Course Description and Objectives
The course provides a new and much needed advanced approach to hazard and risk assessment that includes prediction uncertainty estimated through validation techniques. It is intended for geomorphologists, environmental scientists, remote sensing specialists, geographers, spatial data analysts, GIS specialists, managers and others who would like to understand the basic principles underlying spatial prediction models and their associated uncertainties. It will cover conceptual ideas, rather than rigorous mathematics, and practical hands-on experiments. No previous exposure to prediction models is necessary although a degree in engineering or science (or equivalent experience) is desirable. Those attending can expect to gain an understanding of the state-of-the-art and be in a position to make informed decisions about the extent this technology is relevant to the specific problems in their respective fields of interest.
Hazard maps should show the likely location of future hazardous events, possibly including the expected intensity and time interval of occurrence. In addition, they must display the degrees of reliability and uncertainty as accompanying maps. Because for many current mapping techniques there is hardly any discussion of the uncertainty associated to predictions, this course focuses on that fundamental aspect by applying validation strategies in different phases of spatial modelling. The representation of the uncertainty is the foundation of the estimation of the probability map showing the probability of future hazardous events at each pixel under certain conditions/assumptions. By integrating the probability map with socio-economic vulnerability data, including the spatial distributions of population densities, infrastructures, the flow of goods and services, and other related economic parameters, a risk assessment map is generated.
Several case studies including both earthquake- and rain-induced landslides, from Columbia, Korea, Portugal, Spain, Canada and U.S.A will be discussed, amongst other types of hazards and vulnerabilities, to illustrate the procedures proposed. The estimation of the probability of occurrence of future hazardous events, based on estimated uncertainty from the cross-validation/blind-tests, does provide the necessary elements of robustness and transparency to contribute to not only a decisional process but also to obtain the necessary information to generate a risk map. Risk maps are generated using assumptions and scenarios. The Spatial Target Mapping Systems and Spatial Risk Assessment System (STM-SRA), designed for the application of those techniques, will be used in the practical exercises during the course. They will be described and applied to the databases of the case studies. Course notes and software will be provided to each attendee.
Tuesday, 28 March 2017
- Overview aims and scope of the course (AGF)
- Deficiencies in current hazard mapping and risk assessment (AGF)
- Mathematical frameworks for spatial prediction models (CJC)
- Practical applications and case studies: Generate hazard maps (AGF + CJC)
Wednesday, 29 March 2017
- Uncertainty in spatial prediction models (CJC)
- Cross-validation (blind test) and iterative procedures (AGF)
- From hazard map to probability map – requirements and assumptions (CJC)
- Practical applications and case studies: Generate probability maps (AGF + CJC)
Thursday, 30 March 2017
- Overview of risk assessment (AGF + CJC)
- Socio-economic data layers for risk assessment (AGF)
- Practical applications and case studies: Generate risk assessment maps (AGF + CJC)
Each day is subdivided into four sessions and will commence at 9.00 am and finish at 5.00 pm. Lunch break is from 12.30 pm to 2.00 pm. Coffee will be served during the breaks. Please note that the course will start at 9.15 am on the first day.
The course fee includes all working materials, lunch, coffee, tea and all computer facilities used, where applicable. During the course software will be provided and therefore participants may wish to bring their own laptops. The Institute reserves the right to make changes to the programme that may prove necessary.
Andrea G. Fabbri obtained his M.Sc. in geology from the University of Bologna in Italy and his Ph.D. from the University of Ottawa in Canada. He is an internationally recognized scientist who pioneered the development of geographical information systems for prediction modeling in mineral exploration, hazard and risk assessment, and environmental impact studies. He has contributed with fundamental works on database management, image processing, pattern recognition and multi-criteria analysis in geological and environmental geo-sciences. For fourteen years he has held the position of research scientist at the Geological Survey of Canada (GSC) in Ottawa. Later his research continued with the Bologna’s Institute of Marine Geology of the Italian National Research Council, the Canada Centre for Remote Sensing (CCRS) in Ottawa, the International Institute for Geo-Information Science and Earth Observation, ITC, in Enschede, The Netherlands, where he was awarded the chair of geology, and the SPINlab, of the Vrije Universiteit in Amsterdam, The Netherlands, as Chair of Geo-information and Risk Management. In 2002 he was awarded the chair of Environmental Geology at the University of Milano-Bicocca in Milan, Italy, where he has been offering graduate courses on hydro-geologic risk, geo-statistics and spatial prediction modeling until his retirement in 2012. Prof. Fabbri has authored or co-authored over 180 scientific papers and several volumes, including the book entitled “Image Processing of Geological Data (1984, New York, van Nostrand-Reinhold). His present research interest is in the digital representation of environmental indicators and indices and predictive modeling of environmental impacts. He has directed a NATO Advanced Study Institute on “Geo-environmental Deposit Modeling for Resource Exploitation and Environmental Security” that was held in Mátraháza, Hungary, in September 1999. He has been the coordinator and a principal investigator of the GETS Research Network of the European Commission’s Programme on Training and Mobility of Researchers (T&MR) on “Geomorphology and Environmental Impact Assessment of Transportation Systems in Europe” (1999-2001).
Dr. Chang-Jo Chung was a principal consultant (2008-2016) at Spatialmodels Inc., an adjunct professor (2008-2013) at the Department of Earth Sciences of the University of Ottawa, Canada since his retirement in 2008 from the Geological Survey of Canada as a research scientist (1970-2008). His research built on a multi-disciplinary platform focuses on the development of comprehensive quantitative techniques for spatial prediction models by synthesizing complex and often incompletely known geological processes within controllable mathematical frameworks. More significantly, he has provided conceptual procedures to estimate uncertainties associated with the application of these predictive models. Whereas the models provide quantitative predictions regarding future events, such as climate changes, natural hazard or mineral discoveries, the uncertainties indicate how wrong or right the predictions are likely to be. These procedures for estimating uncertainties are the fundamental underpinnings of much of the worldwide cutting-edge research in spatial predictive models. Since 1996, he has particularly targeted his applications to climate changes and hazard mitigation while he has maintained his study in mineral target mapping for sustainable resource development. In addition, his contribution has been to bridge gaps between statistical research community and the specialists in geosciences and environmental sciences, and it has allowed the statistical techniques to be operational tools in tackling the problems in geosciences fields. He is the author of over 120 publications (peer-reviewed scientific papers, key-note lectures, book-chapters, and technical reports) and has received numerous awards and recognitions: University medal from Carleton University, Canada, Foreign Scientist Visiting Professor Fellowship from The University of Tokyo, Japan, and Queen Elizabeth II Golden Jubilee Medal from the Governor General of Canada.
To register online for this course please complete the registration form by clicking on the 'Register' button at the top of this page.
The New Forest is one of the UK's most popular tourist destinations and offers many attractions all year round, including picturesque forest villages as well as beautiful scenery. It is located in Southern England, spreading over 150 square miles of Hampshire. The New Forest was established as a royal hunting ground by King William I, and by the 14th century the land was being used to produce timber for the ship building industry on the south coast. Today, after nearly 1000 years, the forest is still Crown property and is administered by the Forestry Commission. Since the reign of King William I commoners have been given the right to graze their livestock, normally ponies, cattle and pigs, on Forest land where they wander freely. In the New Forest the well-being of the animals and the special needs of the countryside are a priority. The Forest is unarguably recognised as one of the most unique and important wilderness areas in Western Europe and, because of this, it is now a National Park.
Venue and Accommodation
The course will take place at the Wessex Institute of Technology at Ashurst Lodge located in the New Forest, an outstanding National Park that borders the South Coast. Ashurst Lodge is an ideal venue for conferences, courses and seminars. The participants can benefit from an excellent standard of accommodation, either on Campus or in various hotels or bed and breakfasts in the area. The surroundings are equally appealing to those who enjoy walking, horse riding, cycling, sailing and fine landscapes.
For more information on how to find Ashurst Lodge and to arrange accommodation during the courses please use the information provided on the Contact Us page.