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Can it really be that dangerous?Issues in visualization of risk and vulnerability

Abstract:Risk analysis tends to be a highly mathematically, statistically, let alone probabilistically oriented science. Riskmaps derived from risk analysis often portray only one possible scenario and do not leave much room forpersonal interpretation. Data on risks and hazards often tend to be heterogeneous, complex, inter-dependent,

not directly comparable, and correlated in ways that are not immediately apparent. Visualization technology hasemerged as a form of exploratory cartography, which can help explain, analyze and communicate risk. ecause

the risk analyst and the public in general may differ on what constitutes a risk or what not, visualizationtechni!ues can help the risk assessor better understand underlying factors and generate better risk maps, thuscommunicating a clearer message to the public. "xamples of how risk should be communicated are presentedand discussed along with current visualizations.

Introduction#e live in an advanced and seemingly peaceful society. #e have tamed nature the best we can, but naturaldisasters still happen. #e are surrounded by state-of-the-art safety technology, but ma$or accidents still happen.

%he ever increasing complexity of today&s modern society, coupled with its interwoven and interdependenttechnological infrastructure, where even a small-scale man-made or natural disaster can affect much more than

$ust the immediate vicinity of the disaster, has given rise to the field of risk assessment, aimed at !uantifyingrisks and their probability, and thus managing risks.

'eneral use of risk assessment can provide a basis for preventing and limiting the conse!uences of accidents,thus enabling the risks to be dealt with in a coherent way (D)D"*, +. %his is also supported by the nited/ations "nvironment *rogram 0*"11 (0wareness and *reparedness for "mergencies at the 1ocal 1evel, whichlists the identification of risks that can pose a potential threat as one of its main goals. 2imilarly, 3"40 (3"40,+5 has its *R67")% 84*0)%, aimed at building disaster-resistant communities. 8n order to gain betterpreparedness for disasters, possible risks must be identified. Visualization may here provide a valuable tool forboth identifying, exploring and communicating risks.

'eographic visualization has emerged as a tool for searching through huge volumes of data, for communicatingcomplex patterns, for providing a formal framework for data presentation, and for exploratory analysis of data('ahegan, +. Data on risks and hazards often tend to heterogeneous, complex, inter-dependent, not directlycomparable, and correlated in ways that may not be apparent without the use of visualization technology. 8n apaper on the use of '82 to assess natural hazards, )oppock (599: noted visualization as important not only inthe development of '82 generally, but also as a tool to improve reliability of hazard assessment, thus decisionsupport, and also to improve the ability of non-experts to take advantage of the information presented. 0statement on the need to improve the representation of risk and vulnerability is also found in Radke et al. (+,noting that the average '82 is not able to represent the depth and richness of the dynamic nature of risk andvulnerability.

%his paper will address the issue of visualization as a means of risk communication as well as risk exploration,highlighting the different approaches that need to be used in explorative visualization versus communicativevisualization.

Risk and vulnerability

Objective versus perceived risk8n its simplest form risk may be seen as the product of probability and conse!uence.

R ; * x ) (Risk ; *robability x )onse!uence

8n this sense, both high-probability low-conse!uence incidents and low-probability high-conse!uence incidentsmay have the same risk value< 8t is !uite probable that 8 may stumble and fall when walking along a forest trail=the conse!uences in most cases are minor. 8t is much less probable that 8 will be hit by a falling tree whenwalking the same trail= the conse!uences however may be dire. "ven though the ob$ective risk numbers may bethe same, we humans will rank one risk above the other. #hich is the greater risk>

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%his makes it clear that in dealing with risk, it is often necessary to distinguish between ob$ective risk andperceived risk. 6b$ective risk is a measure of the scientifically !uantifiable risk, often derived from probabilitycalculations. *erceived risk is a measure of the imminent danger a person feels he or she is in. *erceived risk canalso be a measure of what conse!uences the individual person is willing to accept before he or she considers aprobable incident to be a risk.

VulnerabilityRisk often pertains to a factual event= vulnerability often pertains to a system, such as power supply,

telecommunications, infrastructure or society as a whole. Vulnerability is a measure of how well a system cancope with or sustain a risk. %he average risk of a long-term power outage may be relatively small in our modern

world, except for example during severe winter storms. ?et, even though the risk is minor, the vulnerability isextremely high. %his makes it eminent that any risk needs to be linked to its conse!uences to have a meaning.)onse!uences in narrative form are one form of @visualization@. 2ince vision is the dominant sense in sightedhumans ('ahegan, +, a visual presentation of conse!uences will often generate a better insight.

Risk eperts versus public opinion8t may seem oversimplified to phrase it this way, but one could say that the risk expert is mainly concerned withfinding the !uantitative risk, that can be stated in mathematical figures, because that is what most technologicaldecisions are based on. %he general public or the individual person on the other hand is more concerned with the!ualitative risk that affects him or her personally. )onse!uently, the communication of risk becomes either anobstacle for widening or a bridge for closing this gap between the expert and the layperson. Risk visualization canplay a ma$or part in doing so.

Risk co!!unication0s a conse!uence of the understanding about the divergence in perceptions of risk between the public and theexperts, and the ensuing debate over the acceptability of such risks, a whole new area of study has developed,called risk communication. Risk communication is the process of developing and delivering a message from therisk expert to the general public ()utter, 599A.%his process may be aimed at communicating about the danger in a pending emergency or in general to informabout the risk in an issue that the public may or may not perceive differently from the experts.

Risk visualization can, in fact, be viewed as one form of risk communication, which can be further separated intoexplorative visualization and communicative visualization. %he first approach emphasizes exploration, meant tostudy and to analyze phenomena or events that can be considered a risk, the latter emphasizes communication,meant to inform and to raise awareness among the public in general.

6ne of the main issues that needs to be addressed in risk communication is the !uestion of how to communicaterisk and the !uestion of to whom the communication is directed. 'oing further into area of risk communicationwill be beyond the scope of this paper= readers are referred to 1undgren (599B or 'utteling et al. (599C for

further study.

Issues in visualization of risk

Visualization versus cartographyVisualization of spatial data has close links with cartography. )artography is the art or science of making maps(#ebster or the art and science of graphically representing a geographical area, usually on a flat surface such asa map or chart= it may involve the superimposition of political, cultural, or other nongeographical divisions ontothe representation of a geographical area.)artography is an ancient discipline that dates from the prehistoric depiction of hunting and fishing territories(www.britannica.com.

4aps have been used for centuries to visualize spatial data. %hey help their users to better understand spatial

relationships. 3rom maps, information on distances, directions and area sizes can be retrieved, patterns revealedand relations understood. (raak and 6rmeling, 599C

*ast presentation-oriented cartographic research has emphasized the use of static maps designed for publicconsumption with the emphasis on extracting specific pieces of information (4ac"achren and raak, 599E.Visualization, which has emerged and gained momentum during the last decade, is less concerned withpresentation created by a supposed expert, and more concerned with exploration by the individual.

4ac"achren (599B introduced a map-use based approach to visualization, presented as a cube, which was latermodified together with raak (4ac"achren and raak, 599E, see figure.

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"ploration versus co!!unication"ven though this map-use cube identifies B speparated stages in visualization, it may be better to seevisualization as a continuuum ranging from exploration, that is looking at the data, via analysis, that isdiscovering hidden relationships, to presentation, that is communicating one or more realizations of the data.

0s mentioned above, past communication-oriented cartographic research has emphasized the use of static mapsdesigned for public consumption with the emphasis on extracting specific pieces of information (4ac"achren andraak, 599E. nfortunately this still holds true in the realm of risk mapping, where the lay user of the map has

to rely on the information that the risk expert chooses to put on the map. #ith little or no understanding of howthe map was derived or how to interpret it properly, risk perception becomes a highly personal matter.

#ncertainty%he very word risk implies uncertainty. )onversely, if there exists an uncertainty whether a hazard exists, thereremains a probability that it does and therefore there exists a risk. Fuantitative analysis of uncertainty andvariability is receiving growing acceptance in risk acceptance. %hus, it is the responsibility of the risk assessor touse whatever information us available to obtain a number between zero and one for a risk estimate, with asmuch precision as possible, together with an estimate of the imprecision. (#ilson and 2hylakter, 599E

Davis and eller (599E explore the modeling and visualization of multiple spatial uncertainties, using slopestability and landslide susceptibility. Davis and eller argue for a dynamic, rather than static display, because animportant aspect of visualizing uncertainty should be the ability to view the various realizations rather than theparameters. %his is particularly true when viewing the results of a process model. %he static display of standarddeviation values would be of little use to decision makers. Visualizing the implications of variance is far more

important. %his has direct bearings to risk visualization where one static display of a certain set of parametersdoes not give a full picture of the variability in the data. 8n lay terms, exploring different combinations of riskrelated to the certainty of the derived risk may give a different view than the risk value alone. 8f the risk is high,but its certainty is low, then is the risk actually high or is it not>

0 similar approach can be discerned in "hlschlaeger et al. (599E, where uncertainty in elevation data creates anumber of diverging realizations of a possible corridor between two locations. sing the analogy of corridoranalysis, and substituting the elevation surface with a risk surface, this could be applied to road design in findingthe least hazardous path over a given terrain, avoiding terrain with a high potential for wildfires, landslides, flashflooding in gullies, or analyzing an existing right-of-way corridor with relation to its hazard potential.

Correlation%obler (59E9 championed the phrase @everything is related to everything else, but near things are more related

than distant things&&. 6ne way of visualizing this is through scatterplots. 2catterplots are perhaps the most well-known visualization techni!ue for exploring spatial relationships 'ahegan (+, as well as dependency betweenvariables in a risk analysis (Vose, 599E. %he ma$or difference between the two is that while risk analysts and

statisticians confine themselves to investigating the dependencies between two variables, spatial analysts usingvisualization techni!ues can work in A or more dimensions