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Fatemeh Jalayer  - - - 
Top co-authors See all
G. Forte

351 shared publications

Center for Translational Medicine, International Clinical Research Center, St. Anne’s University Hospital, Czechia

Andrea Prota

116 shared publications

Full Professor, Dept. of Structures for Engineering and Architecture, Univ. of Napoli “Federico II”, via Claudio, 21, 80125 Napoli, Italy

Iunio Iervolino

79 shared publications

Dipartimento di Strutture per l’Ingegneria e l’Architettura, Università degli Studi di Napoli Federico II, Naples, Italy

Stephan Pauleit

67 shared publications

Strategic Landscape Planning and Management, Center of Life and Food Sciences Weihenstephan, Technical University of Munich, Emil-Ramann-Str. 6, 85354 Freising, Germany

Hikmet Sezen

66 shared publications

Elettra–Sincrotrone Trieste S.C.p.A., SS 14–Km 163.5 in Area Science Park, I-34149 Basovizza, Trieste, Italy

Publication Record
Distribution of Articles published per year 
(2002 - 2018)
Total number of journals
published in
Publications See all
PROCEEDINGS-ARTICLE 0 Reads 0 Citations Performance Based Assessment and Retrofit of Nonductile Existing Reinforced Concrete Structures Andrea Miano, Halil Sezen, Fatemeh Jalayer, Andrea Prota Published: 17 April 2018
Structures Conference 2018, doi: 10.1061/9780784481349.010
DOI See at publisher website
Article 0 Reads 1 Citation Cloud to IDA: Efficient fragility assessment with limited scaling Andrea Miano, Fatemeh Jalayer, Hossein Ebrahimian, Andrea Pr... Published: 26 December 2017
Earthquake Engineering & Structural Dynamics, doi: 10.1002/eqe.3009
DOI See at publisher website
Article 0 Reads 0 Citations Robust seismicity forecasting based on Bayesian parameter estimation for epidemiological spatio-temporal aftershock clus... Hossein Ebrahimian, Fatemeh Jalayer Published: 29 August 2017
Scientific Reports, doi: 10.1038/s41598-017-09962-z
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
In the immediate aftermath of a strong earthquake and in the presence of an ongoing aftershock sequence, scientific advisories in terms of seismicity forecasts play quite a crucial role in emergency decision-making and risk mitigation. Epidemic Type Aftershock Sequence (ETAS) models are frequently used for forecasting the spatio-temporal evolution of seismicity in the short-term. We propose robust forecasting of seismicity based on ETAS model, by exploiting the link between Bayesian inference and Markov Chain Monte Carlo Simulation. The methodology considers the uncertainty not only in the model parameters, conditioned on the available catalogue of events occurred before the forecasting interval, but also the uncertainty in the sequence of events that are going to happen during the forecasting interval. We demonstrate the methodology by retrospective early forecasting of seismicity associated with the 2016 Amatrice seismic sequence activities in central Italy. We provide robust spatio-temporal short-term seismicity forecasts with various time intervals in the first few days elapsed after each of the three main events within the sequence, which can predict the seismicity within plus/minus two standard deviations from the mean estimate within the few hours elapsed after the main event.
Article 0 Reads 1 Citation Delineation of flooding risk hotspots based on digital elevation model, calculated and historical flooding extents: the ... Raffaele De Risi, Fatemeh Jalayer, Francesco De Paola, Sarah... Published: 29 August 2017
Stochastic Environmental Research and Risk Assessment, doi: 10.1007/s00477-017-1450-8
DOI See at publisher website ABS Show/hide abstract
Delineation of flood risk hotspots can be considered as one of the first steps in an integrated methodology for urban flood risk management and mitigation. This paper presents a step-by-step methodology in a GIS-based framework for identifying flooding risk hotspots for residential buildings. This is done by overlaying a map of potentially flood-prone areas [estimated through the topographic wetness index (TWI)], a map of residential areas [extracted from a city-wide assessment of urban morphology types (UMT)], and a geo-spatial census dataset. The novelty of this paper consists in the fact that the flood-prone areas (the TWI thresholds) are identified through a maximum likelihood method (MLE) based both on inundation profiles calculated for a specific return period (TR), and on information about the extent of historical flooding in the area of interest. Furthermore, Bayesian parameter updating is employed in order to estimate the TWI threshold by employing the historical extent as prior information and the inundation map for calculating the likelihood function. For different statistics of the TWI threshold, the map of potentially flood-prone areas is overlaid with the map of residential urban morphology units in order to delineate the residential flooding risk urban hotspots. Overlaying the delineated urban hotspots with geo-spatial census datasets, the number of people affected by flooding is estimated. These kind of screening procedures are particularly useful for locations where there is a lack of detailed data or where it is difficult to perform accurate flood risk assessment. In fact, an application of the proposed procedure is demonstrated for the identification of urban flooding risk hotspots in the city of Ouagadougou, capital of Burkina Faso, a city for which the observed spatial extent of a major flood event in 2009 and a calculated inundation map for a return period of 300 years are both available.
Article 0 Reads 5 Citations Analytical fragility assessment using unscaled ground motion records Fatemeh Jalayer, Hossein Ebrahimian, Andrea Miano, Gaetano M... Published: 26 June 2017
Earthquake Engineering & Structural Dynamics, doi: 10.1002/eqe.2922
DOI See at publisher website
BOOK-CHAPTER 0 Reads 0 Citations The Role of the Precipitation History on Landslide Triggering in Unsaturated Pyroclastic Soils Luca Comegna, Melania De Falco, Fatemeh Jalayer, Luciano Pic... Published: 21 May 2017
Advancing Culture of Living with Landslides, doi: 10.1007/978-3-319-53485-5_35
DOI See at publisher website