Lead Instructors : Fausto Guzzetti, Paola Salvati, Bruce Malamud
03
Workshop
From Sentinel-1 to NISAR: Opportunities, Limitations and Future Perspectives of Satellite SAR for Landslide Applications
Lead Instructors: Dr Oriol Monserrat Hernandez, Centro Tecnológico de Telecomunicaciones de Cataluña (CTTC)
04
Workshop
Hydrometeorological Thresholds and EWS Under Climate Change.
Lead Instructors : Dr Thom Bogaard, Tu Delft
05
Workshop
AI for Landslides
Lead Instructors : Rajat Shinde (Computer Scientist, NASA IMPACT/UAH) and Prof. Wenwen Li (Univ of Arizona)
Workshops
01
Workshop
Multi Hazard Risk Assessment (MHRA)
As part of the World Landslide Forum 7 (WLF7), this short course introduces participants to the principles, methods, and tools of Multi-Hazard Risk Assessment (MHRA), with a particular focus on landslide risk within multi-hazard environments and its applications in disaster risk reduction, climate adaptation, and resilience planning. This course is intended for researchers, disaster risk reduction professionals, GIS and remote sensing specialists, engineers, and students interested in understanding and managing risks arising from multiple interacting hazards.
Lead Instructors
Prof. Cees J. van Westen Full Professor, Multi-Hazard Risk Dynamics Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, The Netherlands
Dr. Ashok Dahal Assistant Professor, Department of Applied Earth Sciences Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, The Netherlands
Key Topics
Foundations of Multi-Hazard Risk Assessment
Multi-hazard concepts, terminology, and risk assessment frameworks
Hazards, exposure, vulnerability, loss, and damage
Impact chains, hazard interactions, and cascading effects
Data for Multi-Hazard Assessment
Data sources for hazard and risk analysis, including disaster databases and landslide inventories
Remote sensing and Earth observation applications
Data quality assessment, suitability analysis, and AI-based approaches for multi-hazard assessment
Exposure and Vulnerability Assessment
Asset classification, building characteristics, and exposure analysis
Population datasets and dynamic exposure mapping
Physical and indicator-based vulnerability assessment methods
Spatial Multi-Criteria Evaluation (SMCE) for risk analysis
Risk Assessment Approaches
Qualitative and quantitative risk assessment methodologies
INFORM Risk framework and other decision-support approaches
Project development – making a risk assessment for your own region
Practical Tools and Applications
Fast Flood and Fast Landslide modeling applications
RiskChanges Multi-Hazard Risk Assessment Platform
Online geospatial tools for hazard and risk analysis
02
Workshop
Landslide Risk Assessment
As part of the 7th World Landslide Forum (WLF7), this workshop provides a comprehensive introduction to the concepts, methodologies, and practical applications of landslide risk assessment. Reliable landslide risk assessment is fundamental for developing effective risk management, mitigation, preparedness, and adaptation strategies, particularly in areas where landslides threaten communities, infrastructure, cultural heritage, and economic activities.
This workshop is intended for researchers, practitioners, civil protection officers, planners, students, engineers, and decision-makers interested in understanding, assessing, and reducing landslide risk.
Lead Instructors
Dr. Fausto Guzzetti Professor of Geomorphology and Landslide Risk Assessment Department of Geography, Durham University, United Kingdom
Dr. Paola Salvati Senior Research Scientist National Research Council of Italy (CNR-IRPI), Italy
Prof. Bruce D. Malamud Professor of Natural and Environmental Hazards Department of Geography, Durham University, United Kingdom
Key Topics
Foundations of Landslide Risk Assessment
Definitions and concepts of landslide risk & assessment frameworks
Hazard, exposure, vulnerability, and consequences
Current challenges and uncertainties in risk estimation
Data Requirements for Risk Assessment
Landslide inventories and event databases
Geomorphological and geological information
Triggering factors and susceptibility data
Population and infrastructure exposure datasets
Vulnerability information and historical damage records
Risk Assessment Methodologies
Geomorphological approaches
Statistical & probabilistic approaches
Individual and societal risk estimation
Risk Communication and Decision Support
Landslide risk perception
Communication of risk information
Supporting land-use planning and policy development
Emergency preparedness and civil protection applications
Long-term mitigation and adaptation strategies
Case Studies and Applications
Local and site-specific landslide risk assessments
Regional and national-scale assessments
Population exposure analysis
Applications from Italy and other international contexts
03
Workshop
From Sentinel-1 to NISAR: Opportunities, Limitations and Future Perspectives of Satellite SAR for Landslide Applications
As part of the 7th World Landslide Forum (WLF7), this workshop explores the opportunities, limitations, and future directions of satellite Synthetic Aperture Radar (SAR) and Interferometric SAR (InSAR) technologies for landslide detection and monitoring. Building on the success of the Sentinel-1 mission and the emergence of next-generation systems such as NISAR, the workshop will examine when radar-based monitoring works effectively, where its limitations lie, and how it can be integrated with optical imagery, LiDAR, and GNSS observations. Through practical examples and expert discussion, participants will gain insights into the evolving role of Earth observation technologies in landslide risk assessment, civil protection, and early warning applications.
Lead Instructor
Dr. Oriol Monserrat Senior Research Scientist Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), Spain
Key Topics
Fundamentals of SAR and InSAR
Principles of Synthetic Aperture Radar (SAR)
Interferometric SAR (InSAR) techniques
Applications in landslide detection and monitoring
Factors affecting measurement accuracy
Sentinel-1 and a Decade of Systematic Monitoring
The impact of the Copernicus Sentinel-1 mission
Global monitoring capabilities
Advances enabled by open-access radar data
Lessons learned from operational applications
Understanding the Limitations
Vegetation effects and temporal decorrelation
Atmospheric disturbances and noise
Slope geometry constraints
Monitoring fast-moving landslides
Examples of successful and unsuccessful applications
Comparing Radar Frequency Bands
C-band, L-band, and X-band systems
Strengths, weaknesses, and complementary capabilities
Selecting appropriate systems for different landslide environments
Multi-Source Monitoring Approaches
Integration with optical remote sensing
LiDAR applications for terrain analysis
GNSS-based deformation monitoring
From Research to Operations
Operational landslide monitoring frameworks
Civil protection applications and Early warning systems
Challenges in implementing large-scale monitoring programs
NISAR and Future Perspectives
Overview of the NISAR mission
Expected advances in landslide monitoring
Remaining scientific and operational challenges
Future directions for satellite-based hazard assessment
04
Workshop
Hydrometeorological Thresholds and EWS Under Climate Change
Lead Instructor
Dr. Thom Bogaard Associate Professor of Hydrology and Natural Hazards Faculty of Civil Engineering and Geosciences, Delft University of Technology (TU Delft), The Netherlands
05
Workshop
AI for Landslides
Lead Instructors
Dr. Rajat Shinde Computer Scientist, NASA IMPACT Program The University of Alabama in Huntsville (UAH), United States
Prof. Wenwen Li, University of Arizona
06
Workshop
Using InSAR and AI for Slow-Moving Landslides
As part of the World Landslide Forum 7 (WLF7), this short course introduces participants to the principles, methodologies, and practical applications of satellite-based deformation monitoring and artificial intelligence (AI) for detecting, monitoring, and forecasting slow-moving landslides. The workshop focuses on integrating Interferometric Synthetic Aperture Radar (InSAR) observations with machine learning approaches to support landslide hazard assessment, early warning systems, infrastructure management, and risk-informed decision-making.
Slow-moving landslides often remain active for months or years following triggering events such as earthquakes and extreme rainfall, posing long-term threats to communities, transportation networks, critical infrastructure, and economic activities. Recent advances in satellite remote sensing have significantly enhanced our ability to measure ground deformation with millimeter-scale precision over large areas, while developments in AI have created new opportunities to forecast future slope behavior from large deformation datasets.
This course is intended for researchers, geohazard specialists, disaster risk reduction professionals, engineers, GIS and remote sensing practitioners, government agencies, infrastructure managers, and students interested in operational landslide monitoring and forecasting.
Lead Instructor
Dr. Ashok Dahal Assistant Professor, Department of Applied Earth Sciences Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, The Netherlands
Key Topics
Fundamentals of Landslide Deformation Monitoring
Mechanisms and evolution of slow-moving landslides
Factors controlling slope instability and long-term deformation
Earthquake- and rainfall-induced slope movements
Monitoring requirements for hazard assessment and early warning
InSAR for Landslide Detection and Monitoring
Principles of Interferometric Synthetic Aperture Radar (InSAR)
Satellite missions and deformation monitoring capabilities
Mapping active landslides using Sentinel-1 observations
Generation and interpretation of deformation maps
Applications in post-earthquake and rainfall-triggered landslide environments
Limitations, uncertainties, and operational considerations
Deformation Time-Series Analysis
Extraction and interpretation of displacement time series
Identification of deformation trends and acceleration phases
Detection of precursory signals and instability indicators
Integration of environmental and geospatial datasets
Artificial Intelligence for Landslide Forecasting
Introduction to machine learning and data-driven forecasting approaches
Feature engineering and preparation of deformation datasets
Forecasting future landslide behavior using historical displacement records
Model validation, performance assessment, and uncertainty analysis
Operational implementation of forecasting models
Landslide Early Warning and Risk Management Applications
Integration of monitoring and forecasting systems
Decision-support frameworks for landslide risk reduction
Applications for infrastructure management and asset protection
Emergency response planning and operational early warning systems
Opportunities and challenges for operational deployment
Practical Exercises and Workflows
Accessing and visualizing InSAR-derived deformation products
Identification and mapping of active slow-moving landslides
Processing displacement time-series datasets
Preparing datasets for machine learning applications
Developing and evaluating forecasting workflows
Reproducible and scalable operational workflows
Learning Outcomes
By the end of the course, participants will:
Understand the principles and applications of InSAR for landslide monitoring.
Be able to identify and characterize slow-moving landslides using satellite-derived deformation data.
Gain practical experience in extracting and interpreting displacement time series.
Understand the fundamentals of AI-based deformation forecasting.
Develop and evaluate forecasting workflows using real-world datasets.
Understand opportunities, limitations, and uncertainties associated with operational forecasting systems.
Learn how monitoring and forecasting outputs can support landslide early warning systems and risk management.
07
Workshop
Rainfall Thresholds and Digital Twin Earth Project
Lead Instructor
Dr. Maria Teresa Brunetti Senior Research Scientist Research Institute for Geo-Hydrological Protection (IRPI), National Research Council of Italy (CNR), Italy
Contact Us
Organising Secretariat 7th World Landslide Forum (WLF7) Amrita Vishwa Vidyapeetham, Faridabad Campus Mata Amritanandamayi Marg, Sector 88 Faridabad, Haryana – 121002 Delhi NCR, India