Articles | Volume 15, issue 7
https://doi.org/10.5194/essd-15-2863-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-2863-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
11 Jul 2023
Data description paper |
| 11 Jul 2023
| 11 Jul 2023
The ITAlian rainfall-induced LandslIdes CAtalogue, an extensive and accurate spatio-temporal catalogue of rainfall-induced landslides in Italy
Silvia Peruccacci
CORRESPONDING AUTHOR
Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Perugia, 06128, Italy
Stefano Luigi Gariano
Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Perugia, 06128, Italy
Massimo Melillo
Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Perugia, 06128, Italy
Monica Solimano
Agenzia Regionale per la Protezione dell'Ambiente Ligure, Genoa, 16149, Italy
Fausto Guzzetti
Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Perugia, 06128, Italy
Presidenza del Consiglio dei Ministri, Dipartimento della Protezione Civile, Rome, 00189, Italy
Maria Teresa Brunetti
Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Perugia, 06128, Italy
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M. Santangelo, I. Marchesini, F. Bucci, M. Cardinali, F. Fiorucci, and F. Guzzetti
Nat. Hazards Earth Syst. Sci., 15, 2111–2126, https://doi.org/10.5194/nhess-15-2111-2015, https://doi.org/10.5194/nhess-15-2111-2015, 2015
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In this work, we present a new semi-automatic procedure to prepare landslide inventory maps that uses GIS applications and tools for the digitization of photo-interpreted data. Results show that the new semi-automatic procedure proves more efficient for the production of landslide inventories and results in the production of more accurate maps, compared to the manual procedure. The presented work has potential consequences for multiple applications of landslide studies.
O. G. Terranova, S. L. Gariano, P. Iaquinta, and G. G. R. Iovine
Geosci. Model Dev., 8, 1955–1978, https://doi.org/10.5194/gmd-8-1955-2015, https://doi.org/10.5194/gmd-8-1955-2015, 2015
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A model for predicting the timing of activation of rainfall-induced landslides is presented. Calibration against real events is based on genetic algorithms, and provides a family of optimal solutions (kernels) that maximize a fitness function. Accordingly, a set of mobility functions is obtained through convolution with rainfall. Once properly validated, the model allows one to estimate future landslide activations in the same study area, by employing either recorded or forecasted rainfall.
M. Mergili, I. Marchesini, M. Alvioli, M. Metz, B. Schneider-Muntau, M. Rossi, and F. Guzzetti
Geosci. Model Dev., 7, 2969–2982, https://doi.org/10.5194/gmd-7-2969-2014, https://doi.org/10.5194/gmd-7-2969-2014, 2014
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The article deals with strategies to (i) reduce computation time and to (ii) appropriately account for uncertain input parameters when applying an open source GIS sliding surface model to estimate landslide susceptibility for a 90km² study area in central Italy. For (i), the area is split into a large number of tiles, enabling the exploitation of multi-processor computing environments. For (ii), the model is run with various parameter combinations to compute the slope failure probability.
P. Salvati, C. Bianchi, F. Fiorucci, P. Giostrella, I. Marchesini, and F. Guzzetti
Nat. Hazards Earth Syst. Sci., 14, 2589–2603, https://doi.org/10.5194/nhess-14-2589-2014, https://doi.org/10.5194/nhess-14-2589-2014, 2014
O. G. Terranova and S. L. Gariano
Nat. Hazards Earth Syst. Sci., 14, 2423–2434, https://doi.org/10.5194/nhess-14-2423-2014, https://doi.org/10.5194/nhess-14-2423-2014, 2014
G. Vessia, M. Parise, M. T. Brunetti, S. Peruccacci, M. Rossi, C. Vennari, and F. Guzzetti
Nat. Hazards Earth Syst. Sci., 14, 2399–2408, https://doi.org/10.5194/nhess-14-2399-2014, https://doi.org/10.5194/nhess-14-2399-2014, 2014
I. Marchesini, F. Ardizzone, M. Alvioli, M. Rossi, and F. Guzzetti
Nat. Hazards Earth Syst. Sci., 14, 2215–2231, https://doi.org/10.5194/nhess-14-2215-2014, https://doi.org/10.5194/nhess-14-2215-2014, 2014
B. Merz, J. Aerts, K. Arnbjerg-Nielsen, M. Baldi, A. Becker, A. Bichet, G. Blöschl, L. M. Bouwer, A. Brauer, F. Cioffi, J. M. Delgado, M. Gocht, F. Guzzetti, S. Harrigan, K. Hirschboeck, C. Kilsby, W. Kron, H.-H. Kwon, U. Lall, R. Merz, K. Nissen, P. Salvatti, T. Swierczynski, U. Ulbrich, A. Viglione, P. J. Ward, M. Weiler, B. Wilhelm, and M. Nied
Nat. Hazards Earth Syst. Sci., 14, 1921–1942, https://doi.org/10.5194/nhess-14-1921-2014, https://doi.org/10.5194/nhess-14-1921-2014, 2014
A. Manconi, F. Casu, F. Ardizzone, M. Bonano, M. Cardinali, C. De Luca, E. Gueguen, I. Marchesini, M. Parise, C. Vennari, R. Lanari, and F. Guzzetti
Nat. Hazards Earth Syst. Sci., 14, 1835–1841, https://doi.org/10.5194/nhess-14-1835-2014, https://doi.org/10.5194/nhess-14-1835-2014, 2014
A. C. Mondini, A. Viero, M. Cavalli, L. Marchi, G. Herrera, and F. Guzzetti
Nat. Hazards Earth Syst. Sci., 14, 1749–1759, https://doi.org/10.5194/nhess-14-1749-2014, https://doi.org/10.5194/nhess-14-1749-2014, 2014
S. Raia, M. Alvioli, M. Rossi, R. L. Baum, J. W. Godt, and F. Guzzetti
Geosci. Model Dev., 7, 495–514, https://doi.org/10.5194/gmd-7-495-2014, https://doi.org/10.5194/gmd-7-495-2014, 2014
C. Vennari, S. L. Gariano, L. Antronico, M. T. Brunetti, G. Iovine, S. Peruccacci, O. Terranova, and F. Guzzetti
Nat. Hazards Earth Syst. Sci., 14, 317–330, https://doi.org/10.5194/nhess-14-317-2014, https://doi.org/10.5194/nhess-14-317-2014, 2014
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Landslides occur often across the world, with the potential to cause significant damage. Although a substantial amount of research has been conducted on the mapping of landslides using remote-sensing data, gaps and uncertainties remain when developing models to be operational at the global scale. To address this issue, we present the High-Resolution Global landslide Detector Database (HR-GLDD) for landslide mapping with landslide instances from 10 different physiographical regions globally.
Eloi González-Esvertit, Juan Alcalde, and Enrique Gomez-Rivas
Earth Syst. Sci. Data, 15, 3131–3145, https://doi.org/10.5194/essd-15-3131-2023, https://doi.org/10.5194/essd-15-3131-2023, 2023
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Evaporites are, scientifically and economically, key rocks due to their unique geological features and value for industrial purposes. To compile and normalise the vast amount of information of evaporite structures in the Iberian Peninsula, we present the IESDB – the first comprehensive database of evaporite structures and their surrounding rocks in Spain and Portugal. The IESDB is free to use, open access, and can be accessed and downloaded through the interactive IESDB webpage.
Joana Cardoso-Fernandes, Douglas Santos, Cátia Rodrigues de Almeida, Alexandre Lima, Ana C. Teodoro, and GREENPEG project team
Earth Syst. Sci. Data, 15, 3111–3129, https://doi.org/10.5194/essd-15-3111-2023, https://doi.org/10.5194/essd-15-3111-2023, 2023
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GREENPEG aims to develop tools for pegmatite exploration and to enhance European databases, adding new data on pegmatite properties, such as the spectral signature. Samples comprise pegmatites and wall rocks from Austria, Ireland, Norway, Portugal, and Spain. A detailed description of the spectral database is presented as well as reflectance spectra, photographs, and absorption features. Its European scale comprises pegmatites with distinct characteristics, providing a reference for exploration.
Wartini Ng, Budiman Minasny, Alex McBratney, Patrice de Caritat, and John Wilford
Earth Syst. Sci. Data, 15, 2465–2482, https://doi.org/10.5194/essd-15-2465-2023, https://doi.org/10.5194/essd-15-2465-2023, 2023
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With a higher demand for lithium (Li), a better understanding of its concentration and spatial distribution is important to delineate potential anomalous areas. This study uses a framework that combines data from recent geochemical surveys and relevant environmental factors to predict and map Li content across Australia. The map shows high Li concentration around existing mines and other potentially anomalous Li areas. The same mapping principles can potentially be applied to other elements.
Hong-He Xu, Zhi-Bin Niu, Yan-Sen Chen, Xuan Ma, Xiao-Jing Tong, Yi-Tong Sun, Xiao-Yan Dong, Dan-Ni Fan, Shuang-Shuang Song, Yan-Yan Zhu, Ning Yang, and Qing Xia
Earth Syst. Sci. Data, 15, 2213–2221, https://doi.org/10.5194/essd-15-2213-2023, https://doi.org/10.5194/essd-15-2213-2023, 2023
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A multi-dimensional and integrated dataset of fossil specimens is described. The dataset potentially contributes to a range of scientific activities and provides easy access to and virtual examination of fossil specimens in a convenient and low-cost way. It will greatly benefit paleontology in research, teaching, and science communication.
Patrice de Caritat, Anthony Dosseto, and Florian Dux
Earth Syst. Sci. Data, 15, 1655–1673, https://doi.org/10.5194/essd-15-1655-2023, https://doi.org/10.5194/essd-15-1655-2023, 2023
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This new, extensive (~1.5×106 km2) dataset from northern Australia contributes considerable new information on Australia's strontium (Sr) isotope coverage. The data are discussed in terms of lithology and age of the source areas. This dataset will reduce Northern Hemisphere bias in future global Sr isotope models. Other potential applications of the new data include mineral exploration, hydrology, food tracing, dust provenancing, and examining historic migrations of people and animals.
Samuel W. Scott, Léa Lévy, Cari Covell, Hjalti Franzson, Benoit Gibert, Ágúst Valfells, Juliet Newson, Julia Frolova, Egill Júlíusson, and María Sigríður Guðjónsdóttir
Earth Syst. Sci. Data, 15, 1165–1195, https://doi.org/10.5194/essd-15-1165-2023, https://doi.org/10.5194/essd-15-1165-2023, 2023
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Rock properties such as porosity and permeability play an important role in many geological processes. The Valgarður database is a compilation of petrophysical, geochemical, and mineralogical observations on more than 1000 Icelandic rock samples. In addition to helping constrain numerical models and geophysical inversions, these data can be used to better understand the interrelationship between lithology, hydrothermal alteration, and petrophysical properties.
Giuseppe Esposito and Fabio Matano
Earth Syst. Sci. Data, 15, 1133–1149, https://doi.org/10.5194/essd-15-1133-2023, https://doi.org/10.5194/essd-15-1133-2023, 2023
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In the highly urbanized volcanic area of Campi Flegrei (southern Italy), more than 500 000 people are exposed to multi-hazard conditions, including landslides. In the 1828–2017 time span, more than 2000 mass movements affected the volcanic slopes, concentrated mostly along the coastal sector. Rapid rock failures and flow-like landslides are frequent in the whole area. Besides their relevant role in modeling the landscape of Campi Flegrei, these processes also pose a societal risk.
Peter Stimmler, Mathias Goeckede, Bo Elberling, Susan Natali, Peter Kuhry, Nia Perron, Fabrice Lacroix, Gustaf Hugelius, Oliver Sonnentag, Jens Strauss, Christina Minions, Michael Sommer, and Jörg Schaller
Earth Syst. Sci. Data, 15, 1059–1075, https://doi.org/10.5194/essd-15-1059-2023, https://doi.org/10.5194/essd-15-1059-2023, 2023
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Arctic soils store large amounts of carbon and nutrients. The availability of nutrients, such as silicon, calcium, iron, aluminum, phosphorus, and amorphous silica, is crucial to understand future carbon fluxes in the Arctic. Here, we provide, for the first time, a unique dataset of the availability of the abovementioned nutrients for the different soil layers, including the currently frozen permafrost layer. We relate these data to several geographical and geological parameters.
Francesca Ardizzone, Francesco Bucci, Mauro Cardinali, Federica Fiorucci, Luca Pisano, Michele Santangelo, and Veronica Zumpano
Earth Syst. Sci. Data, 15, 753–767, https://doi.org/10.5194/essd-15-753-2023, https://doi.org/10.5194/essd-15-753-2023, 2023
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This paper presents a new geomorphological landslide inventory map for the Daunia Apennines, southern Italy. It was produced through the interpretation of two sets of stereoscopic aerial photographs, taken in 1954/55 and 2003, and targeted field checks. The inventory contains 17 437 landslides classified according to relative age, type of movement, and estimated depth. The dataset consists of a digital archive publicly available at https://doi.org/10.1594/PANGAEA.942427.
Zhaohui Pan, Zhibin Niu, Zumin Xian, and Min Zhu
Earth Syst. Sci. Data, 15, 41–51, https://doi.org/10.5194/essd-15-41-2023, https://doi.org/10.5194/essd-15-41-2023, 2023
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Antiarch placoderms, the most basal jawed vertebrates, have the potential to enlighten the origin of the last common ancestor of jawed vertebrates during the Paleozoic. This dataset, which was extracted manually from 142 published papers or books from 1939 to 2021, consists of 60 genera of 6025 specimens from the Ludfordian to the Famennian, covering all antiarch lineages. We transferred the unstructured data from the literature to structured data for further detailed research.
Zhiheng Du, Jiao Yang, Lei Wang, Ninglian Wang, Anders Svensson, Zhen Zhang, Xiangyu Ma, Yaping Liu, Shimeng Wang, Jianzhong Xu, and Cunde Xiao
Earth Syst. Sci. Data, 14, 5349–5365, https://doi.org/10.5194/essd-14-5349-2022, https://doi.org/10.5194/essd-14-5349-2022, 2022
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A dataset of the radiogenic strontium and neodymium isotopic compositions from the three poles (the third pole, the Arctic, and Antarctica) were integrated to obtain new findings. The dataset enables us to map the standardized locations in the three poles, while the use of sorting criteria related to the sample type permits us to trace the dust sources and sinks. The purpose of this dataset is to try to determine the variable transport pathways of dust at three poles.
Yutian Ke, Damien Calmels, Julien Bouchez, and Cécile Quantin
Earth Syst. Sci. Data, 14, 4743–4755, https://doi.org/10.5194/essd-14-4743-2022, https://doi.org/10.5194/essd-14-4743-2022, 2022
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In this paper, we introduce the largest and most comprehensive database for riverine particulate organic carbon carried by suspended particulate matter in Earth's fluvial systems: 3546 data entries for suspended particulate matter with detailed geochemical parameters are included, and special attention goes to the elemental and isotopic carbon compositions to better understand riverine particulate organic carbon and its role in the carbon cycle from regional to global scales.
Egor Zelenin, Dmitry Bachmanov, Sofya Garipova, Vladimir Trifonov, and Andrey Kozhurin
Earth Syst. Sci. Data, 14, 4489–4503, https://doi.org/10.5194/essd-14-4489-2022, https://doi.org/10.5194/essd-14-4489-2022, 2022
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Active faults are faults in the Earth's crust that could experience a possible future slip. A slip at the fault would cause an earthquake; thus, this draws particular attention to active faults in tectonic studies and seismic hazard assessment. We present the Active Faults of Eurasia Database (AFEAD): a high-detail continental-scale geodatabase comprising ~48 000 faults. The location, name, slip characteristics, and a reference to source publications are provided for database entries.
Patrice de Caritat, Anthony Dosseto, and Florian Dux
Earth Syst. Sci. Data, 14, 4271–4286, https://doi.org/10.5194/essd-14-4271-2022, https://doi.org/10.5194/essd-14-4271-2022, 2022
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Strontium isotopes are useful in geological, environmental, archaeological, and forensic research to constrain or identify the source of materials such as minerals, artefacts, or foodstuffs. A new dataset, contributing significant new data and knowledge to Australia’s strontium isotope coverage, is presented from an area of over 500 000 km2 of inland southeastern Australia. Various source areas for the sediments are recognized, and both fluvial and aeolian transport processes identified.
Francesco Bucci, Michele Santangelo, Lorenzo Fongo, Massimiliano Alvioli, Mauro Cardinali, Laura Melelli, and Ivan Marchesini
Earth Syst. Sci. Data, 14, 4129–4151, https://doi.org/10.5194/essd-14-4129-2022, https://doi.org/10.5194/essd-14-4129-2022, 2022
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The paper describes a new lithological map of Italy at a scale of 1 : 100 000 obtained from classification of a digital database following compositional and geomechanical criteria. The map represents the national distribution of the lithological classes at high resolution. The outcomes of this study can be relevant for a wide range of applications, including statistical and physically based modelling of slope stability assessment and other geoenvironmental studies.
Zhuoxuan Xia, Lingcao Huang, Chengyan Fan, Shichao Jia, Zhanjun Lin, Lin Liu, Jing Luo, Fujun Niu, and Tingjun Zhang
Earth Syst. Sci. Data, 14, 3875–3887, https://doi.org/10.5194/essd-14-3875-2022, https://doi.org/10.5194/essd-14-3875-2022, 2022
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Retrogressive thaw slumps are slope failures resulting from abrupt permafrost thaw, and are widely distributed along the Qinghai–Tibet Engineering Corridor. The potential damage to infrastructure and carbon emission of thaw slumps motivated us to obtain an inventory of thaw slumps. We used a semi-automatic method to map 875 thaw slumps, filling the knowledge gap of thaw slump locations and providing key benchmarks for analysing the distribution features and quantifying spatio-temporal changes.
Peter Betlem, Thomas Birchall, Gareth Lord, Simon Oldfield, Lise Nakken, Kei Ogata, and Kim Senger
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-143, https://doi.org/10.5194/essd-2022-143, 2022
Revised manuscript accepted for ESSD
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We present the digitization (i.e., textured outcrop and terrain models) of the Agardhfjellet Formation cliffs exposed in Konusdalen West, Svalbard. The formation forms the seal of a carbon capture site in Longyearbyen, where several boreholes cover the exposed interval. The outcrop data feature cm-scale accuracies, a maximum resolutions of 8 mm, and have been correlated with the boreholes through structural-stratigraphic annotations that form the basis for various numerical modelling scenarios.
Alexandru T. Codilean, Henry Munack, Wanchese M. Saktura, Tim J. Cohen, Zenobia Jacobs, Sean Ulm, Paul P. Hesse, Jakob Heyman, Katharina J. Peters, Alan N. Williams, Rosaria B. K. Saktura, Xue Rui, Kai Chishiro-Dennelly, and Adhish Panta
Earth Syst. Sci. Data, 14, 3695–3713, https://doi.org/10.5194/essd-14-3695-2022, https://doi.org/10.5194/essd-14-3695-2022, 2022
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OCTOPUS v.2 is a web-enabled database that allows users to visualise, query, and download cosmogenic radionuclide, luminescence, and radiocarbon ages and denudation rates associated with erosional landscapes, Quaternary depositional landforms, and archaeological records, along with ancillary geospatial data layers. OCTOPUS v.2 hosts five major data collections. Supporting data are comprehensive and include bibliographic, contextual, and sample-preparation- and measurement-related information.
Gregor Luetzenburg, Kristian Svennevig, Anders A. Bjørk, Marie Keiding, and Aart Kroon
Earth Syst. Sci. Data, 14, 3157–3165, https://doi.org/10.5194/essd-14-3157-2022, https://doi.org/10.5194/essd-14-3157-2022, 2022
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We produced the first landslide inventory for Denmark. Over 3200 landslides were mapped using a high-resolution elevation model and orthophotos. We implemented an independent validation into our mapping and found an overall level of completeness of 87 %. The national inventory represents a range of landslide sizes covering all regions that were covered by glacial ice during the last glacial period. This inventory will be used for investigating landslide causes and for natural hazard mitigation.
Cited articles
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The Swiss flood and landslide damage database: Normalisation and trends, J. Flood Risk Manag., 12, e12510, https://doi.org/10.1111/jfr3.12510, 2019.
Belair, G. M., Jones, E. S., Slaughter, S. L., and Mirus, B. B.:
Landslide Inventories across the United States version 2, Geological Survey data release, https://doi.org/10.5066/P9FZUX6N, 2022.
Berti, M., Martina, M. L. V., Franceschini, S., Pignone, S., Simoni, A., and Pizziolo, M.:
Probabilistic rainfall thresholds for landslide occurrence using a Bayesian approach, J. Geophys. Res.-Earth, 117, F04006, https://doi.org/10.1029/2012JF002367, 2012.
Bianchi, C. and Salvati, P.:
Rapporto Periodico sul Rischio posto alla Popolazione italiana da Frane e Inondazioni. Anno 2022, Istituto di Ricerca per la Protezione Idrogeologica (IRPI), Consiglio Nazionale delle Ricerche (CNR), https://doi.org/10.30437/REPORT2021, 2023 (in Italian).
Bíl, M., Raška, P., Dolák, L., and Kubeček, J.:
CHILDA – Czech Historical Landslide Database, Nat. Hazards Earth Syst. Sci., 21, 2581–2596, https://doi.org/10.5194/nhess-21-2581-2021, 2021.
Brunetti, M. T., Melillo, M., Gariano, S. L., Guzzetti, F., Bartolini, D., Brutti, F., Bianchi, C., Calzolari, C., Denti, B., Gioia, E., Luciani, S., Martinotti, M. E., Palladino, M. R., Pisano, L., Roccati, A., Solimano, M., Vennari, C., Vessia, G., Viero, A., and Peruccacci, S.:
ITALICA (ITAlian rainfall-induced LandslIdes CAtalogue), Zenodo [data set], https://doi.org/10.5281/zenodo.8009366, 2023.
Calvello, M. and Pecoraro, G.:
FraneItalia: a catalog of recent Italian landslides, Geoenvironmental Disasters, 5, 13, https://doi.org/10.1186/s40677-018-0105-5, 2018.
Corominas, J., Einstein, H., Davis, T., Strom, A., Zuccaro, G., Nadim, F., and Verdel, T.:
Glossary of Terms on Landslide Hazard and Risk, in: Engineering Geology for Society and Territory – Volume 2, edited by: Lollino, G., Giordan, D., Crosta, G. B., Corominas, J., Azzam, R., Wasowski, J., and Sciarra, N., Springer International Publishing, Cham, 1775–1779, https://doi.org/10.1007/978-3-319-09057-3_314, 2015.
Cruden, D. and Varnes, D.:
Landslide Types and Processes, Chapter 3 in Landslides: Investigation and Mitigation. Special Report 247, National Research Council, Spec. Rep. Natl. Res. Counc. Transp. Res. Board, Washington, DC, 36–75, 1996.
Damm, B. and Klose, M.:
Landslide Database for the Federal Republic of Germany: A Tool for Analysis of Mass Movement Processes, in: Landslide Science for a Safer Geoenvironment, edited by: Sassa, K., Canuti, P., and Yin, Y., Springer Cham, 787–792, https://doi.org/10.1007/978-3-319-05050-8_121, 2014.
Damm, B. and Klose, M.:
The landslide database for Germany: Closing the gap at national level, Geomorphology, 249, 82–93, https://doi.org/10.1016/j.geomorph.2015.03.021, 2015.
Devoli, G., Strauch, W., Chávez, G., and Høeg, K.:
A landslide database for Nicaragua: a tool for landslide-hazard management, Landslides, 4, 163–176, https://doi.org/10.1007/s10346-006-0074-8, 2007.
Fioravanti, G., Fraschetti, P., Lena, F., Perconti, W., Piervitali, E.:
I normali climatici 1991–2020 di temperatura e precipitazione in Italia, Stato dell'Ambiente 99/2022, ISPRA, Rome, Italy, ISBN 978-88-448-1120-4, 2022 (in Italian).
Foster, C., Pennington, C. V. L., Culshaw, M. G., and Lawrie, K.:
The national landslide database of Great Britain: development, evolution and applications, Environ. Earth Sci., 66, 941–953, https://doi.org/10.1007/s12665-011-1304-5, 2012.
Franceschini, R., Rosi, A., Catani, F., and Casagli, N.:
Exploring a landslide inventory created by automated web data mining: the case of Italy, Landslides, 19, 841–853, https://doi.org/10.1007/s10346-021-01799-y, 2022a.
Franceschini, R., Rosi, A., del Soldato, M., Catani, F., and Casagli, N.:
Integrating multiple information sources for landslide hazard assessment: the case of Italy, Sci. Rep., 12, 20724, https://doi.org/10.1038/s41598-022-23577-z, 2022b.
Froude, M. J. and Petley, D. N.:
Global fatal landslide occurrence from 2004 to 2016, Nat. Hazards Earth Syst. Sci., 18, 2161–2181, https://doi.org/10.5194/nhess-18-2161-2018, 2018.
Guzzetti, F.:
Landslide fatalities and the evaluation of landslide risk in Italy, Eng. Geol., 58, 89–107, https://doi.org/10.1016/S0013-7952(00)00047-8, 2000.
Guzzetti, F. and Tonelli, G.:
Information system on hydrological and geomorphological catastrophes in Italy (SICI): a tool for managing landslide and flood hazards, Nat. Hazards Earth Syst. Sci., 4, 213–232, https://doi.org/10.5194/nhess-4-213-2004, 2004.
Guzzetti, F., Cardinali, M., and Reichenbach, P.:
The AVI project: A bibliographical and archive inventory of landslides and floods in Italy, Environ. Manage., 18, 623–633, https://doi.org/10.1007/BF02400865, 1994.
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C. P.:
Rainfall thresholds for the initiation of landslides in central and southern Europe, Meteorol. Atmos. Phys., 98, 239–267, https://doi.org/10.1007/s00703-007-0262-7, 2007.
Guzzetti, F., Gariano, S. L., Peruccacci, S., Brunetti, M. T., Marchesini, I., Rossi, M., and Melillo, M.:
Geographical landslide early warning systems, Earth-Sci. Rev., 200, 102973, https://doi.org/10.1016/j.earscirev.2019.102973, 2020.
Guzzetti, F., Gariano, S. L., Peruccacci, S., Brunetti, M. T., and Melillo, M.:
Rainfall and landslide initiation, in: Rainfall, edited by: Morbidelli, R., Elsevier, 427–450, https://doi.org/10.1016/B978-0-12-822544-8.00012-3, 2022.
Haque, U., Blum, P., da Silva, P. F., Andersen, P., Pilz, J., Chalov, S. R., Malet, J.-P., Auflič, M. J., Andres, N., Poyiadji, E., Lamas, P. C., Zhang, W., Peshevski, I., Pétursson, H. G., Kurt, T., Dobrev, N., García-Davalillo, J. C., Halkia, M., Ferri, S., Gaprindashvili, G., Engström, J., and Keellings, D.:
Fatal landslides in Europe, Landslides, 13, 1545–1554, https://doi.org/10.1007/s10346-016-0689-3, 2016.
Herrera, G., Mateos, R. M., García-Davalillo, J. C., Grandjean, G., Poyiadji, E., Maftei, R., Filipciuc, T.-C., Jemec Auflič, M., Jež, J., Podolszki, L., Trigila, A., Iadanza, C., Raetzo, H., Kociu, A., Przyłucka, M., Kułak, M., Sheehy, M., Pellicer, X. M., McKeown, C., Ryan, G., Kopačková, V., Frei, M., Kuhn, D., Hermanns, R. L., Koulermou, N., Smith, C. A., Engdahl, M., Buxó, P., Gonzalez, M., Dashwood, C., Reeves, H., Cigna, F., Liščák, P., Pauditš, P., Mikulėnas, V., Demir, V., Raha, M., Quental, L., Sandić, C., Fusi, B., and Jensen, O. A.:
Landslide databases in the Geological Surveys of Europe, Landslides, 15, 359–379, https://doi.org/10.1007/s10346-017-0902-z, 2018.
Hess, J., Rickli, C., McArdell, B., and Stähli, M.:
Investigating and Managing Shallow Landslides in Switzerland, in: Landslide Science for a Safer Geoenvironment, edited by: Sassa, K., Canuti, P., and Yin, Y., Springer Cham, 805–808, https://doi.org/10.1007/978-3-319-05050-8_124, 2014.
Innocenzi, E., Greggio, L., Frattini, P., and de Amicis, M.:
A Web-Based Inventory of Landslides Occurred in Italy in the Period 2012–2015, in: Advancing Culture of Living with Landslides, edited by: Mikos, M., Tiwari, B., Yin, Y., and Sassa, K., Springer International Publishing, Cham, 1127–1133, https://doi.org/10.1007/978-3-319-53498-5_128, 2017.
Jaedicke, C., Lied, K., and Kronholm, K.:
Integrated database for rapid mass movements in Norway, Nat. Hazards Earth Syst. Sci., 9, 469–479, https://doi.org/10.5194/nhess-9-469-2009, 2009.
Kirschbaum, D., Stanley, T., and Zhou, Y.:
Spatial and temporal analysis of a global landslide catalog, Geomorphology, 249, 4–15, https://doi.org/10.1016/j.geomorph.2015.03.016, 2015.
Kirschbaum, D. B., Adler, R., Hong, Y., Hill, S., and Lerner-Lam, A.:
A global landslide catalog for hazard applications: method, results, and limitations, Nat. Hazards, 52, 561–575, https://doi.org/10.1007/s11069-009-9401-4, 2010.
Komac, M. and Hribernik, K.:
Slovenian national landslide database as a basis for statistical assessment of landslide phenomena in Slovenia, Geomorphology, 249, 94–102, https://doi.org/10.1016/j.geomorph.2015.02.005, 2015.
Luetzenburg, G., Svennevig, K., Bjørk, A. A., Keiding, M., and Kroon, A.:
A national landslide inventory for Denmark, Earth Syst. Sci. Data, 14, 3157–3165, https://doi.org/10.5194/essd-14-3157-2022, 2022.
Melillo, M., Brunetti, M. T., Peruccacci, S., Gariano, S. L., Roccati, A., and Guzzetti, F.:
A tool for the automatic calculation of rainfall thresholds for landslide occurrence, Environ. Model. Softw., 105, 230–243, https://doi.org/10.1016/j.envsoft.2018.03.024, 2018.
Mrozek, T., Kułak, M., Grabowski, D., and Wójcik, A.:
Landslide Counteracting System (SOPO): Inventory Database of Landslides in Poland, in: Landslide Science for a Safer Geoenvironment, edited by: Sassa, K., Canuti, P., and Yin, Y., Springer Cham, 815–820, https://doi.org/10.1007/978-3-319-05050-8_126, 2014.
Palladino, M. R., Viero, A., Turconi, L., Brunetti, M. T., Peruccacci, S., Melillo, M., Luino, F., Deganutti, A. M., and Guzzetti, F.:
Rainfall thresholds for the activation of shallow landslides in the Italian Alps: the role of environmental conditioning factors, Geomorphology, 303, 53–67, https://doi.org/10.1016/j.geomorph.2017.11.009, 2018.
Pennington, C., Freeborough, K., Dashwood, C., Dijkstra, T., and Lawrie, K.:
The National Landslide Database of Great Britain: Acquisition, communication and the role of social media, Geomorphology, 249, 44–51, https://doi.org/10.1016/j.geomorph.2015.03.013, 2015.
Peruccacci, S., Brunetti, M. T., Gariano, S. L., Melillo, M., Rossi, M., and Guzzetti, F.:
Rainfall thresholds for possible landslide occurrence in Italy, Geomorphology, 290, 39–57, https://doi.org/10.1016/j.geomorph.2017.03.031, 2017.
Rosser, B., Dellow, S., Haubrock, S., and Glassey, P.:
New Zealand's National Landslide Database, Landslides, 14, 1949–1959, https://doi.org/10.1007/s10346-017-0843-6, 2017.
Salvati, P., Bianchi, C., Rossi, M., and Guzzetti, F.:
Societal landslide and flood risk in Italy, Nat. Hazards Earth Syst. Sci., 10, 465–483, https://doi.org/10.5194/nhess-10-465-2010, 2010.
Salvati, P., Petrucci, O., Rossi, M., Bianchi, C., Pasqua, A. A., and Guzzetti, F.:
Gender, age and circumstances analysis of flood and landslide fatalities in Italy, Sci. Total Environ., 610–611, 867–879, https://doi.org/10.1016/j.scitotenv.2017.08.064, 2018.
Segoni, S., Rossi, G., Rosi, A., and Catani, F.:
Landslides triggered by rainfall: A semi-automated procedure to define consistent intensity–duration thresholds, Comput. Geosci., 63, 123–131, https://doi.org/10.1016/j.cageo.2013.10.009, 2014.
Segoni, S., Piciullo, L., and Gariano, S. L.:
A review of the recent literature on rainfall thresholds for landslide occurrence, Landslides, 15, 1483–1501, https://doi.org/10.1007/s10346-018-0966-4, 2018.
Trigila, A., Iadanza, C., and Spizzichino, D.:
Quality assessment of the Italian Landslide Inventory using GIS processing, Landslides, 7, 455–470, https://doi.org/10.1007/s10346-010-0213-0, 2010.
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Short summary
ITALICA (ITAlian rainfall-induced LandslIdes CAtalogue) is the largest catalogue of rainfall-induced landslides accurately located in space and time available in Italy. ITALICA currently lists 6312 landslides that occurred between January 1996 and December 2021. The information was collected using strict objective and homogeneous criteria. The high spatial and temporal accuracy makes the catalogue suitable for reliably defining the rainfall conditions capable of triggering future landslides.
ITALICA (ITAlian rainfall-induced LandslIdes CAtalogue) is the largest catalogue of...
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