Filippo Catani

Filippo Catani

Università degli Studi di Padova

H-index: 53

Europe-Italy

About Filippo Catani

Filippo Catani, With an exceptional h-index of 53 and a recent h-index of 43 (since 2020), a distinguished researcher at Università degli Studi di Padova, specializes in the field of Landslides, Engineering Geology, Machine Intelligence, Geomorphometry, Remote Sensing.

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

Modelling Uncertainties and Sensitivity Analysis of Landslide Susceptibility Prediction under Different Environmental Factor Connection Methods and Machine Learning Models

Identifying Heterogeneous Landslides using Multi-modal Deep Learning

Uncertainties of landslide susceptibility prediction: influences of different study area scales and mapping unit scales

Uncertainties in landslide susceptibility prediction: Influence rule of different levels of errors in landslide spatial position

Sentinel-1 SAR-based Globally Distributed Landslide Detection by Deep Neural Networks

Landslide Regime Shift Detector (LRSD) for Landslide Early Warning Systems

Landslide topology uncovers failure movements

Machine learning approaches for the assessment of ground instabilities. An overview of Return VS2 approach against existing literature

Filippo Catani Information

University

Position

Professor of Engineering Geology - Department of Geosciences - UNESCO Chair

Citations(all)

9799

Citations(since 2020)

6273

Cited By

5770

hIndex(all)

53

hIndex(since 2020)

43

i10Index(all)

96

i10Index(since 2020)

85

Email

University Profile Page

Università degli Studi di Padova

Google Scholar

View Google Scholar Profile

Filippo Catani Skills & Research Interests

Landslides

Engineering Geology

Machine Intelligence

Geomorphometry

Remote Sensing

Top articles of Filippo Catani

Title

Journal

Author(s)

Publication Date

Modelling Uncertainties and Sensitivity Analysis of Landslide Susceptibility Prediction under Different Environmental Factor Connection Methods and Machine Learning Models

KSCE Journal of Civil Engineering

Faming Huang

Haowen Xiong

Xiaoting Zhou

Filippo Catani

Jinsong Huang

2024/1

Identifying Heterogeneous Landslides using Multi-modal Deep Learning

Xiaochuan Tang

Xuanmei Fan

Filippo Catani

2024/3/7

Uncertainties of landslide susceptibility prediction: influences of different study area scales and mapping unit scales

Journal of Rock Mechanics and Geotechnical Engineering

Faming Huang

Zuokui Teng

Chi Yao

Shui-Hua Jiang

Filippo Catani

...

2024/1/1

Uncertainties in landslide susceptibility prediction: Influence rule of different levels of errors in landslide spatial position

Journal of Rock Mechanics and Geotechnical Engineering

Faming Huang

Ronghui Li

Filippo Catani

Xiaoting Zhou

Ziqiang Zeng

...

2024/3/6

Sentinel-1 SAR-based Globally Distributed Landslide Detection by Deep Neural Networks

Lorenzo Nava

Alessandro Cesare Mondini

Kushanav Bhuyan

Chengyong Fang

Oriol Monserrat

...

2024/4/5

Landslide Regime Shift Detector (LRSD) for Landslide Early Warning Systems

Lorenzo Nava

Antoinette Tordesillas

Guoqi Qian

Filippo Catani

2024/2/18

Landslide topology uncovers failure movements

arXiv preprint arXiv:2310.09631

Kamal Rana

Kushanav Bhuyan

Joaquin Vicente Ferrer

Fabrice Cotton

Ugur Ozturk

...

2023/10/14

Machine learning approaches for the assessment of ground instabilities. An overview of Return VS2 approach against existing literature

L Nava

F Catani

A Rosi

K Bhuyan

R Tufano

...

2024/2

Monitoring and forecasting subsurface geo-interfaces behavior of active slow-moving landslides using fiber optic nerve sensing system

Xiao Ye

Hong-Hu Zhu

Bin Shi

Filippo Catani

2024/3/7

Modelling landslide susceptibility prediction: A review and construction of semi-supervised imbalanced theory

Faming Huang

Haowen Xiong

Shui-Hua Jiang

Chi Yao

Xuanmei Fan

...

2024/1/29

Landsifier 2.0: Towards automating landslide trigger and failure movement identification

Lorenzo Nava

Kushanav Bhuyan

Manan Kapoor

Kamal Rana

Ascanio Rosi

...

2024/3/7

Landslide displacement forecasting using deep learning and monitoring data across selected sites

Landslides

Lorenzo Nava

Edoardo Carraro

Cristina Reyes-Carmona

Silvia Puliero

Kushanav Bhuyan

...

2023/10

Interaction between human activities and geo-environment for sustainable development

Xuanmei Fan

Xiaoyan Zhao

Xiangjun Pei

Filippo Catani

Yunhui Zhang

2023/3/2

Can AI-generated landslide inventories replace humans' cognitive abilities in hazard and risk scenarios?

EGU General Assembly Conference Abstracts

Sansar Raj Meena

Mario Floris

Filippo Catani

2023/5

An updating of landslide susceptibility prediction from the perspective of space and time

Geoscience Frontiers

Zhilu Chang

Faming Huang

Jinsong Huang

Shui-Hua Jiang

Yuting Liu

...

2023/9/1

Mapping landslides through a temporal lens: an insight toward multi-temporal landslide mapping using the u-net deep learning model

GIScience & Remote Sensing

Kushanav Bhuyan

Sansar Raj Meena

Lorenzo Nava

Cees van Westen

Mario Floris

...

2023/12/31

Sentinel-1 and Deep Learning for rapid landslide mapping

EGU General Assembly Conference Abstracts

Sansar Raj Meena

Lorenzo Nava

Kushanav Bhuyan

Oriol Monserrat

Filippo Catani

2023/5

Effects of roots cohesion on regional distributed slope stability modelling

Catena

Elena Benedetta Masi

Veronica Tofani

Guglielmo Rossi

Sabatino Cuomo

Wei Wu

...

2023/3/1

Earthquake-induced soil landslides: volume estimates and uncertainties with the existing scaling exponents

Scientific Reports

Ali P Yunus

Chen Xinyu

Filippo Catani

Srikrishnan Siva Subramaniam

Xuanmei Fan

...

2023/5/19

Spatial and Temporal Characterization of Landslide Deformation Pattern with Sentinel-1

Francesco Poggi

Roberto Montalti

Emanuele Intrieri

Alessandro Ferretti

Filippo Catani

...

2023/12/25

See List of Professors in Filippo Catani University(Università degli Studi di Padova)

Co-Authors

H-index: 103
Andrea Rinaldo

Andrea Rinaldo

École Polytechnique Fédérale de Lausanne

H-index: 75
Nicola Casagli

Nicola Casagli

Università degli Studi di Firenze

H-index: 31
Matteo Convertino, PhD Prof

Matteo Convertino, PhD Prof

Hokkaido University

H-index: 25
Ping Lu

Ping Lu

Tongji University

H-index: 24
ascanio rosi

ascanio rosi

Università degli Studi di Firenze

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