaster Risk Reduction 2021, 55, 102087 .

AMA Style

Paola Salvati, Francesca Ardizzone, Mauro Cardinali, Federica Fiorucci, Federico Fugnoli, Fausto Guzzetti, Ivan Marchesini, Gianluca Rinaldi, Mauro Rossi, Michele Santangelo, Ivan Vujica. Acquiring vulnerability indicators to geo-hydrological hazards: An example of mobile phone-based data collection. International Journal of Disaster Risk Reduction. 2021; 55 ():102087.

Chicago/Turabian Style

Paola Salvati; Francesca Ardizzone; Mauro Cardinali; Federica Fiorucci; Federico Fugnoli; Fausto Guzzetti; Ivan Marchesini; Gianluca Rinaldi; Mauro Rossi; Michele Santangelo; Ivan Vujica. 2021. "Acquiring vulnerability indicators to geo-hydrological hazards: An example of mobile phone-based data collection." International Journal of Disaster Risk Reduction 55, no. : 102087.

Journal article
Published: 05 April 2020 in Journal of Maps
Reads 0
Downloads 0

The paper describes the multitemporal landslide inventory map prepared for the urban areas of Motta Montecorvino and Volturino, two municipalities located in the Southern Apennines (Apulia Region, Italy). These territories show a high propensity to landslides of different types and magnitude, which periodically interfere with the anthropic structures and infrastructures. For the study area, the spatial and temporal distribution of landslides is detected for the period between 1954 and 2003, through the visual interpretation of multiple sets of black and white digital stereoscopic aerial photographs at different scales. The analysis reveals locally high frequency of landslide occurrence and built-up areas on existing landslides, either on the body or on the crown areas. In particular, we show that over the years new residential areas were developed despite the presence of large old mass movements.

ACS Style

Veronica Zumpano; Francesca Ardizzone; Francesco Bucci; Mauro Cardinali; Federica Fiorucci; Mario Parise; Luca Pisano; Paola Reichenbach; Francesca Santaloia; Michele Santangelo; Janusz Wasowski; Piernicola Lollino. The relation of spatio-temporal distribution of landslides to urban development (a case study from the Apulia region, Southern Italy). Journal of Maps 2020, 1 -8.

AMA Style

Veronica Zumpano, Francesca Ardizzone, Francesco Bucci, Mauro Cardinali, Federica Fiorucci, Mario Parise, Luca Pisano, Paola Reichenbach, Francesca Santaloia, Michele Santangelo, Janusz Wasowski, Piernicola Lollino. The relation of spatio-temporal distribution of landslides to urban development (a case study from the Apulia region, Southern Italy). Journal of Maps. 2020; ():1-8.

Chicago/Turabian Style

Veronica Zumpano; Francesca Ardizzone; Francesco Bucci; Mauro Cardinali; Federica Fiorucci; Mario Parise; Luca Pisano; Paola Reichenbach; Francesca Santaloia; Michele Santangelo; Janusz Wasowski; Piernicola Lollino. 2020. "The relation of spatio-temporal distribution of landslides to urban development (a case study from the Apulia region, Southern Italy)." Journal of Maps , no. : 1-8.

Preprint content
Published: 09 March 2020
Reads 0
Downloads 0

Landslides are nearly ubiquitous phenomena and pose severe threats to people, properties, and the environment. Investigators have for long attempted to estimate landslide hazard to determine where, when, and how destructive landslides are expected to be in an area. This information is useful to design landslide mitigation strategies, and to reduce landslide risk and societal and economic losses. In the geomorphology literature, most attempts at predicting the occurrence of populations of landslides rely on the observation that landslides are the result of multiple interacting, conditioning and triggering factors. Here, we propose a novel Bayesian modelling framework for the prediction of space-time landslide occurrences of the slide type caused by weather triggers. We consider log-Gaussian cox processes, assuming that individual landslides stem from a point process described by an unknown intensity function. We tested our prediction framework in the Collazzone area, Umbria, Central Italy, for which a detailed multi-temporal landslide inventory spanning 1941-2014 is available together with lithological and bedding data. We tested five models of increasing complexity. Our most complex model includes fixed effects and latent spatio-temporal effects, thus largely fulfilling the common definition of landslide hazard in the literature. We quantified the spatio-temporal predictive skill of our model and found that it performed better than simpler alternatives. We then developed a novel classification strategy and prepared an intensity-susceptibility landslide map, providing more information than traditional susceptibility zonations for land planning and management. We expect our novel approach to lead to better projections of future landslides, and to improve our collective understanding of the evolution of landscapes dominated by mass-wasting processes under geophysical and weather triggers.

ACS Style

Luigi Lombardo; Thomas Opitz; Francesca Ardizzone; Raphaël Huser; Fausto Guzzetti. Space-Time Landslide Predictive Modelling. 2020, 1 .

AMA Style

Luigi Lombardo, Thomas Opitz, Francesca Ardizzone, Raphaël Huser, Fausto Guzzetti. Space-Time Landslide Predictive Modelling. . 2020; ():1.

Chicago/Turabian Style

Luigi Lombardo; Thomas Opitz; Francesca Ardizzone; Raphaël Huser; Fausto Guzzetti. 2020. "Space-Time Landslide Predictive Modelling." , no. : 1.

Research article
Published: 22 January 2020 in Natural Hazards and Earth System Sciences
Reads 0
Downloads 0

This contribution tests the added value of including landslide path dependency in statistically based landslide susceptibility modelling. A conventional pixel-based landslide susceptibility model was compared with a model that includes landslide path dependency and with a purely path-dependent landslide susceptibility model. To quantify path dependency among landslides, we used a space–time clustering (STC) measure derived from Ripley's space–time K function implemented on a point-based multi-temporal landslide inventory from the Collazzone study area in central Italy. We found that the values of STC obey an exponential-decay curve with a characteristic timescale of 17 years and characteristic spatial scale of 60 m. This exponential space–time decay of the effect of a previous landslide on landslide susceptibility was used as the landslide path-dependency component of susceptibility models. We found that the performance of the conventional landslide susceptibility model improved considerably when adding the effect of landslide path dependency. In fact, even the purely path-dependent landslide susceptibility model turned out to perform better than the conventional landslide susceptibility model. The conventional plus path-dependent and path-dependent landslide susceptibility model and their resulting maps are dynamic and change over time, unlike conventional landslide susceptibility maps.

ACS Style

Jalal Samia; Arnaud Temme; Arnold Bregt; Jakob Wallinga; Fausto Guzzetti; Francesca Ardizzone. Dynamic path-dependent landslide susceptibility modelling. Natural Hazards and Earth System Sciences 2020, 20, 271 -285.

AMA Style

Jalal Samia, Arnaud Temme, Arnold Bregt, Jakob Wallinga, Fausto Guzzetti, Francesca Ardizzone. Dynamic path-dependent landslide susceptibility modelling. Natural Hazards and Earth System Sciences. 2020; 20 (1):271-285.

Chicago/Turabian Style

Jalal Samia; Arnaud Temme; Arnold Bregt; Jakob Wallinga; Fausto Guzzetti; Francesca Ardizzone. 2020. "Dynamic path-dependent landslide susceptibility modelling." Natural Hazards and Earth System Sciences 20, no. 1: 271-285.

Journal article
Published: 18 December 2019 in ISPRS International Journal of Geo-Information
Reads 0
Downloads 0

Nowadays, the increasing demand to collect, manage and share archives of data supporting geo-hydrological processes investigations requires the development of spatial data infrastructure able to store geospatial data and ground deformation measurements, also considering multisource and heterogeneous data. We exploited the GeoNetwork open-source software to simultaneously organize in-situ measurements and radar sensor observations, collected in the framework of the HAMMER project study areas, all located in high mountain regions distributed in the Alpines, Apennines, Pyrenees and Andes mountain chains, mainly focusing on active landslides. Taking advantage of this free and internationally recognized platform based on standard protocols, we present a valuable instrument to manage data and metadata, both in-situ surface measurements, typically acquired at local scale for short periods (e.g., during emergency), and satellite observations, usually exploited for regional scale analysis of surface displacement. Using a dedicated web-interface, all the results derived by instrumental acquisitions and by processing of remote sensing images can be queried, analyzed and downloaded from both expert users and stakeholders. This leads to a useful instrument able to share various information within the scientific community, including the opportunity of reprocessing the raw data for other purposes and in other contexts.

ACS Style

Martina Cignetti; Diego Guenzi; Francesca Ardizzone; Paolo Allasia; Daniele Giordan. An Open-Source Web Platform to Share Multisource, Multisensor Geospatial Data and Measurements of Ground Deformation in Mountain Areas. ISPRS International Journal of Geo-Information 2019, 9, 4 .

AMA Style

Martina Cignetti, Diego Guenzi, Francesca Ardizzone, Paolo Allasia, Daniele Giordan. An Open-Source Web Platform to Share Multisource, Multisensor Geospatial Data and Measurements of Ground Deformation in Mountain Areas. ISPRS International Journal of Geo-Information. 2019; 9 (1):4.

Chicago/Turabian Style

Martina Cignetti; Diego Guenzi; Francesca Ardizzone; Paolo Allasia; Daniele Giordan. 2019. "An Open-Source Web Platform to Share Multisource, Multisensor Geospatial Data and Measurements of Ground Deformation in Mountain Areas." ISPRS International Journal of Geo-Information 9, no. 1: 4.

Preprint content
Published: 08 July 2019
Reads 0
Downloads 0

This contribution tests the added value of including landslide path dependency in statistically-based landslide susceptibility modelling. A conventional pixel-based landslide susceptibility model was compared with a model that includes landslide path dependency, and with a purely path dependent landslide susceptibility model. To quantify path dependency among landslides, we used a Space-Time Clustering (STC) measure derived from Ripley's space-time K function implemented on a point-based multi-temporal landslide inventory from the Collazzone study area in central Italy. We found that the values of STC obey an exponential decay curve with characteristic time scale of 17 years, and characteristic space scale of 60 meters. This exponential space-time decay of the effect of a previous landslide on landslide susceptibility was used as the landslide path dependency component of susceptibility models. We found that the performance of the conventional landslide susceptibility model improved considerably when adding the effect of landslide path dependency. In fact, even the purely path dependent landslide susceptibility model turned out to perform better than the conventional landslide susceptibility model. The conventional plus path dependent and path dependent landslide susceptibility model and their resulted maps are dynamic and change over time unlike conventional landslide susceptibility maps.

ACS Style

Jalal Samia; Arnaud Temme; Arnold Bregt; Jakob Wallinga; Fausto Guzzetti; Francesca Ardizzone. Dynamic path dependent landslide susceptibility modelling. 2019, 2019, 1 -20.

AMA Style

Jalal Samia, Arnaud Temme, Arnold Bregt, Jakob Wallinga, Fausto Guzzetti, Francesca Ardizzone. Dynamic path dependent landslide susceptibility modelling. . 2019; 2019 ():1-20.

Chicago/Turabian Style

Jalal Samia; Arnaud Temme; Arnold Bregt; Jakob Wallinga; Fausto Guzzetti; Francesca Ardizzone. 2019. "Dynamic path dependent landslide susceptibility modelling." 2019, no. : 1-20.

Science
Published: 14 February 2019 in Journal of Maps
Reads 0
Downloads 0

A 1:5,000 scale geological map and 31 geological cross-sections are presented for the surroundings of Amatrice village (central Apennines, Italy), epicentral area of the first damaging earthquake of the 2016–2017 seismic sequence. This detailed geological dataset focuses on: (i) the extent, the thickness, and the internal stratigraphic architecture of the Quaternary continental deposits; (ii) the bedding and the thickness of the Miocene substratum; and (iii) the spatial distribution of the main fault systems. The provided dataset would update the available regional geological maps in deciphering the syn-to-post-orogenic history of the Amatrice Basin. Eventually, the accuracy of the geological mapping would represent a basic tool for interpreting and integrating the multidisciplinary dataset deriving from post-seismic activities.

ACS Style

G. Vignaroli; M. Mancini; F. Bucci; M. Cardinali; Gianpaolo Cavinato; M. Moscatelli; M.L. Putignano; P. Sirianni; M. Santangelo; Francesca Ardizzone; G. Cosentino; C. Di Salvo; F. Fiorucci; I. Gaudiosi; S. Giallini; P. Messina; E. Peronace; F. Polpetta; P. Reichenbach; V. Scionti; M. Simionato; F. Stigliano. Geology of the central part of the Amatrice Basin (Central Apennines, Italy). Journal of Maps 2019, 15, 193 -202.

AMA Style

G. Vignaroli, M. Mancini, F. Bucci, M. Cardinali, Gianpaolo Cavinato, M. Moscatelli, M.L. Putignano, P. Sirianni, M. Santangelo, Francesca Ardizzone, G. Cosentino, C. Di Salvo, F. Fiorucci, I. Gaudiosi, S. Giallini, P. Messina, E. Peronace, F. Polpetta, P. Reichenbach, V. Scionti, M. Simionato, F. Stigliano. Geology of the central part of the Amatrice Basin (Central Apennines, Italy). Journal of Maps. 2019; 15 (2):193-202.

Chicago/Turabian Style

G. Vignaroli; M. Mancini; F. Bucci; M. Cardinali; Gianpaolo Cavinato; M. Moscatelli; M.L. Putignano; P. Sirianni; M. Santangelo; Francesca Ardizzone; G. Cosentino; C. Di Salvo; F. Fiorucci; I. Gaudiosi; S. Giallini; P. Messina; E. Peronace; F. Polpetta; P. Reichenbach; V. Scionti; M. Simionato; F. Stigliano. 2019. "Geology of the central part of the Amatrice Basin (Central Apennines, Italy)." Journal of Maps 15, no. 2: 193-202.

Technical note
Published: 22 October 2018 in Landslides
Reads 0
Downloads 0

Landslide inventory maps are commonly prepared through the visual interpretation of stereoscopic aerial photographs and field checks. Stereoscopic satellite images can also be interpreted visually to recognize and map landslides. When interpreting stereoscopic imagery, shadows can conceal the photographic elements typical of landslides, hampering the recognition and mapping of the landslides. To mitigate the problem, we propose a method that exploits normalized difference vegetation index (NDVI) images and digital stereoscopy for the 3D visual recognition and mapping of landslides in shadowed areas. We tested the method in the 25 km2 Pogliaschina catchment, northern Italy, where intense rainfall caused abundant landslides on 25 October 2011. Using a PLANAR® StereoMirror™ digital stereoscope, we prepared an event landslide inventory map (E-LIM) through the visual interpretation of a pair of NDVI images obtained from a WorldView-2 stereoscopic multispectral bundle. We compared the event inventory with two independent E-LIMs for the same area and landslide event. The 3D vision of the NDVI stereoscopic image pair maximized the use of the radiometric (color and tone) and the terrain (elevation, slope, relief, and convexity) information captured by the stereoscopic multispectral images, allowing for the recognition of more landslides and more landslide areas than the other E-LIMs in the shadowed areas. Our results confirm that use of NDVI images facilitates the visual recognition and mapping of landslides in terrain affected by shadows. We expect that the proposed method can help trained interpreters to map landslides more accurately in areas affected by shadows.

ACS Style

Federica Fiorucci; Francesca Ardizzone; Alessandro Cesare Mondini; Alessia Viero; Fausto Guzzetti. Visual interpretation of stereoscopic NDVI satellite images to map rainfall-induced landslides. Landslides 2018, 16, 165 -174.

AMA Style

Federica Fiorucci, Francesca Ardizzone, Alessandro Cesare Mondini, Alessia Viero, Fausto Guzzetti. Visual interpretation of stereoscopic NDVI satellite images to map rainfall-induced landslides. Landslides. 2018; 16 (1):165-174.

Chicago/Turabian Style

Federica Fiorucci; Francesca Ardizzone; Alessandro Cesare Mondini; Alessia Viero; Fausto Guzzetti. 2018. "Visual interpretation of stereoscopic NDVI satellite images to map rainfall-induced landslides." Landslides 16, no. 1: 165-174.

Original paper
Published: 15 June 2018 in Landslides
Reads 0
Downloads 0

Landslide susceptibility modelling—a crucial step towards the assessment of landslide hazard and risk—has hitherto not included the local, transient effects of previous landslides on susceptibility. In this contribution, we implement such transient effects, which we term “landslide path dependency”, for the first time. Two landslide path dependency variables are used to characterise transient effects: a variable reflecting how likely it is that an earlier landslide will have a follow-up landslide and a variable reflecting the decay of transient effects over time. These two landslide path dependency variables are considered in addition to a large set of conditioning attributes conventionally used in landslide susceptibility. Three logistic regression models were trained and tested fitted to landslide occurrence data from a multi-temporal landslide inventory: (1) a model with only conventional variables, (2) a model with conventional plus landslide path dependency variables, and (3) a model with only landslide path dependency variables. We compare the model performances, differences in the number, coefficient and significance of the selected variables, and the differences in the resulting susceptibility maps. Although the landslide path dependency variables are highly significant and have impacts on the importance of other variables, the performance of the models and the susceptibility maps do not substantially differ between conventional and conventional plus path dependent models. The path dependent landslide susceptibility model, with only two explanatory variables, has lower model performance, and differently patterned susceptibility map than the two other models. A simple landslide susceptibility model using only DEM-derived variables and landslide path dependency variables performs better than the path dependent landslide susceptibility model, and almost as well as the model with conventional plus landslide path dependency variables—while avoiding the need for hard-to-measure variables such as land use or lithology. Although the predictive power of landslide path dependency variables is lower than those of the most important conventional variables, our findings provide a clear incentive to further explore landslide path dependency effects and their potential role in landslide susceptibility modelling.

ACS Style

Jalal Samia; Arnaud Temme; Arnold K. Bregt; Jakob Wallinga; John Stuiver; Fausto Guzzetti; Francesca Ardizzone; Mauro Rossi. Implementing landslide path dependency in landslide susceptibility modelling. Landslides 2018, 15, 2129 -2144.

AMA Style

Jalal Samia, Arnaud Temme, Arnold K. Bregt, Jakob Wallinga, John Stuiver, Fausto Guzzetti, Francesca Ardizzone, Mauro Rossi. Implementing landslide path dependency in landslide susceptibility modelling. Landslides. 2018; 15 (11):2129-2144.

Chicago/Turabian Style

Jalal Samia; Arnaud Temme; Arnold K. Bregt; Jakob Wallinga; John Stuiver; Fausto Guzzetti; Francesca Ardizzone; Mauro Rossi. 2018. "Implementing landslide path dependency in landslide susceptibility modelling." Landslides 15, no. 11: 2129-2144.

Chapter
Published: 28 December 2017 in Landslide Dynamics: ISDR-ICL Landslide Interactive Teaching Tools
Reads 0
Downloads 0

In Italy rainfall-induced slope failures occur every year, claiming lives and causing severe economic disruptions. We have designed and implemented a warning system, named SANF (an acronym for national early warning system for rainfall-induced landslides), to forecast the possible occurrence of rainfall-induced landslides. The system is based on: (i) rainfall thresholds for possible landslide occurrence, (ii) sub-hourly rainfall measurements obtained by a nationwide network of 1950 rain gauges, and (iii) quantitative rainfall forecasts. All system components exploit Open Source software. Twice a day the system compares the measured and the forecasted rainfall amounts against pre-defined thresholds, and assigns to each rain gauge a probability of landslide occurrence. This information is used to prepare synoptic-scale maps showing where rainfall-induced landslides are expected. The system outputs are delivered to the National Civil Protection Authorities in different formats. Spatial outputs are published as standard OGC (Open Geospatial Consortium) web services (WMS, WFS, WCS) by the IRPI Spatial Data Infrastructure (IRPI SDI). A password protected WebGIS interface facilitates the use of the system by the Civil Protection personnel and gives access to current and past forecasts. In addition, bulletins containing the system information can be generated automatically and sent via e-mail to the Civil Protection personnel. In a more recent implementation, the system calculate hourly-based forecast using new regional rainfall thresholds and combine landslide forecasts with landslide susceptibility information available at synoptic scale in the national territory. Improvements of the validation procedures and of the landslide susceptibility layer are currently underway.

ACS Style

Mauro Rossi; Ivan Marchesini; Gabriele Tonelli; Silvia Peruccacci; Maria Teresa Brunetti; Silvia Luciani; Francesca Ardizzone; Vinicio Balducci; Cinzia Bianchi; Mauro Cardinali; Federica Fiorucci; Alessandro Cesare Mondini; Paola Reichenbach; Paola Salvati; Michele Santangelo; Fausto Guzzetti. TXT-tool 2.039-1.1 Italian National Early Warning System. Landslide Dynamics: ISDR-ICL Landslide Interactive Teaching Tools 2017, 341 -349.

AMA Style

Mauro Rossi, Ivan Marchesini, Gabriele Tonelli, Silvia Peruccacci, Maria Teresa Brunetti, Silvia Luciani, Francesca Ardizzone, Vinicio Balducci, Cinzia Bianchi, Mauro Cardinali, Federica Fiorucci, Alessandro Cesare Mondini, Paola Reichenbach, Paola Salvati, Michele Santangelo, Fausto Guzzetti. TXT-tool 2.039-1.1 Italian National Early Warning System. Landslide Dynamics: ISDR-ICL Landslide Interactive Teaching Tools. 2017; ():341-349.

Chicago/Turabian Style

Mauro Rossi; Ivan Marchesini; Gabriele Tonelli; Silvia Peruccacci; Maria Teresa Brunetti; Silvia Luciani; Francesca Ardizzone; Vinicio Balducci; Cinzia Bianchi; Mauro Cardinali; Federica Fiorucci; Alessandro Cesare Mondini; Paola Reichenbach; Paola Salvati; Michele Santangelo; Fausto Guzzetti. 2017. "TXT-tool 2.039-1.1 Italian National Early Warning System." Landslide Dynamics: ISDR-ICL Landslide Interactive Teaching Tools , no. : 341-349.

Chapter
Published: 28 December 2017 in Landslide Dynamics: ISDR-ICL Landslide Interactive Teaching Tools
Reads 0
Downloads 0

Landslides are common phenomena in mountainous countries, and play an important role in the evolution of landscapes. They also represent a serious hazard in many areas of the world. Acquiring systematic information on the type, abundance, and distribution of landslides, and preparing landslide inventory maps is of fundamental importance to mitigate landslide risk. Landslide inventory maps are essential for evaluating landslide hazard, vulnerability and risk, and for studying the evolution of landscapes dominated by mass-wasting processes. Landslide maps, including geomorphological, event, seasonal, and multi-temporal inventory maps, can be prepared using different techniques. We present the results of an experiment aiming at testing the possibility of using very high resolution, stereoscopic satellite images to map rainfall-induced shallow landslides. Three landslide inventory maps were prepared for the Collazzone study area, Umbria, Italy. Two of the maps were prepared through the visual interpretation of stereoscopic satellite images, and cover the periods January–March 2010, and March–May 2010. The third inventory map shows landslides occurred in the period January–March 2010, and was obtained through reconnaissance field surveys. We describe the statistics of landslide area for the three inventories, and compare quantitatively two of the landslide maps.

ACS Style

Francesca Ardizzone; Federica Fiorucci; Alessandro Cesare Mondini; Fausto Guzzetti. TXT-tool 1.039-1.1: Very-High Resolution Stereo Satellite Images for Landslide Mapping. Landslide Dynamics: ISDR-ICL Landslide Interactive Teaching Tools 2017, 83 -94.

AMA Style

Francesca Ardizzone, Federica Fiorucci, Alessandro Cesare Mondini, Fausto Guzzetti. TXT-tool 1.039-1.1: Very-High Resolution Stereo Satellite Images for Landslide Mapping. Landslide Dynamics: ISDR-ICL Landslide Interactive Teaching Tools. 2017; ():83-94.

Chicago/Turabian Style

Francesca Ardizzone; Federica Fiorucci; Alessandro Cesare Mondini; Fausto Guzzetti. 2017. "TXT-tool 1.039-1.1: Very-High Resolution Stereo Satellite Images for Landslide Mapping." Landslide Dynamics: ISDR-ICL Landslide Interactive Teaching Tools , no. : 83-94.

Journal article
Published: 01 September 2017 in Geomorphology
Reads 0
Downloads 0
ACS Style

Jalal Samia; Arnaud Temme; Arnold Bregt; Jakob Wallinga; Fausto Guzzetti; Francesca Ardizzone; Mauro Rossi. Characterization and quantification of path dependency in landslide susceptibility. Geomorphology 2017, 292, 16 -24.

AMA Style

Jalal Samia, Arnaud Temme, Arnold Bregt, Jakob Wallinga, Fausto Guzzetti, Francesca Ardizzone, Mauro Rossi. Characterization and quantification of path dependency in landslide susceptibility. Geomorphology. 2017; 292 ():16-24.

Chicago/Turabian Style

Jalal Samia; Arnaud Temme; Arnold Bregt; Jakob Wallinga; Fausto Guzzetti; Francesca Ardizzone; Mauro Rossi. 2017. "Characterization and quantification of path dependency in landslide susceptibility." Geomorphology 292, no. : 16-24.

Article
Published: 01 July 2017 in Journal of Mountain Science
Reads 0
Downloads 0

In this paper, an attempt to analyse landslide hazard and vulnerability in the municipality of Pahuatlán, Puebla, Mexico, is presented. In order to estimate landslide hazard, the susceptibility, magnitude (area-velocity ratio) and landslide frequency of the area of interest were produced based on information derived from a geomorphological landslide inventory; the latter was generated by using very high resolution satellite stereo pairs along with information derived from other sources (Google Earth, aerial photographs and historical information). Estimations of landslide susceptibility were determined by combining four statistical techniques: (i) logistic regression, (ii) quadratic discriminant analysis, (iii) linear discriminant analysis, and (iv) neuronal networks. A Digital Elevation Model (DEM) of 10 m spatial resolution was used to extract the slope angle, aspect, curvature, elevation and relief. These factors, in addition to land cover, lithology and distance to faults, were used as explanatory variables for the susceptibility models. Additionally, a Poisson model was used to estimate landslide temporal frequency, at the same time as landslide magnitude was obtained by using the relationship between landslide area and the velocity of movements. Then, due to the complexity of evaluating it, vulnerability of population was analysed by applying the Spatial Approach to Vulnerability Assessment (SAVE) model which considered levels of exposure, sensitivity and lack of resilience. Results were expressed on maps on which different spatial patterns of levels of landslide hazard and vulnerability were found for the inhabited areas. It is noteworthy that the lack of optimal methodologies to estimate and quantify vulnerability is more notorious than that of hazard assessments. Consequently, levels of uncertainty linked to landslide risk assessment remain a challenge to be addressed.

ACS Style

Franny G. Murillo-García; Mauro Rossi; Francesca Ardizzone; Federica Fiorucci; Irasema Alcántara-Ayala. Hazard and population vulnerability analysis: a step towards landslide risk assessment. Journal of Mountain Science 2017, 14, 1241 -1261.

AMA Style

Franny G. Murillo-García, Mauro Rossi, Francesca Ardizzone, Federica Fiorucci, Irasema Alcántara-Ayala. Hazard and population vulnerability analysis: a step towards landslide risk assessment. Journal of Mountain Science. 2017; 14 (7):1241-1261.

Chicago/Turabian Style

Franny G. Murillo-García; Mauro Rossi; Francesca Ardizzone; Federica Fiorucci; Irasema Alcántara-Ayala. 2017. "Hazard and population vulnerability analysis: a step towards landslide risk assessment." Journal of Mountain Science 14, no. 7: 1241-1261.

Technical note
Published: 25 May 2017 in Landslides
Reads 0
Downloads 0

Despite abundant information on landslides, and on landslide hazard and risk, in Italy, little is known on the direct impact of event landslides on road networks and on the related economic costs. We investigated the physical and economic damage caused by two rainfall-induced landslide events in Central and Southern Italy, to obtain road restoration cost statistics. Using a GIS-based method, we exploited road maps and landslide event inventory maps to compute different metrics that quantify the impact of the landslide events on the natural landscape and on the road networks, by road type. The maps were used with cost data obtained from multiple sources, including local authorities, and specific legislation, to evaluate statistically the unit cost per metre of damaged road and the unit cost per square metre of damaging landslide, separately for main and secondary roads. The obtained unit costs showed large variations which we attribute to the different road types in the two study areas and to the different abundance of landslides. Our work confirms the long-standing conundrum of obtaining accurate landslide damage data and outlines the need for reliable, standardized methods to evaluate landslide damage and associated restoration costs that regional and local administrations can use rapidly in the aftermath of a landslide event. We conclude recommending that common standardized procedures to collect landslide cost data following each landslide event are established, in Italy and elsewhere. This will allow for more accurate and reliable evaluations of the economic costs of landslide events.

ACS Style

Marco Donnini; Elisabetta Napolitano; Paola Salvati; Francesca Ardizzone; Francesco Bucci; Federica Fiorucci; Michele Santangelo; Mauro Cardinali; Fausto Guzzetti. Impact of event landslides on road networks: a statistical analysis of two Italian case studies. Landslides 2017, 14, 1521 -1535.

AMA Style

Marco Donnini, Elisabetta Napolitano, Paola Salvati, Francesca Ardizzone, Francesco Bucci, Federica Fiorucci, Michele Santangelo, Mauro Cardinali, Fausto Guzzetti. Impact of event landslides on road networks: a statistical analysis of two Italian case studies. Landslides. 2017; 14 (4):1521-1535.

Chicago/Turabian Style

Marco Donnini; Elisabetta Napolitano; Paola Salvati; Francesca Ardizzone; Francesco Bucci; Federica Fiorucci; Michele Santangelo; Mauro Cardinali; Fausto Guzzetti. 2017. "Impact of event landslides on road networks: a statistical analysis of two Italian case studies." Landslides 14, no. 4: 1521-1535.

Journal article
Published: 01 February 2017 in Geomorphology
Reads 0
Downloads 0
ACS Style

Matthias Vanmaercke; Francesca Ardizzone; Mauro Rossi; Fausto Guzzetti. Exploring the effects of seismicity on landslides and catchment sediment yield: An Italian case study. Geomorphology 2017, 278, 171 -183.

AMA Style

Matthias Vanmaercke, Francesca Ardizzone, Mauro Rossi, Fausto Guzzetti. Exploring the effects of seismicity on landslides and catchment sediment yield: An Italian case study. Geomorphology. 2017; 278 ():171-183.

Chicago/Turabian Style

Matthias Vanmaercke; Francesca Ardizzone; Mauro Rossi; Fausto Guzzetti. 2017. "Exploring the effects of seismicity on landslides and catchment sediment yield: An Italian case study." Geomorphology 278, no. : 171-183.

Journal article
Published: 09 November 2016 in Geoscientific Model Development
Reads 0
Downloads 0

Automatic subdivision of landscapes into terrain units remains a challenge. Slope units are terrain units bounded by drainage and divide lines, but their use in hydrological and geomorphological studies is limited because of the lack of reliable software for their automatic delineation. We present the r.slopeunits software for the automatic delineation of slope units, given a digital elevation model and a few input parameters. We further propose an approach for the selection of optimal parameters controlling the terrain subdivision for landslide susceptibility modeling. We tested the software and the optimization approach in central Italy, where terrain, landslide, and geo-environmental information was available. The software was capable of capturing the variability of the landscape and partitioning the study area into slope units suited for landslide susceptibility modeling and zonation. We expect r.slopeunits to be used in different physiographical settings for the production of reliable and reproducible landslide susceptibility zonations.

ACS Style

Massimiliano Alvioli; Ivan Marchesini; Paola Reichenbach; Mauro Rossi; Francesca Ardizzone; Federica Fiorucci; Fausto Guzzetti. Automatic delineation of geomorphological slope units with r.slopeunits v1.0 and their optimization for landslide susceptibility modeling. Geoscientific Model Development 2016, 9, 3975 -3991.

AMA Style

Massimiliano Alvioli, Ivan Marchesini, Paola Reichenbach, Mauro Rossi, Francesca Ardizzone, Federica Fiorucci, Fausto Guzzetti. Automatic delineation of geomorphological slope units with r.slopeunits v1.0 and their optimization for landslide susceptibility modeling. Geoscientific Model Development. 2016; 9 (11):3975-3991.

Chicago/Turabian Style

Massimiliano Alvioli; Ivan Marchesini; Paola Reichenbach; Mauro Rossi; Francesca Ardizzone; Federica Fiorucci; Fausto Guzzetti. 2016. "Automatic delineation of geomorphological slope units with r.slopeunits v1.0 and their optimization for landslide susceptibility modeling." Geoscientific Model Development 9, no. 11: 3975-3991.

Journal article
Published: 20 October 2016 in Remote Sensing
Reads 0
Downloads 0

This paper presents a methodology taking advantage of the GPOD-SBAS service to study the surface deformation information over high mountain regions. Indeed, the application of the advanced DInSAR over the arduous regions represents a demanding task. We implemented an iterative selection procedure of the most suitable SAR images, aimed to preserve the largest number of SAR scenes, and the fine-tuning of several advanced configuration parameters. This method is aimed at minimizing the temporal decorrelation effects, principally due to snow cover, and maximizing the number of coherent targets and their spatial distribution. The methodology is applied to the Valle d’Aosta (VDA) region, Northern Italy, an alpine area characterized by high altitudes, complex morphology, and susceptibility to different mass wasting phenomena. The approach using GPOD-SBAS allows for the obtainment of mean deformation velocity maps and displacement time series relative to the time period from 1992 to 2000, relative to ESR-1/2, and from 2002 to 2010 for ASAR-Envisat. Our results demonstrate how the DInSAR application can obtain reliable information of ground displacement over time in these regions, and may represent a suitable instrument for natural hazards assessment.

ACS Style

Martina Cignetti; Andrea Manconi; Michele Manunta; Daniele Giordan; Claudio De Luca; Paolo Allasia; Francesca Ardizzone. Taking Advantage of the ESA G-POD Service to Study Ground Deformation Processes in High Mountain Areas: A Valle d’Aosta Case Study, Northern Italy. Remote Sensing 2016, 8, 852 .

AMA Style

Martina Cignetti, Andrea Manconi, Michele Manunta, Daniele Giordan, Claudio De Luca, Paolo Allasia, Francesca Ardizzone. Taking Advantage of the ESA G-POD Service to Study Ground Deformation Processes in High Mountain Areas: A Valle d’Aosta Case Study, Northern Italy. Remote Sensing. 2016; 8 (10):852.

Chicago/Turabian Style

Martina Cignetti; Andrea Manconi; Michele Manunta; Daniele Giordan; Claudio De Luca; Paolo Allasia; Francesca Ardizzone. 2016. "Taking Advantage of the ESA G-POD Service to Study Ground Deformation Processes in High Mountain Areas: A Valle d’Aosta Case Study, Northern Italy." Remote Sensing 8, no. 10: 852.

Original paper
Published: 29 July 2016 in Landslides
Reads 0
Downloads 0

Landslides are a major category of natural disasters, causing loss of lives, livelihoods and property. The critical roles played by triggering (such as extreme rainfall and earthquakes), and intrinsic factors (such as slope steepness, soil properties and lithology) have previously successfully been recognized and quantified using a variety of qualitative, quantitative and hybrid methods in a wide range of study sites. However, available data typically do not allow to investigate the effect that earlier landslides have on intrinsic factors and hence on follow-up landslides. Therefore, existing methods cannot account for the potentially complex susceptibility changes caused by landslide events. In this study, we used a substantially different alternative approach to shed light on the potential effect of earlier landslides using a multi-temporal dataset of landslide occurrence containing 17 time slices. Spatial overlap and the time interval between landslides play key roles in our work. We quantified the degree to which landslides preferentially occur in locations where landslides occurred previously, how long such an effect is noticeable, and how landslides are spatially associated over time. We also investigated whether overlap with previous landslides causes differences in landslide geometric properties. We found that overlap among landslides demonstrates a clear legacy effect (path dependency) that has influence on the landslide affected area. Landslides appear to cause greater susceptibility for follow-up landslides over a period of about 10 years. Follow-up landslides are on average larger and rounder than landslides that do not follow earlier slides. The effect of earlier landslides on follow-up landslides has implications for understanding of the landslides evolution and the assessment of landslide susceptibility.

ACS Style

Jalal Samia; Arnaud Temme; Arnold Bregt; Jakob Wallinga; Fausto Guzzetti; Francesca Ardizzone; Mauro Rossi. Do landslides follow landslides? Insights in path dependency from a multi-temporal landslide inventory. Landslides 2016, 14, 547 -558.

AMA Style

Jalal Samia, Arnaud Temme, Arnold Bregt, Jakob Wallinga, Fausto Guzzetti, Francesca Ardizzone, Mauro Rossi. Do landslides follow landslides? Insights in path dependency from a multi-temporal landslide inventory. Landslides. 2016; 14 (2):547-558.

Chicago/Turabian Style

Jalal Samia; Arnaud Temme; Arnold Bregt; Jakob Wallinga; Fausto Guzzetti; Francesca Ardizzone; Mauro Rossi. 2016. "Do landslides follow landslides? Insights in path dependency from a multi-temporal landslide inventory." Landslides 14, no. 2: 547-558.