Fabio Dell’Acqua
Biographic Data
| ID | 6932746 |
|---|---|
| NAME | Fabio Dell’Acqua |
| GIVEN NAMES | Fabio |
| FAMILY NAME | Dell’Acqua |
| SIGNATURE | DELL’ACQUA F |
| AFFILIATIONS | University of Pavia |
| ORCID | 0000-0002-0044-2998 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Integrated Remote Sensing and Machine Learning for Urban Air Temperature Assessment and Mapping in Highly Heterogeneous Environments
This paper investigates the prediction of urban air temperature (Tair) from satellite-derived land surface temperature (LST) in the complex urban and topographic environment of Yerevan, Armenia. Building on previous work that demonstrated the effectiveness of machine learning (ML) approaches for point-based Tair estimation using Partial Least-Squares Regression (PLSR) with multiple environmental variables, this study shifts the focus to the spati…
Extensive Exposure Mapping in Urban Areas through Deep Analysis of Street-Level Pictures for Floor Count Determination
In order for a risk assessment to deliver sensible results, exposure in the concerned area must be known or at least estimated in a reliable manner. Exposure estimation, though, may be tricky, especially in urban areas, where large-scale surveying is generally expensive and impractical; yet, it is in urban areas that most assets are at stake when a disaster strikes. Authoritative sources such as cadastral data and business records may not be read…
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Extensive Exposure Mapping in Urban Areas through Deep Analysis of Street-Level Pictures for Floor Count Determination
In order for a risk assessment to deliver sensible results, exposure in the concerned area must be known or at least estimated in a reliable manner. Exposure estimation, though, may be tricky, especially in urban areas, where large-scale surveying is generally expensive and impractical; yet, it is in urban areas that most assets are at stake when a disaster strikes. Authoritative sources such as cadastral data and business records may not be read…
Integrated Remote Sensing and Machine Learning for Urban Air Temperature Assessment and Mapping in Highly Heterogeneous Environments
This paper investigates the prediction of urban air temperature (Tair) from satellite-derived land surface temperature (LST) in the complex urban and topographic environment of Yerevan, Armenia. Building on previous work that demonstrated the effectiveness of machine learning (ML) approaches for point-based Tair estimation using Partial Least-Squares Regression (PLSR) with multiple environmental variables, this study shifts the focus to the spati…
3D city models (1 works) · Air temperature (1 works) · Artificial Intelligence (1 works) · Cadastre (1 works) · Cartography (1 works) · Computer Science (1 works) · Crowdsourcing (1 works) · Data mining (1 works) · Data science (1 works) · Flood Risk Assessment and Management (1 works)