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Lorenzo Nava

Senior Lecturer

King’s College London

United Kingdom

Research Interests

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Professors in United Kingdom

Articles (20)

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2026

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2023

Collaborators (8)

Filippo Catani

Prof.

University of Padova

ITALY

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Saman Ghaffarian

University College London

UNITED KINGDOM

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Miguel Ángel Fernández Torres

Universidad Carlos III de Madrid

SPAIN

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Michele Crosetto

Head of Geomatics Division

Centre Tecnologic De Telecomunicacions De Catalunya

SPAIN

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Ascanio Rosi

University of Padova

ITALY

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Oriol Monserrat

Senior Researcher

Centre Tecnologic De Telecomunicacions De Catalunya

SPAIN

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Maximillian Van Wyk de Vries

Asst. Prof in Natural Hazards

University of Cambridge

UNITED KINGDOM

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Mario Floris

University of Padua

ITALY

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Lorenzo Nava

Research Interests

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Articles (20)

A workflow to identify and monitor slow-moving landslides through spaceborne optical feature tracking

Hillslope memory of sequential earthquakes

Converting Raw Data Into Actionable Information: A topical review of artificial intelligence, machine learning, and digital twins in disaster management

Sentinel-1 SAR-based globally distributed co-seismic landslide detection by deep neural networks

Explainability can foster trust in artificial intelligence in geoscience

Towards automatic delineation of landslide source and runout

Introducing AI practitioners to international standards through online competitions

Mamba for Landslide Detection

Brief communication: AI-driven rapid landslide mapping following the 2024 Hualien earthquake in Taiwan

Displacement residuals reveal landslide regime shifts

Improving Ground Deformation Classification by Integrating InSAR Time Series With Geospatial Information

A globally distributed dataset of coseismic landslide mapping via multi-source high-resolution remote sensing images

Deformation evaluation and displacement forecasting of baishuihe landslide after stabilization based on continuous wavelet transform and deep learning

Artificial intelligence applications for landslide mapping and monitoring on EO data

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

HR-GLDD: a globally distributed dataset using generalized deep learning (DL) for rapid landslide mapping on high-resolution (HR) satellite imagery

InSAR time series and LSTM model to support early warning detection tools of ground instabilities: mining site case studies

Generating multi-temporal landslide inventories through a general deep transfer learning strategy using HR EO data

Classification of rock slope cavernous weathering on UAV photogrammetric point clouds

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

Collaborators (8)

Filippo Catani

Saman Ghaffarian

Miguel Ángel Fernández Torres

Michele Crosetto

Ascanio Rosi

Oriol Monserrat

Maximillian Van Wyk de Vries

Mario Floris

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