S
Stefano Tarantola
Researcher at Institute for the Protection and Security of the Citizen
Publications - 99
Citations - 21873
Stefano Tarantola is an academic researcher from Institute for the Protection and Security of the Citizen. The author has contributed to research in topics: Sensitivity (control systems) & Uncertainty analysis. The author has an hindex of 51, co-authored 99 publications receiving 19697 citations.
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Report SeriesDOI
Handbook on Constructing Composite Indicators: Methodology and User Guide
Michela Nardo,Michaela Saisana,Andrea Saltelli,Stefano Tarantola,Anders Hoffman,Enrico Giovannini +5 more
TL;DR: In this paper, the authors present a handbook for constructing and using composite indicators for policy makers, academics, the media and other interested parties, which is concerned with those which compare and rank country performance in areas such as industrial competitiveness, sustainable development, globalisation and innovation.
Book
Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models
TL;DR: In this paper, the authors present a method for sensitivity analysis of a fish population model using Monte Carlo filtering and variance-based methods, which is based on the Bayesian uncertainty estimation.
Journal ArticleDOI
Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index
Andrea Saltelli,Paola Annoni,Ivano Azzini,Francesca Campolongo,Marco Ratto,Stefano Tarantola +5 more
TL;DR: Existing and new practices for sensitivity analysis of model output are compared and recommendations on which to use are offered to help practitioners choose which techniques to use.
Journal ArticleDOI
A quantitative model-independent method for global sensitivity analysis of model output
TL;DR: In this paper, the Fourier amplitude sensitivity test (FAST) has been extended to include all the interaction terms involving a factor and the main effect of the factor's main effect.
Journal ArticleDOI
Detecting vegetation leaf water content using reflectance in the optical domain
TL;DR: In this paper, the authors investigated the potential and approaches for using optical remote sensing to assess vegetation water content at the leaf level using laboratory measurements, the radiative transfer model PROSPECT and a sensitivity analysis.