Cees van Westen

University of Twente, Faculty of Geoinformation Science and Earth Observation (ITC), Department of Earth Systems Analysis, Faculty Member

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Dr. Cees van Westen graduated in 1988 for his MSc (doctoraal) in Physical Geography from the University of Amsterdam. After working with the University of Amsterdam for one year on landslide related problems in Austria and Switzerland, he joined the Division of Applied Geomorphology of ITC in 1988, and specialized in the use of Remote Sensing and Geographic Information Systems for natural hazard and risk assessment. He obtained his PhD in Engineering Geology from the Technical University of Delft in 1993, with a research on "Geographic Information Systems for Landslide Hazard Zonation". During his work at ITC he has been working in various positions. Starting as an AIO (PhD student), he changed to working as lecturer, and assistant professor before being appointed as associated professor in 2000. Dr. Van Westen has worked on research projects, training courses and consulting projects related to natural hazard and risk assessment in many different countries, such as Austria, Switzerland, Italy, Spain, France, Georgia, Mexico, Guatemala, El Salvador, Honduras, Costa Rica, Colombia, Peru, Bolivia, Argentina, Sri Lanka, Indonesia, Thailand, India, Nepal, China, Vietnam and Philippines. Since 2005 he is Director of the United Nations University - ITC School on Geoinformation for Disaster Risk Management.

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113 Papers
5 Thesis Chapters
12 Drafts
12 Teaching Documents
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- 2 Books
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Papers by Cees van Westen

Low-cost UAV surveys of hurricane damage in Dominica: automated processing with co-registration of pre-hurricane imagery for change analysis

by Cees van Westen, Paul Weber, and Toby Meredith

In 2017, hurricane Maria caused unprecedented damage and fatalities on the Caribbean island of Do... more In 2017, hurricane Maria caused unprecedented damage and fatalities on the Caribbean island of Dominica. In order to 'build back better' and to learn from the processes causing the damage, it is important to quickly document, evaluate and map changes, both in Dominica and in other high-risk countries. This paper presents an innovative and relatively low-cost and rapid workflow for accurately quantifying geomorphological changes in the aftermath of a natural disaster. We used unmanned aerial vehicle (UAV) surveys to collect aerial imagery from 44 hurricane-affected key sites on Dominica. We processed the imagery using structure from motion (SfM) as well as a purpose-built Python script for automated processing, enabling rapid data turnaround. We also compared the data to an earlier UAV survey undertaken shortly before hurricane Maria and established ways to co-register the imagery, in order to provide accurate change detection data sets. Consequently, our approach has had to differ considerably from the previous studies that have assessed the accuracy of UAV-derived data in relatively undisturbed settings. This study therefore provides an original contribution to UAV-based research, outlining a robust aerial methodology that is potentially of great value to post-disaster damage surveys and geomorphological change analysis. Our findings can be used (1) to utilise UAV in post-disaster change assessments ; (2) to establish ground control points that enable before-and-after change analysis; and (3) to provide baseline data reference points in areas that might undergo future change. We recommend that countries which are at high risk from natural disasters develop capacity for low-cost UAV surveys, building teams that can create pre-disaster baseline surveys, respond within a few hours of a local disaster event and provide aerial photography of use for the damage assessments carried out by local and incoming disaster response teams.

Cees van Westen

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