Alessia Goffi

Alessia Goffi

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10
Publications
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317
Citations

Publications

Publications (10)
Article
Full-text available
Background Since February 2020, the COVID-19 epidemic has rapidly spread throughout Italy. Some studies showed an association of environmental factors, such as PM10, PM2.5, NO2, temperature, relative humidity, wind speed, solar radiation and mobility with the spread of the epidemic. In this work, we aimed to predict via Deep Learning the real-time...
Article
Full-text available
The COVID-19 pandemic has sparked an intense debate about the hidden factors underlying the dynamics of the outbreak. Several computational models have been proposed to inform effective social and healthcare strategies. Crucially, the predictive validity of these models often depends upon incorporating behavioral and social responses to infection....
Article
After the appearance of COVID-19 in China last December 2019, Italy was the first European country to be severely affected by the outbreak. The first diagnosis in Italy was on February 20, 2020, followed by the establishment of a light and a tight lockdown on February 23 and on March 8, 2020, respectively. The virus spread rapidly, particularly in...
Preprint
The COVID-19 pandemic has sparked an intense debate about the factors underlying the dynamics of the outbreak. Mitigating virus spread could benefit from reliable predictive models that inform effective social and healthcare strategies. Crucially, the predictive validity of these models depends upon incorporating behavioral and social responses to...
Article
Full-text available
Background Italy's severe COVID-19 outbreak was addressed by a lockdown that gradually increased in space, time and intensity. The effectiveness of the lockdown has not been precisely assessed with respect to the intensity of mobility restriction and the time until the outbreak receded. Methods We used processed mobile phone tracking data to measu...
Article
Following the outbreak of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) last December 2019 in China, Italy was the first European country to be severely affected, with the first local case diagnosed on 20 February 2020. The virus spread quickly, particularly in the North of Italy, with three regions (Lombardy, Veneto and Emilia-Romag...
Article
Full-text available
The paper proposes a transparent approach for mapping the status of environmental phenomena from multisource information based on both soft computing and machine learning. It is transparent, intended as human understandable as far as the employed criteria, and both knowledge and data-driven. It exploits remote sensing experts’ interpretations to de...
Article
Full-text available
The paper proposes a scalable fuzzy approach for mapping the status of the environment integrating several distinct models exploiting geo big data. The process is structured into two phases: the first one can exploit products yielded by distinct models of remote sensing image interpretation defined in the scientific literature, and knowledge of dom...
Article
Full-text available
In this work we propose an approach for mapping flooded areas from Sentinel-2 MSI (Multispectral Instrument) data based on soft fuzzy integration of evidence scores derived from both band combinations (i.e. Spectral Indices - SIs) and components of the Hue, Saturation and Value (HSV) colour transformation. Evidence scores are integrated with Ordere...
Conference Paper
Full-text available
The Self-Reflection on their own work has always been present in all designers, including architects and planners. In the mid 80-90 Donald Schon has made more explicit this aspect, which until then had not found a systematic scientific treatment. The results of Schon are the basis of practical planning of the 90s period. However, the Schon's analy...

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Projects

Projects (2)
Project
The aim of EPICO19 project is to support public health technicians and decision makers in managing the COVID-19 pandemic in progress. EPICO19 is a tool designed as a Web based GIS (Geographic Information System) DSS (Decision Support System), led by an epidemiological modelling and a logistic engine that analyze and predict the historical and the real-time transmission of SARS-COV-2 virus at a local level, keeping into account spatio-temporal correlations. This project is funded by European Spatial Agency ESA (ESA Contract No. 4000131356/20/NL/AF).
Project
Reducing the uncertainties related to emission estimation compilation will lead to a better development, implementation and evaluation of air quality assessment, air quality plans and source apportionment in the framework of the Ambient Air Quality Directives. Provide the recommendations to support modelling groups in reducing modelling uncertainties related to emission processing. Provide operational guidelines concerning integration and harmonization of urban/regional emission inventory.