Training Decision-makers In Hazard
Spatial Prediction And Risk Assessment:
Ideas, Tools, Strategies And Challenges
Author(s)
A. G. Fabbri & C. J. Chung
Abstract
Hazard prediction and risk assessment over regions exposed to natural and
technological processes are complex tasks that require exposure to quantization
of its uncertainty related to the prediction of future events through statistical
methods, spatial data analysis, case studies and process evolution interpretation
in conditions of uncertainty. All too often decision makers, DMs, similarly to
judges in environmental legal practice, do not have technical training to enable
them to communicate/understand the associated uncertainty from technical
specialists. In particular communication is a challenge with those who can
provide prediction maps and associated statistics to support decisions on disaster
prevention, avoidance or mitigation. An interactive short course was prepared to
overcome such obstacles to responsible land use planning and proactive measure
taking, for example, by asking a set of questions. A first phase in the training
follows steps that are to facilitate the comprehension of a spatial database on
landslide hazard, of its data processing, and of the interpretation of the analysis
results. Integral parts of a second phase are the theory of predictive methods, the
strategy in prediction map generation and visualization, including validation via
blind tests and the representation of the associated spatial and prediction
uncertainties. A successive third phase of the training brings in environmental
and socioeconomic spatial indicators to assign vulnerabilities and values to
exposed elements in the spatial database. Scenarios for hazard development in
the future are then provided. They allow to estimate the uncertainty associated
with the probabilities of hazardous occurrences and to resolve the risk equation
for different settings. The DM training course includes interactive and iterative
Keywords
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