Silvia Bianchini

About Silvia Bianchini

Silvia Bianchini, With an exceptional h-index of 35 and a recent h-index of 31 (since 2020), a distinguished researcher at Università degli Studi di Firenze, specializes in the field of Earth sciences, hydrogeology, geology, landslides, subsidence.

His recent articles reflect a diverse array of research interests and contributions to the field:

Semi-automatic analysis of InSAR large datasets for landslide mapping and monitoring: the Great Britain case study

Mapping and monitoring ground deformations: Insights from a Sentinel-1 Persistent Scatterer Interferometry study in Northeastern Italy

Sinkhole risk mapping and early warning: the case of Camaiore (Italy)

Sinkhole risk assessment by using machine learning model: the case study of Guidonia-Bagni di Tivoli plain (Rome), Italy

Machine learning model to assess the spatial probability of Sentinel-1 based deformation trend changes

The Potential of Satellite Interferometry for Geohazard Assessment in Cultural Heritage Sites

Advanced technologies for landslides—ATLaS (WCoE 2020–2023)

Machine learning for defining the probability of Sentinel-1 based deformation trend changes occurrence

Silvia Bianchini Information

University

Position

Earth Sciences Department Italy

Citations(all)

3538

Citations(since 2020)

2629

Cited By

2072

hIndex(all)

35

hIndex(since 2020)

31

i10Index(all)

54

i10Index(since 2020)

50

Email

University Profile Page

Google Scholar

Silvia Bianchini Skills & Research Interests

Earth sciences

hydrogeology

geology

landslides

subsidence

Top articles of Silvia Bianchini

Semi-automatic analysis of InSAR large datasets for landslide mapping and monitoring: the Great Britain case study

2024/3/7

Silvia Bianchini
Silvia Bianchini

H-Index: 27

Mapping and monitoring ground deformations: Insights from a Sentinel-1 Persistent Scatterer Interferometry study in Northeastern Italy

2024/3/7

Sinkhole risk mapping and early warning: the case of Camaiore (Italy)

Frontiers in Earth Science

2023/5/16

Sinkhole risk assessment by using machine learning model: the case study of Guidonia-Bagni di Tivoli plain (Rome), Italy

EGU General Assembly Conference Abstracts

2023/5

Machine learning model to assess the spatial probability of Sentinel-1 based deformation trend changes

EGU General Assembly Conference Abstracts

2023/5

The Potential of Satellite Interferometry for Geohazard Assessment in Cultural Heritage Sites

2023/2/11

Machine learning for defining the probability of Sentinel-1 based deformation trend changes occurrence

Remote Sensing

2022/4/5

Machine learning for sinkhole risk mapping in Guidonia-Bagni di Tivoli plain (Rome), Italy

Geocarto International

2022/12/13

Review of satellite radar interferometry for subsidence analysis

2022/12/1

Satellite Radar Interferometry for Monitoring Historic Urban Fabric: Lucca and Florence Test Cities

2022/5/16

Silvia Bianchini
Silvia Bianchini

H-Index: 27

Davide Festa
Davide Festa

H-Index: 0

Considerations on regional continuous Sentinel-1 monitoring services over three different regions

EGU General Assembly Conference Abstracts

2022/5

Shallow landslides and rockfalls velocity assessment at regional scale: a methodology based on a morphometric approach

Geosciences

2022/4/16

Sentinel-1-based monitoring services at regional scale in Italy: State of the art and main findings

2021/10/1

Integration of satellite interferometric data in civil protection strategies for landslide studies at a regional scale

Remote Sensing

2021/5/11

Silvia Bianchini
Silvia Bianchini

H-Index: 27

Filippo Catani
Filippo Catani

H-Index: 35

Review of works combining GNSS and InSAR in Europe

2021/4/27

Ground motion detection in a salt solution mining area, an application of Multi-Temporal Satellite Interferometry

EGU General Assembly Conference Abstracts

2021/4

Roberto Montalti
Roberto Montalti

H-Index: 5

Silvia Bianchini
Silvia Bianchini

H-Index: 27

From Sentinel-1 data processing to field survey: an operating workflow for the continuous monitoring of the Earth surface deformations

EGU General Assembly Conference Abstracts

2021/4

Linee Guida per il monitoraggio delle frane. Dei Cas L.; Trigila A.; Iadanza C.(eds)

2021

Correction to: From Satellite Images to Field Survey: A Complete Scheme of Landslide InSAR Monitoring

Understanding and Reducing Landslide Disaster Risk: Volume 2 From Mapping to Hazard and Risk Zonation 5th

2021

See List of Professors in Silvia Bianchini University(Università degli Studi di Firenze)