‘background’ activity (no unrest), through to the highest level of activity (usually a large eruption) (Newhall 2000; Fearnley 2011).

Volcano observatories play a key role in the management and assignment of alert levels for volcanoes. However, with over 80 volcano observatories around the world, it is understandable that VAL systems operate in very different ways. Some provide only scientific advice on what a volcano is doing, others forecast activity, and others provide guidance on what vulnerable populations should do. There is a growing discussion globally around the role of VAL systems and whether they should be standardised, either nationally and/or internationally.

In 1989, the member states of the United Nations declared the period from 1990 to the year 2000 to be the International Decade for Natural Disaster Reduction (IDNDR) to focus attention on reducing loss of life, and social and economic disruption caused by natural disasters. Of fundamental importance was the recognition in 1991 of early warnings as a key objective of disaster reduction practices (Maskrey 1997). The United Nations has called for more effective procedures via standardisation and the application of new technologies and enhanced scientific understanding (United Nations 2006) but few hazards have an EWS operating beyond a national or regional scale. The most successful example is the Pacific Tsunami Warning Centre (PTWC), established in Hawaii in 1949. Until recently, PTWC provided Warning and Watch alert level services for numerous Pacific nations and beyond, but currently they provide nations with threat level information (e.g., wave amplitude forecasts), which the countries then use in-house to develop and disseminate specific tsunami alert levels (i.e., Warning, Watch).

The growing pressure on volcano observatories to standardise warnings is felt especially in relation to provision of advice and alert levels to the aviation sector. In 2006, the International Civil Aviation Organization (ICAO) globally standardised a considerable portion of products, including the alert levels (via the Aviation Colour Code (ACC); Table 1), messages to airlines that observatories are expected to provide (via

the Volcano Observatory Notice for Aviation; VONA), and the framework for monitoring and alerting related to ash clouds (via the Volcanic Ash Advisory Centres; VAACs). While VAACs provide the aviation community with information regarding where ash currently is in the air, the role of the ACC is more about warning (Gardner and Guffanti 2006). The ACC allows a recognition of the level of volcano activity for the purpose of attention by the aviation industry, and to inform their decisions, such as regarding re-routing or extra fuel (Gardner and Guffanti 2006). VONAs are standardised plain-English messages aimed at dispatchers, pilots, and air-traffic controllers ‘produced by Volcano Observatory scientists and are based on analysis of data from monitoring networks, direct observations, and satellite sensors’ (as described on the USGS website<fnref n="1" />). The international nature of these aviation products reflects the need for aviation personnel to ascertain the status of volcanic activity across a number of countries and VAL systems (e.g., Guffanti and Miller 2013), which is why a standardised approach is used. While working fine for international air traffic, problems have been encountered for low-level domestic and private aviation with the ACC (Fearnley 2011).

Numerous volcano observatories across the world are now implementing the ACC, and many of these are questioning the adoption of other VAL systems for ground-based hazards and reviewing their volcano early warning systems. This includes reviewing the effectiveness of VAL issuances, as Winson et al. (2014, p. 12) invite “countries to perform their own self-evaluation and weigh the cost of a higher number of alerts against the benefit of a higher accuracy in VAL issuances and to decide how to proceed accordingly with their own local populations”.

The benefits of standardisation are principally:

* simplicity through application of common language, frameworks and understanding;

* clarity for emergency responders;

<footnote n="1">¹https://volcanoes.usgs.gov/vhp/notifications.html accessed 11 May 2017.</footnote>
* reduced workload for monitoring and emergency management agencies, including education and outreach;

* interoperability of equipment and systems across hazards, and across agencies, countries or internationally.

Warning messages with specific language and approaches can benefit from standardisation. In doing so, it is advisable to publish and make accessible the definitions of technical volcanic terms, and of the words ‘risk’ and ‘hazard’ as used by the scientists. This is to ensure local users understand the intention behind the scientist’s use of the terms. For example, calculation of ‘hazard’ can be based on previous events, deterministic and/or probabilistic approaches, and should be described. In addition, the communication of likelihood/probability can also be a point of confusion; ideally numeric values should be mapped against qualitative descriptions and both presented together (e.g., Doyle and Potter 2016). Standardisation can also increase credibility, a known requirement for effective warning, by producing warnings that are clear, and from a trusted source. With a credible source user groups are less likely to look for alternatives or confirmation, leading to faster action. However, end-user decision making and action can be limited in terms of contingent-specific-needs if warning products are standardised too much (e.g., depending on a user’s ability to read different types of maps (Haynes et al. 2007); or loss of meaning or relevance in the warning within a local context).

There are various elements of end-to-end warnings that lend themselves to standardisation that can aid the effectiveness of the VAL system:

* Technical: Equipment type, deployment (distribution/location/density), telemetry (radio, wire, internet etc.), visualization (software packages) and analysis all receive some level of standardisation through manufacturing standards, detection limits, and international scientific best practice.

* Analytical tools: Analysis may be further structured through statistical approaches such as expert elicitation, Bayesian event trees or Bayesian belief networks.

* Warning tools: Notification may be standardised through message content (e.g., standard messages, terminology, alert level criteria), packaging (e.g., bulletins, alert levels, maps) and delivery channels (e.g., phone, internet, siren). Some standards lend interoperability, such as a Common Alerting Protocol.

* Response: Decision-making and action by the end-user can be standardised to some extent through communication and education approaches and message content.

Clearly there are cases where standardisation provides many advantages, but the process of standardisation is predominantly triggered and shaped by social, political, and economic factors, rather than in response to scientific needs specific to a region. Standardisation, by definition, tends to exclude the importance of incorporating local factors into a global procedure. Hence, even if standardisation may yield improved strategies for gathering and interpreting warning signals, it will still favour inflexible procedures not designed to accommodate local social and cultural constraints. Challenges are brought about by a range of issues (Fearnley 2011, 2013), especially:

* the realities of varied volcanic systems, each being geophysically unique when examined in detail. The diversity and uncertain nature of numerous hazards that can occur at different temporal and spatial scales require specific EWSs to be developed.

* varied end-users with different needs and perspectives for their decision-making, in terms of the level of volcanic activity, and timing thresholds for response actions.

* multiple local social and cultural contexts and constraints, which presents challenges in relation to the applicability and responsiveness of EWSs to local knowledge and context.
In recent decades, standardisation within VAL systems at a national level has taken place, making provision for consistency of warnings enacted by civil authorities that are required to take action and facilitate national policies for emergency management. VAL systems in a number of countries (including Japan via the Japan Meteorological Agency (JMA), Vanuatu via GeoHazards, the USA via the USGS, and New Zealand via GNS Science) have been standardised in each country for use by all volcanic observatories. Yet, there are variances in the way VAL systems are being standardised. In the USA, for example, two standardised VAL systems are now in place: a textually based version for ground hazards (e.g., watch, warning) and the aviation colour code that uses colours as labels. In New Zealand, the VAL systems adopted in 1994 and reviewed in 1995 also used two standardised VAL systems: one designed for hazards expected at frequently active volcanoes and the other for restless and reawakening volcanoes (see Table 2). Both of the New Zealand VAL systems were numerically based using six levels ranging from 0 to 5 (Scott and Travers 2009). Another review in 2014 resulted in these two systems being combined into one (Potter et al. 2014), whilst also adopting the international aviation colour code (ACC). Notably, both the USA and New Zealand VAL systems are based upon the current activity of a volcano, and neither advocate action nor provide advice to users involved in crisis management and mitigation—this information is provided in other products. In sharp contrast, the Japanese VAL system addresses the measures to be taken for specific areas of danger, indicating extent of evacuation, and outlining the expected volcanic activity.<fnref n="2" />

This chapter focuses on the standardisation of VAL systems using the case study of New Zealand in the revision of the VAL system in 2014, to explore the benefits and challenges in implementing a nationally standardised VAL system. Reflections upon its success will help

inform others as to why the devised national alert level in New Zealand is best placed for their nation, and why perhaps an international level of standardisation for VAL systems is still something that is unadvisable, and unfeasible.

## 1.1 Overview of New Zealand's Volcanic Risk Setting

New Zealand straddles the boundary between the Pacific Plate and the Australian Plate. The resulting subduction zone lies beneath a rifting area of thin crust with magmatic upwelling, called the Taupo Volcanic Zone (TVZ; Fig. 1). The TVZ contains most of New Zealand's active volcanoes, and includes stratovolcanoes and calderas.

New Zealand has a range of volcanic risk settings that creates a challenge in effectively communicating scientific information to stakeholders, including the public. In terms of hazard, the volcanoes have large differences in the potential eruption styles and magnitudes of eruptions, reflected by variations in magma chemistry. The past frequency of eruptions and the date of the most recent eruption also vary considerably between them, which contributes towards a range in the likelihood element of the risk equation. The exposure and vulnerability of communities to unrest and eruptions also differs, with some volcanoes (such as Ruapehu, Ngauruhoe, and Tongariro) situated in a largely unpopulated National Park; and others are islands in the Pacific Ocean with few permanent residents (such as Raoul Island in the Kermadecs). Other volcanoes, such as Auckland Volcanic Field, Taupo Volcanic Centre, Okataina Volcanic Centre and Rotorua Caldera volcano, are in close proximity to cities. A few of the volcanoes receive tens of thousands of visitors each year, and are used commercially by tourist operators (including Whakaari/White Island). Others, such as Taranaki volcano, are surrounded by fertile agricultural land and are near important national infrastructure. Each of these elements of risk (hazard characteristics, likelihood, exposure and vulnerability) influence the type of

<footnote n="2">²www.data.jma.go.jp/svd/vois/data/tokyo/STOCK/kaisetsu/English/level.html accessed on 11 May 2017.</footnote>
<figure><img src="image_195.png" /><figcaption>**Fig. 1** Map of New Zealand’s volcanoes, from Potter (2014), and based on Smith et al. (1993), Nairn (2002), Wilson et al. (2009), and Lindsay et al. (2010). The Taupo Volcanic Zone (TVZ; depicted as a *dashed line*) envelops the majority of the volcanoes. The calderas (*polygons*) are</figcaption></figure>

MI Mayor Island; *Ro Rotorua*; *OVC Okataina Volcanic Centre*; *Kp Kapenga*; *Rp Reporoa*; *Oh Ohakuri*; *Mg Mangakino*; *Wh Whakamaru*; and *TVC Taupo Volcanic Centre*. The volcanic fields are indicated by *ovals* with *diagonal lines*
<figure><img src="image_196.png" /><figcaption>**Fig. 2** Eruption at Te Maari Crater, Tongariro, on 21 November 2012, captured by the GeoNet Te Maari Crater web camera (GNS Science)</figcaption></figure>

communication and information required, as the local context needs to be considered.

The Tongariro Volcanic Centre is the southernmost volcanic complex of the TVZ, and includes the frequently active andesitic Ruapehu and Ngauruhoe/Tongariro stratovolcanoes. Lahars have frequently occurred, causing a hazard in numerous valleys on the volcanoes (e.g., Leonard et al. 2008). Ruapehu hosts popular ski areas, and last erupted with vigour in 1995–96 (Hurst and McGinty 1999). Small eruptions with short durations also occurred in October 2006 and September 2007. Volcanic unrest is on-going. Ngauruhoe is the most frequently active vent of the Tongariro massif, displaying regular eruptions until 1977 (Scott 1978), but none since. Te Maari Crater and Red Crater on northern Tongariro were active in the late 19th Century, with frequent eruptions in 1896–97 (Scott and Potter 2014). After less than one month of minor unrest, Te Maari Crater was the source of two small, short-lived phreatic eruptions on 6 August and 21 November 2012 (Fig. 2). There were no casualties, however the tourism industry was impacted due to the closure of a popular walking track (the Tongariro Alpine Crossing) by the Department of Conservation (DoC), which manages the National Park.

There are eight areas of known caldera collapse in the central TVZ (Fig. 1), which itself can be considered to be a caldera system similar to Yellowstone in the USA. Although calderas are usually formed in occasional very large eruptions, their magma system can also be the source of many smaller eruptions. The calderas in the TVZ have erupted almost exclusively rhyolitic material in at least 25 caldera-forming eruptions in the last 1.6 million years (Wilson et al. 1984, 2009). Only <0.1% of the volume of deposits in all of the TVZ are from basaltic eruptions (Wilson et al. 1995). The caldera volcanoes have a large range in past eruption magnitudes. For example, the TVZ's most-recent caldera collapse took place at Taupo Volcanic Centre (TVC) in 232 ± 5 AD, erupting 35 km³ of magma (Wilson 1993; Davy and Caldwell 1998; Self 2006; Hogg et al. 2012). This devastated a significant portion of the central North Island in widespread pyroclastic density currents (Wilson and Walker 1985). However, 26 of the 29 eruptions at TVC in the past 26,000 years (since the last supervolcano eruption) have been much smaller than the most recent eruption (Wilson et al. 2009). Therefore, it is unknown whether future eruptions at TVC will be relatively small, as has been the case most frequently, or
devastatingly large, as was the case with the most recent eruption. An additional challenge is managing caldera unrest, which can cause social and economic impacts, without a resulting eruption (Potter et al. 2012, 2015).

The north-eastern extremity of the TVZ contains White Island (Whakaari), a privately owned andesitic stratovolcano located 50 km from the Bay of Plenty coastline. It is currently New Zealand's most frequently active volcano, and a popular tourist destination with approximately 25,000 tourists and tourist operators visiting the island per year. Frequent eruptive sequences have been documented since written records began in 1826 (Nairn et al. 1991), with the most recent eruptions occurring in 2016. New Zealand is also responsible for a number of other island volcanoes, including Mayor Island in the Bay of Plenty, and Raoul and Macauley Calderas in the Kermadec Island chain, 750–1000 km northeast of New Zealand. These islands have very few visitors or residents. About 30 submarine volcanoes are also known in the Kermadec area and some exhibit eruptive activity. Due to the lack of monitoring data, a VAL is not allocated to them.

Taranaki Volcano is a stratovolcano located in the west of the North Island, outside of the TVZ. It is thought to have last erupted in 1755 AD (Druce 1966), but it may have subsequently extruded lava, forming a dome after this date (Platz 2007). It is capable of fairly large eruptions, and has a history of sector collapse (e.g., Neall 2003). Taranaki Volcano is surrounded by productive agricultural land and is in a major hydrocarbon (gas and oil) production region. There is a regional population of just over 100,000 people, most of whom live in the city of New Plymouth.

The intraplate Puhipuhi-Whangarei Volcanic Field (PWVF), the Kaikohe-Bay of Islands Volcanic Field (KBOIVF) and Auckland Volcanic Field (AVF) are in northern New Zealand (Fig. 1). PWVF is thought to have been active as recently as 0.26 Ma, while dating of the KBOIVF indicates an eruption occurred at about 0.05 Ma (Smith et al. 1993), or perhaps as recently as in 200–500 AD (Kear and Thompson

1964). AVF has had many eruptions from at least 53 basaltic vents, most recently about 600 years ago (e.g., Needham et al. 2011). Auckland city hosts a third of New Zealand's population with 1.4 million residents, and is sited directly on top of AVF.

Eruptions from most of New Zealand's volcanoes are likely to impact infrastructure of national importance, including many State Highways and road networks, electricity lines and power stations, train lines, water supplies, and sewage facilities (Wilson et al. 2012). Additionally, industries important to the local, regional, and national economies may be threatened during future eruptions, including the tourism, agricultural, forestry, and hydrocarbon industries.

## 1.2 Communication of Volcano-Related Information in New Zealand

In New Zealand, GNS Science is the agency appointed by the Government to provide scientific advice to local, regional, and central government organisations for geological hazards, as stated in the Guide to the National Civil Defence Emergency Management (CDEM) Plan (MCDEM 2015a) and a Memorandum of Understanding with the Ministry of Civil Defence and Emergency Management (MCDEM)(GNS Science, The Ministry of Civil Defence and Emergency Management 2015). The MOU outlines the obligations of GNS Science for geohazard warnings, whereas the Guide to the CDEM Plan is to assist New Zealand agencies to achieve the objectives of the National CDEM Plan (MCDEM 2015b). New Zealand's volcanoes are today monitored by GNS Science through the GeoNet project (Scott and Travers 2009), funded primarily by the New Zealand Earthquake Commission (EQC).

Volcano-related information is communicated to stakeholders, including the public, in a variety of formats before, during, and after volcanic crises. The primary tool used is the Volcano Alert Bulletin (VAB), supported by web page
information on GeoNet News,<fnref n="3" /> blogs, news items and social media tools (Facebook, twitter). Volcano hazard and status information is also presented by scientists during meetings, conferences, workshops, and public lectures; websites; in scientific and non-scientific publications; and via the media. Smartphone app push alerts, emails, faxes, pager alerts, and text messages provide one-way information to registered end-users during crises or changes in volcanic activity. Volcanic ash impact posters (a product of the Volcanic Impact Study Group, commissioned by the Auckland Lifelines Group) provide accessible information for critical infrastructure stakeholders (Wilson et al. 2014). Social media and ‘ask an expert’ interactive online sessions allow questions to be asked by the public and answered by scientists in real-time. Informal conversations during meetings, workshops, or by telephone provide end-users with more specific information from volcanologists, with the opportunity for two-way communication. An example of this is during Volcanic Advisory Group meetings, which are attended by key stakeholders and volcanologists to discuss volcano- and response-related information (Doyle et al. 2011). Long-term hazard maps have been created for some of the more active volcanoes, based on geological evidence of past eruptions (Neall and Alloway 1996; Scott and Nairn 1998). Event-specific hazard maps are created during unrest depending on the situation, likely vent location, and the style and magnitude of the potential eruption, etc. Event-specific hazard maps were created prior to and after the Tongariro eruption in 2012 (Leonard et al. 2014).

New Zealand's VAAC, based at the Meteorological Service of New Zealand Ltd. (MetService) office in Wellington, is designated by the International Airways Volcano Watch system to communicate ash information for a large section of the southwest Pacific, including New Zealand's active volcanoes (Lechner 2012). MetService issues Volcanic Ash Advisories in a text and graphic form, and disseminates a Significant

Meteorological Information (SIGMET) message, while Airways Corporation issue Notice to Airmen (NOTAM), which draws attention to volcanic ash hazards within the NZ VAAC area. These globally standardised messages are also issued when New Zealand's VAL changes, prompting restrictions to local air space. After consultation with GNS Science for NZ volcanoes, Volcanic Ash Advisories are communicated by the VAAC to MCDEM, in addition to being provided to international aviation agencies and meteorological communities (MCDEM 2015a). Volcanic Ash Advisories from MetService forecast the distribution of volcanic ash in the atmosphere for the purpose of aviation safety, whereas GNS Science issues ashfall prediction maps as a VAB, relating to the distribution and thickness of tephra deposits at ground level. In addition to these systems, GNS Science issues Volcano Observatory Notices for Aviation (VONA) to the VAAC to report on ground-based volcanic activity whenever they change the Aviation Colour Code (ACC; Table 1). The ACC is used by the Civil Aviation Authority of New Zealand to alert the aviation industry to changes in the status of volcanoes within the designated coverage area (Lechner 2012).

## 1.3 New Zealand's Past VAL Systems

In New Zealand, scientists at GNS Science determine the VAL as mandated in the Guide to the National CDEM Plan (MCDEM 2015a), with consideration of monitoring data and using their experience and knowledge. When decisions need to be made rapidly (e.g., if an eruption has taken place), the Volcano Duty Officer can make the VAL decision alone. GNS Science, through GeoNet, communicates this information to MCDEM using Volcanic Alert Bulletins. MCDEM forwards this information on to local authorities and CDEM Groups through the National Warning System. GNS Science also disseminates this information to other agencies, the public, and the media (Scott and Travers 2009).

New Zealand's first VAL system (known as the 'Scientific Alert Level' or SAL table;

<footnote n="3">³GeoNet News web page can be found at: http://info.geonet.org.nz/.</footnote>
Table 2) was introduced in 1994. It was designed by local volcanologists, and included descriptions for different levels of activity for several types of volcanoes, sometimes within a single level of the table. For example, some levels included descriptions for both unrest and eruptions. Later this was to cause confusion as people were not sure which description the assigned VAL referred to.

Several teething issues (including media scrutiny) arose during volcanic unrest at Mt. Ruapehu in late 1994, in part due to the conflicting definitions causing confusion. The original SAL system was therefore reviewed, and a significantly revised and amended version was adopted in September 1995, just one week before the 1995–96 Mt. Ruapehu eruption episode started. The resulting system (Table 3), renamed as the VAL system in 2008, was divided into two separate sections, one for frequently active volcanoes, and the other for reawakening volcanoes. In addition to a level for ‘background activity’ (VAL 0), the frequently active volcanoes system included one level for unrest (VAL 1) and four levels of increasing magnitudes of eruption (VAL 2–5), whereas the reawakening volcanoes system included two levels for unrest (VAL 1 and 2) and three eruption levels (VAL 3–5). The VAL system was used until it was again revised in 2014.

The division of the VAL system based on eruptive activity was deemed to be beneficial during the creation of this system because the outcome of unrest was perceived to be more uncertain for reawakening volcanoes than frequently active volcanoes due to no eruptions being witnessed (except for the 1886 eruption at Okataina). Similarly, calderas (which were predominantly in the reawakening volcanoes group) were seen as more likely to exhibit unrest without resulting in an eruption than stratovolcanoes. Many scientists have the perception that end-users, who are more familiar with stratovolcano eruptions, think unrest will predominantly result in an eruption (Potter 2014). Thus, by separating reawakening volcanoes from frequently active volcanoes, it is implied that the volcanoes behave differently, and that unrest at reawakening volcanoes may not result in an

eruption. An additional level of heightened unrest was inserted into the reawakening system to help reinforce this meaning.

## 2 Reviewing New Zealand's VAL Systems

While the VAL system that was developed in 1995 performed well for fifteen years, it underwent an exploratory review between 2010 and 2014 to ensure it was the best system possible. Potter et al. (2014) used a qualitative ethnographic methodology consisting of interviews, observations and document analysis to investigate the VAL system, with the involvement of both scientist and end-user groups. For further details on the methodology and full results of this research, refer to Potter et al. (2014) and Potter (2014). Based on the results of this research, the VAL system was revised (Fig. 3) and implemented in collaboration with MCDEM on 1 July 2014.

### 2.1 Standardising Multiple Systems into One for All Volcanoes

Many of the research participants identified the division between frequently active volcanoes and reawakening volcanoes in the 1995–2014 VAL system as a concern (Potter 2014). It was recognised that the use of two systems:

* Complicated a system that was intended to be a simple communication tool.

* May cause confusion in the future if two volcanoes exhibiting different levels of surface activity were allocated the same VAL system.

* May cause confusion because as reawakening volcanoes become more active they may switch sides to become frequently active (and vice versa). This was the case in 2006 when an eruption occurred at Raoul Island.

It was undefined whether the volcanoes were grouped according to the time since the last eruption and/or the recurrence rate of eruptions.
<table><caption>**Table 1** The International Civil Aviation Organization (ICAO) Aviation Colour Code for volcanic activity (ICAO 2004)</caption><thead><tr><th>ICAO Colour Code</th><th>Status of activity of volcano</th></tr></thead><tbody><tr><td>Green</td><td>Volcano is in normal, non-eruptive state<br>Or, after a change from a higher alert level:<br>Volcanic activity considered to have ceased, and volcano reverted to its normal, non-eruptive state</td></tr><tr><td>Yellow</td><td>Volcano is experiencing signs of elevated unrest above known background levels<br>Or, after a change from a higher alert level:<br>Volcanic activity has decreased significantly but continues to be closely monitored for possible renewed increase</td></tr><tr><td>Orange</td><td>Volcano is exhibiting heightened unrest with increased likelihood of eruption. Or, volcanic eruption is underway with no or minor ash emission [specify ash-plume height if possible]</td></tr><tr><td>Red</td><td>Eruption is forecasted to be imminent with significant emission of ash into the atmosphere likely<br>Or, eruption is underway with significant emission of ash into the atmosphere [specify ash-plume height if possible]</td></tr></tbody></table>

<table><caption>**Table 2** Scientific Alert Level table introduced in 1994 (sourced from Annex C from the CDEM Plan)</caption><thead><tr><th>Scientific Level</th><th>Phenomena Observed</th><th>Scientific Interpretation</th></tr></thead><tbody><tr><td>1</td><td>Abnormal seismic, hydrothermal or other signatures</td><td>Initial sign of volcano reawakening. No eruption imminent. Possible minor activity</td></tr><tr><td>2</td><td>Increase in seismic, hydrothermal and other unrest indicators. Increase from usual background weak eruptions</td><td>Indicators of intrusion process or significant change in on-going eruptive activity</td></tr><tr><td>3</td><td>Relatively high and increasing unrest shown by all indicators. Commencement of minor eruptive activity at reawakening vent(s) or increased vigour of on-going activity</td><td>If increasing trends continue there is a real possibility of hazardous eruptive activity</td></tr><tr><td>4</td><td>Rapid acceleration of unrest indicators. Established magmatic activity at reawakening vents or significant change to on-going activity</td><td>Hazardous volcanic eruption is now imminent</td></tr><tr><td>5</td><td>Hazardous volcanic eruption in progress</td><td>Destruction within the Permanent Danger Zone (red zone) and significant risk over wider areas</td></tr></tbody></table>

Other criteria for grouping volcanoes were also considered. Options identified included grouping volcanoes by their:

* Type (such as volcanic fields vs. calderas vs. stratovolcanoes)

* Potential size of eruption (however even the most explosive volcanoes predominantly have small eruption sizes)

* Tectonic setting (intraplate vs. subduction zone)

* Typical risk from an eruption (e.g., Auckland Volcanic Field vs. Raoul Island)
<table><caption>**Table 3** New Zealand's VALS used between 1995 and 2014. Reproduced from the MCDEM (2006) Guide to the National CDEM Plan, prior to its 2014 revision</caption><thead><tr><th colspan="3">Frequently active cone volcanoes</th><th colspan="3">Reawakening volcanoes</th></tr><tr><th colspan="3">White Island, Tongariro/Ngauruhoe, Ruapehu, Kermadecs</th><th colspan="3">Northland, Auckland, Mayor Island, Rotorua, Okataina, Taupo, Egmont/Taranaki</th></tr><tr><th>Volcano status</th><th>Indicative phenomena</th><th>VOLCANIC ALERT LEVEL</th><th>Indicative phenomena</th><th>Volcano status</th><th></th></tr></thead><tbody><tr><td>Usual dormant, or quiescent state</td><td>Typical background surface activity, seismicity, deformation and heat flow at low levels.</td><td>0</td><td>Typical background surface activity; deformation, seismicity, and heat flow at low levels.</td><td>Usual dormant, or quiescent state.</td><td></td></tr><tr><td>Signs of volcano unrest</td><td>Departure from typical background surface activity.</td><td>1</td><td>Apparent seismic, geodetic, thermal or other unrest indicators.</td><td>Initial signs of possible volcano unrest. No eruption threat.</td><td></td></tr><tr><td>Minor eruptive activity</td><td>Onset of eruptive activity, accompanied by changes to monitored indicators.</td><td>2</td><td>Increase in number or intensity of unrest indicators (seismicity, deformation, heat flow and so on).</td><td>Confirmation of volcano unrest. Eruption threat.</td><td></td></tr><tr><td>Significant local eruption in progress.</td><td>Increased vigour of ongoing activity and monitored indicators. Significant effects on volcano, possible effects beyond.</td><td>3</td><td>Minor steam eruptions. High increasing trends of unrest indicators, significant effects on volcano, possible beyond.</td><td>Minor eruptions commenced. Real possibility of hazardous eruptions</td><td></td></tr><tr><td>Hazardous local eruption in progress.</td><td>Significant change to ongoing activity and monitoring indicators. Effects beyond volcano.</td><td>4</td><td>Eruption of new magma. Sustained high levels of unrest indicators, significant effects beyond volcano.</td><td>Hazardous local eruption in progress. Large-scale eruption now possible.</td><td></td></tr><tr><td>Large hazardous eruption in progress.</td><td>Destruction with major damage beyond volcano. Significant risk over wider areas.</td><td>5</td><td>Destruction with major damage beyond active volcano. Significant risk over wider areas.</td><td>Large hazardous volcanic eruption in progress.</td><td></td></tr></tbody></table>

* Geographical region (or existing Volcanic Advisory Group).

One VAL system for each volcano was also considered, with the perceived benefit of being locally appropriate. However, this would result in at least 15 systems in New Zealand, most of which require a response by the same group of stakeholders and scientists due to the relatively small population size and land area, and having only one volcano observatory (at GNS Science near the township of Taupo). It is more likely

that having multiple systems in this situation will lead to confusion and mismanagement than in a larger country where separate groups of people are responding to the same, familiar volcano over time. Many participants specifically stated that they would not want the over-complication of having too many VAL systems.

The division of volcanoes into separate VAL systems should be considered very carefully. The need for the VAL system to be used as a simple communication tool very likely outweighs any benefits of multiple tailored and more detailed
<table><caption>**Fig. 3** New Zealand's revised VAL system, which was implemented on 1 July 2014. *Source* Sect. 19 of the Guide to the National CDEM Plan (MCDEM 2015a)</caption><caption>New Zealand Volcanic Alert Level System</caption><thead><tr><th></th><th>Volcanic Alert Level</th><th>Volcanic Activity</th><th>Most Likely Hazards</th></tr></thead><tbody><tr><td rowspan="3">Eruption</td><td>5</td><td>Major volcanic eruption</td><td>Eruption hazards on and beyond volcano*</td></tr><tr><td>4</td><td>Moderate volcanic eruption</td><td>Eruption hazards on and near volcano*</td></tr><tr><td>3</td><td>Minor volcanic eruption</td><td>Eruption hazards near vent*</td></tr><tr><td rowspan="3">Unrest</td><td>2</td><td>Moderate to heightened volcanic unrest</td><td>Volcanic unrest hazards, potential for eruption hazards</td></tr><tr><td>1</td><td>Minor volcanic unrest</td><td>Volcanic unrest hazards</td></tr><tr><td>0</td><td>No volcanic unrest</td><td>Volcanic environment hazards</td></tr></tbody><tfoot><tr><td colspan="4">An eruption may occur at any level, and levels may not move in sequence as activity can change rapidly.</td></tr><tr><td colspan="4">Eruption hazards depend on the volcano and eruption style, and may include explosions, ballistics (flying rocks), pyroclastic density currents (fast moving hot ash clouds), lava flows, lava domes, landslides, ash, volcanic gases, lightning, lahars (mudflows), tsunami, and/or earthquakes.</td></tr><tr><td colspan="4">Volcanic unrest hazards occur on and near the volcano, and may include steam eruptions, volcanic gases, earthquakes, landslides, uplift, subsidence, changes to hot springs, and/or lahars (mudflows).</td></tr><tr><td colspan="4">Volcanic environment hazards may include hydrothermal activity, earthquakes, landslides, volcanic gases, and/or lahars (mudflows).</td></tr><tr><td colspan="4">*Ash, lava flow, and lahar (mudflow) hazards may impact areas distant from the volcano.</td></tr><tr><td colspan="4">This system applies to all of New Zealand's volcanoes. The Volcanic Alert Level is set by GNS Science, based on the level of volcanic activity. For more information, see geonet.org.nz/volcano for alert levels and current volcanic activity, gns.cri.nz/volcano for volcanic hazards, and getthru.govt.nz for what to do before, during and after volcanic activity. Version 3.0, 2014.</td></tr></tfoot></table>

VAL system. For these reasons, the revised VAL system was designed to be used for all of New Zealand's volcanoes, regardless of factors such as the type, setting, frequency of eruptions, or typical eruption style.

The foundation of the VAL system was also explored in order to determine how the level of volcanic activity could best be communicated (Potter et al. 2014). The 1995–2014 VAL system was based on the severity of the volcano phenomena (e.g., magnitude of eruption); it ranged from ‘background activity’ to ‘large hazardous eruption’. The perceived benefits of this foundation included:

(a) Scientists were most knowledgeable and “comfortable” in determining the severity of phenomena, as opposed to considering other

elements of risk. This would lead to less uncertainty and shorter warning times.

(b) The severity of phenomena was seen as the first step in communication, and as being more relevant for a wider range of stakeholders. Interpretation and forecasting information can subsequently be tailored to various audiences, environments, and situations in other communication products.

Various other foundations were considered, including: the level of hazard (taking into account the geological and recent eruptive history of a volcano and spatial extent of hazards, but not the exposure and vulnerability of populations); volcano processes and state of the underlying magma system (ranging from ‘no magma’ to ‘large extrusion of magma’); the level
of risk (taking into account the severity of the hazard as well as the exposure and vulnerability of populations); or a combination of factors (e.g., focussing on the phenomena during unrest and then on the spatial extent of hazards during eruptions). Research participants were asked for their preference of these options; scientists preferred the phenomena-based system, while stakeholders were more evenly spread but had a slight preference for a combined foundation. They also suggested other types of VAL systems, particularly retaining a phenomena-based system that also included hazard information. As stated by a stakeholder in the CDEM sector:

> The phenomenon-based system helps me understand what is going on and the relative severity of the event. The hazard-based system sets out clearly what needs to be done as a consequence. In terms of my CDEM responsibilities, we need both—people get twitchy about instructions given without context and justification.

During the final feedback process, this phenomenon foundation system accompanied by hazard information was found to be useful and acceptable for all of New Zealand's volcanoes in their varied risk environments.

### 2.1.1 Other Considerations When Standardising the VAL System

Very careful consideration was given to all words in the VAL system (Fig. 3) by its developers (Potter 2014; Potter et al. 2014). Not only did it need to be effective during escalation, de-escalation and static levels of volcanic activity, it also needed to be appropriate for the wide range of volcano types and settings in New Zealand. For example, the term ‘vent’ was used in VAL 3 in the hazard column instead of ‘crater’ because some volcanoes have very large craters (e.g., Taupo), or an eruption may occur from a vent on a volcano flank. The use of ‘vent’, ‘near volcano’ and ‘beyond volcano’ is part of the introduction of a dimensionless nomenclature to the VAL system.

No eruption forecasting language was included in the VAL system (beyond ‘potential for eruption hazards’ in VAL 2), because the capabilities and

experience of the volcanologists in forecasting at each of New Zealand's volcanoes is unequal. The use of each phenomena-based alert level would be restricted by the associated description of the expected future activity, which at some of New Zealand's volcanoes, will be very uncertain. For example, if statements such as 'eruption expected within the next two weeks' were included in VAL 2, volcanologists would not be able to communicate that a volcano was showing heightened levels of unrest unless they also thought that an eruption was expected within the next two weeks. Forecasting information specific to each volcano is instead included in supplementary information, particularly Volcanic Alert Bulletins (VABs).

Because the VAL system needs to be standardised for use at multiple volcanoes, the wording needed to be very simple. Therefore, terms such as ‘minor’, ‘moderate’ and ‘major’ volcanic eruption needed to be defined in order for scientists to use the system consistently between volcanoes, between each other when voting on the VAL, and over time. A GNS Science guideline document has been drafted for this purpose with examples of typical activity shown at each VAL by various volcanoes. This approach was taken rather than describing monitoring criteria thresholds (e.g., rate of earthquakes or rate of deformation), to ensure the system can be used for every volcano regardless of its setting, and to give the scientists more flexibility. A GNS Science YouTube video<fnref n="4" /> was developed to help communicate the typical levels of activity for each of the VAL systems to the public and stakeholders.

## 3 Lessons Learnt from the NZ Case Study in Relation to the Standardisation of VAL System

When considering whether to utilise a standardised warning approach, Potter et al. (2014) explored the purpose of the VAL system, the information needs of New Zealand's

<footnote n="4">⁴www.youtube.com/watch?v=WeZxW2xyam0&list=UUTL_U_K1eP4T885-JL3rVgw, accessed on 11 May 2017.</footnote>
stakeholders, and the capabilities of the volcano
monitoring system. They paid particular attention
to the benefits and challenges of combining
warning systems for all of the volcanoes into
one. This included determining the foundation of
the VAL system, the words used in the table,
whether forecasting language should be included,
and how the system was going to be used con-
sistently over time and at multiple volcanoes. As
identified by the IDNDR Early Warning Pro-
gramme Convenors (1997), locally appropriate
communication methods should be established
for the distribution of warnings. The social sci-
ence research used for this investigation was a
robust process that enabled the revision of the
VAL system to be based on evidence, as advo-
cated by Leonard and Potter (2015). The result-
ing VAL system has been used for all of New
Zealand's volcanoes since June 2014. It has
worked satisfactorily to date. For example, vol-
canic unrest or eruptions with which the revised
system has been successfully used have included:
unrest at Ngauruhoe (VAL raised to 1 and later
lowered); decrease in unrest at Te Maari (VAL
lowered to 0); and small eruptions at White
Island (VAL raised to 3 and lowered later).
Volcanologists at GNS Science have found the
simple descriptions in the revised VAL table
beneficial for allowing flexible decision-making
when determining the level of activity. Having
just one system for all NZ volcanoes has also
improved clarity. Regular evaluations of this
warning tool will take place in the future,
involving stakeholders, volcanologists, and the
public. There is more monitoring data and
interpretation relevant to end-users and decisions
than the VAL itself and in New Zealand such
information is included in the accompanying
VAB. Based on the recent experiences with
review and implementation of New Zealand's
VAL systems, we strongly recommend stake-
holders consider exactly what parameters,
impacts, uncertainties and lead-times are impor-
tant to each decision that needs to be made (e.g.,
evacuation) and not simply tie responses to
changes in the VAL.

The revised VAL system has been developed
for the New Zealand context, including our

volcanic settings and risk environments, the roles
and responsibilities of our agencies, and our
social and cultural environments including the
centralised nature of our volcano monitoring and
warning system. As such, it is unlikely that it is
able to be directly copied for other countries.
However, the process that we followed can be
used, as summarised in the next section.

4 Recommendations for Reviewing or Developing a VAL System

This chapter has focussed on aspects relating to
standardisation, when reviewing a VAL system.
There are other considerations to take into
account as well. We describe below our recom-
mended processes and considerations when
reviewing a VAL system (or developing a new
one), based on our research and experience.

(1) Understand the context

It is vital to understand the physical, cultural,
social, organisational and historical context of the
VAL and related systems. Potter et al. (2014)
found that using the qualitative methodology of
ethnography allowed a deep understanding of the
culture of the volcanologists to be built to address
many of the following factors. However, we
recognise that this is a time-consuming process
that is not an option for many observatories
looking to revise their VAL systems. If this is the
case, then drawing on published material, attend-
ing volcano monitoring meetings, and holding
discussions with those familiar with the various
environments should be sufficient. We recommend
understanding as much as possible about the:

* Range of potential volcanic activity at every volcano that the VAL system may be used for, including frequency of eruptions, level of ongoing unrest or eruptions, potential magnitude of eruptions (and unrest phenomena), and severity of all possible hazards.

* Volcano monitoring system to understand capabilities and factors such as timing, uncertainties and content of incoming data.
* Level of exposure and vulnerability of elements at risk to volcanic hazards, including the built, social, economic and natural environments.

* Roles and responsibilities, including legislative requirements, of scientific advisors from all institutions, and organisations with the role of planning, education, response and recovery from volcanic events (including governmental and civil defence agencies, infrastructure/lifelines, emergency services, health, agricultural/horticultural and business sectors). For example, understand which agencies have the responsibility to communicate directly to the public.

* Influences on the VAL decision-making process. This includes understanding the cultures of people/groups determining the VAL system, and the receivers of the information including decision-makers and stakeholders, and the public. For example, influences on the VAL decision-making process may include experience, external pressure, peer pressure and other social psychology biases, internal voting guidelines, how individuals interpret the content and structure of the VAL system, and the desire to maintain credibility or conduct fieldwork (Potter 2014). Factors such as these contributed towards the design of the revised NZ VAL system. Additionally, understanding the way stakeholders read volcano-related information and use it in their decision-making contributed towards determining what information was included in the NZ VAL system, how it is communicated to them.

* Previous VAL systems, and any other existing alerting systems for volcanic or other hazards used in the country or for the volcano in question. What were people's experiences with those systems? What worked well or didn't work well? Are there any other warning systems being used on or near the volcano, including the international ACC? Understanding VAL systems that have been implemented in other parts of the world is also useful. Being familiar with the challenges and benefits of standardisation as

outlined in this chapter is relevant for this point.

* What other communication avenues exist for related information from all agencies? For example, Volcanic Alert Bulletins, phone calls, meetings, websites, emails, social media. These provide the context of whether the VAL system will need to include all important information as a standalone system, or if it can be supported by other channels.

## (2) Understand the challenges and benefits of the existing VAL system

It is important to know who the audience is for the VAL system, and what they use it for. If the system is targeted at stakeholders and decision-makers, perhaps more technical and specific information could be included than if the audience includes the public. This information might also inform the position of the divisions between alert levels by matching it to their decision-making needs. However, due to the wide range of stakeholder needs and the differing points at which they need to take action, coupled with a system that communicates to multiple audiences, it is likely that discussions will need to be held to encourage stakeholders to determine their own decision points, rather than them relying on changes in alert levels. Understand their perception of the purpose of the VAL system, and their experiences with any existing VAL systems, through methods such as interviews, open-ended questions in surveys, or workshops/focus groups. Ask the volcanologists (or whomever determines the VAL) what they find useful or challenging, and see if their perceived purpose of the system matches that of the stakeholders/public. Analyse the existing system to identify jargon, unclear meanings, and the foundation of the system. Understand what channels are used to communicate it (such as websites, social media, Bulletins), as this may pose opportunities or limitations in designing a revised system. Ask all parties what they would like to see in a revised system. Determine factors
such as whether it should include eruption forecasting messages, what its foundation should be based on, and whether it is a standardised system for multiple volcanoes, or specific to a single volcano.

### (3) Produce a draft version of the revised VAL system and seek feedback

By considering the context, and collating the information outlined in step 2, recommendations for a revised system can be developed. Based on those recommendations, a draft version (or multiple options) can be developed. Both the summarised findings and the draft(s) can then be circulated back to participants to ensure their perceptions and needs have been accurately captured. For the NZ revision, Potter (2014) asked participants to rank five draft versions, which helped to determine the most appropriate foundation and structure of the revised VAL system. Multiple iterations then occurred to produce the final version. Do not underestimate the amount of time needed for this process! A final version of the VAL system can now be developed (consider utilising graphics specialists).

### (4) Release revised system in collaboration with stakeholders

In conjunction with key stakeholders, determine a date on which the new system will be used, taking into account the length of time all parties need to update documentation, websites, etc. Release communications to circulate the change in VAL system through the media, stakeholder newsletters, meetings, etc. In NZ, GNS Science developed a media release six weeks prior to the start date of the system, and on the day of the changeover, with support from MCDEM. Make a plan for if a new eruptive episode should start close to the changeover date (thankfully no eruptions occurred for the changeover date in NZ!). Write any supporting documentation or procedures, such as a guideline for consistent use by the volcanologists, or whether

the VAL system will be used exactly as written or more flexibly.

### (5) Evaluate the revised VAL System

Conduct regular evaluations to ensure the revised (or new) VAL system is effective, and meeting the needs of stakeholders, the public, and volcanologists. Real events and exercises can be used.

## 5 Volcanic Crisis Communication

Warnings about natural hazard events are communicated in order to minimise losses (Newhall 2000). However, trust and communication networks must already be in place prior to a crisis for effective planning and response. This can be achieved by developing networks, ascertaining information needs and establishing methods of effective communication (Paton et al. 1998). VAL systems are just one aspect of an EWS, and by design are the simplest tool to communicate the status of the volcano (or level of response required, etc.). Due to this overarching purpose, standardising VAL systems can help ensure a consistent, simple, and understandable design. As we have outlined in this chapter however, there are issues with using a one-size-fits-all communication product. This was also identified by Thompson et al. (2015) in using probabilistic volcanic hazard maps. We found that taking into account the local context is vital, which supports the findings of numerous recent research in volcanic crisis communication (Haynes et al. 2007; Fearnley et al. 2012; Potter et al. 2014). Providing supporting information using other means helps to alleviate these issues.

Over the past two decades, social science has increasingly played a valuable role in mitigating volcanic risks by providing evidence-based links between communities, stakeholders and scientists (Barclay et al. 2008; Leonard and Potter 2015). We recommend that in the future these robust methodologies are embraced by volcano observatories, such as when revising
communication strategies and products, to help effectively share information and reduce the risk to society.

**Acknowledgements** The authors would like to thank all research participants, supervisors and colleagues for their contribution to this research. The research was primarily funded by the Government of New Zealand through the Natural Hazards Research Platform, and through the Earthquake Commission.

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holder.
More Than Meets the Eye: Volcanic
Hazard Map Design and Visual
Communication

Mary Anne Thompson, Jan M. Lindsay
and Graham S. Leonard

Abstract

Volcanic hazard maps depict areas that may be affected by dangerous
volcanic processes, such as pyroclastic density currents, lava flows, lahars,
and tephra fall. These visualisations of volcanic hazard information are
used to communicate with a wide variety of audiences both during times
of dormancy and volcanic crisis. Although most volcanic hazard maps
show similar types of content, such as hazard footprints or zones, they
vary greatly in communication style, appearance, and visual design. For
example, maps for different volcanoes will use different combinations of
graphics, symbols, colours, base maps, legends, and text. While this
variety is a natural reflection of the diverse social, cultural, political, and
volcanic settings in which the maps are created, crises and past work
suggest that such visual design choices can potentially play an important
role in volcanic crisis communication by influencing how people
understand the hazard map and use it to make decisions. Map reading is
a complex process, in which people construct meaning by interpreting the
various visual representations within the context of their information
needs, goals, knowledge, and experience. Visual design of the map and
the characteristics of the hazard map audience can therefore influence how
hazard maps are understood and applied. Here, we review case studies of
volcanic crises and interdisciplinary research that addresses the relation-
ship between hazard maps, visual design, and communication. Overall,

<footnote>M.A. Thompson (✉) · J.M. Lindsay
School of Environment, University of Auckland,
Private Bag 92019, Auckland, New Zealand
e-mail: m.thompson@auckland.ac.nz</footnote>

<footnote>J.M. Lindsay
e-mail: j.lindsay@auckland.ac.nz</footnote>

<footnote>G.S. Leonard
GNS Science, P.O. Box 30-968, Lower Hutt 5040,
New Zealand
e-mail: g.leonard@gns.cri.nz</footnote>
this growing body of work suggests that volcanic hazard maps can be very useful visual tools for crisis communication if they are designed in a way that provides clear and useful information for the audience. Further, while it is important that each map is designed for its unique situation and setting, engaging with hazard map audiences to better understand their information needs and considering lessons learnt from interdisciplinary work on visual communication can help inform and guide knowledge exchange using maps.

# 1 Introduction

As a volcanic crisis begins to unfold, demand for information about when and where dangerous volcanic hazards might impact increases. A key medium for communicating this information is a volcanic hazard map—a visual, spatial depiction of where volcanic phenomena might occur within a certain time frame. While hazard maps play a role in managing many elements of a volcanic crisis, such as understanding relationships between hazards, identifying areas of potential danger, informing risk assessments, and planning evacuation routes, they serve as an important tool in crisis communication.

We live in an increasingly visual society, where most of us see and process images more than we read words (Lester 2014). In many cases, images can attract visual attention (Carrasco 2011), trigger information-processing (Domke et al. 2002), stimulate emotional response (Mould et al. 2012; Lester 2014), and influence decision-making (Tufte 1997; Daron et al. 2015) more than other types of media. Images can be concisely delivered in many different formats, through many different channels, and can communicate across lexical and linguistic boundaries. Hazard maps are common images used by scientists to communicate information about volcanic hazards with a wide range of audiences. These maps, and the inferences and responses that they elicit, become particularly important during crisis situations when they may become read and circulated widely. During such high-stakes, high-pressure situations, people tend to rely more

on their initial impressions and intuitive feelings about hazard and risk than on exhaustive analytical evaluation of hazard and risk information (Finucane et al. 2000). Accordingly, the way that a hazard map captures visual attention and conveys affective meaning could have a significant impact on decisions made during a volcanic crisis. It is therefore important to understand how people interact with hazard map images, and how visual communication processes influence the messages that audiences take away.

Volcanic hazard maps are created by scientists across the world, using a number of different types of datasets, methodologies, and approaches (Calder et al. 2015). For example, a map could show only one volcanic hazard (e.g., ash fall), or multiple volcanic hazards (e.g., ash fall, lava flow, and ballistic ejecta). These hazards may be depicted as intensities (e.g., centimetres of ash that are likely to accumulate) or as a set of nested or cumulative zones (e.g., high, medium, and low hazard zones). The hazard map may be based on observation of past volcanic hazard deposits, probabilistic hazard modelling, simulation of a particular hazard scenario, or information drawn from an analogue volcano. The high degrees of freedom mean that volcanic hazard maps can represent many different types of information. In reviewing 120 volcanic hazard maps from around the world, Calder et al. (2015) identify five different hazard map “types” which describe these various combinations: geology-based maps, integrated qualitative maps, administrative maps, modelling-based maps, and probabilistic maps (Fig. 1). The classification provides a way to categorise and consider the types of
inputs used in developing volcanic hazard maps around the world. The way that these inputs are visualised into a final map design output are similarly diverse.

Volcanic hazard maps are traditionally created by the scientists who carry out volcanic hazard assessments. Visual design of a hazard map is therefore typically governed by factors such as the specific methodology used, common scientific and cartographic practice at the time, status of volcanic activity, social and cultural setting, and local agency standards or policy requirements in place. Variation in these factors over time and place has resulted in the vastly different layouts, formats, colour schemes, data representations, symbology, and hazard map styles being

used around the world today. While this visual diversity reflects important and unique differences in map purpose and social and volcanic setting, past crises and research over the last few decades have highlighted that such visual design choices can also carry great importance for communication, as they may influence how different audiences interpret the map and use it to make decisions regarding hazard and risk.

Maps communicate more than meets the eye. Each reader individually constructs meaning from the map through visual cognition and interpretation of the various symbols, colours, shapes, and text within the context of his or her prior knowledge and experience (MacEachren 1995; Perkins et al. 2011). Map reading is thus a

<figure><img src="image_197.png" /><figcaption>**Fig. 1** Hypothetical examples of the five types of volcanic hazard map identified by Calder et al. (2015). Each map type represents a different type of input information: a geology-based maps, the most common type of volcanic hazard map, are based on hazard footprints of past events; b integrated qualitative maps are based on amalgamation of many different types of</figcaption></figure>

hazard information; c modelling-based maps are based on simulation of certain hazard scenarios; d probabilistic maps are based on probabilistic assessment of hazards; and e administrative maps are based on both hazard information but also on emergency management and administrative information. Modified from Calder et al. (2015)
complex information-processing exercise, and visual design and audience background can have a strong effect on the messages that people take away (Robinson and Petchenik 1976; Bertin 1983; MacEachren 1995; Monmonier 1996; Lloyd 2011; Perkins et al. 2011). During a crisis, hazard maps can become widely distributed and used for communicating with many different audiences. In these rapid mass communication contexts, audiences may not always consult supporting resources beyond the map image itself (e.g., Leonard et al. 2014). In such contexts, it is important to consider how visual design and communication factors influence hazard map reading, knowledge exchange, and decision-making. Here, we draw upon case studies and past work to review how volcanic hazard maps are used to visually communicate with difference audiences, and how visual design plays a role in this communication.

## 2 Visual Communication

Volcanic hazard maps synthesize a wealth of information about individual processes and interdependent phenomena over a range of spatial and temporal scales. As with all cartographic representations, a number of generalisations therefore have to be carried out in order to visually communicate this complex data in a clear and concise way in two dimensions. This often requires simplifying complicated physical and numerical concepts, such as particle and flow dynamics and probabilistic uncertainty. Deciding upon the most salient and useful content, and the clearest and simplest way to display that content, is a challenging, but important task. Highly complex maps are often difficult for most audiences to understand (MacEachren 1982). However, past crises and work have shown that engaging with audiences to understand the way that they perceive hazards can help guide generalisation of complex content and inform communication approaches.

## 2.1 Communicating Complex Content

On 13 November 1985, after a year of awakening, but with little short-term warning, the ice-capped volcano Nevado del Ruiz erupted. The eruption sent devastating lahars—turbulent mixes of snow, ice, meltwater and pyroclastic debris—down valleys and channels to the Colombian town of Armero, causing one of the worst volcanic disasters in history (Pierson et al. 1990). The Nevado del Ruiz tragedy was the result of a complex interplay between a number of technological, political, and social circumstances (Voight 1990). However, retrospective accounts recall the “state of frustration and confusion” (Voight 1990, p. 180) that arose from a “poorly understood” (Parra and Cepeda 1990, p. 117) hazard map (Fig. 2a). Although a revised hazard map was being prepared, the lahars struck two days before the planned release of the new map. Although the available map showed overall accurate content, it was displayed using scientific and probabilistic concepts that were unfamiliar to many map audiences, leading to miscommunication among authorities, the media, and the public (Parra and Cepeda 1990; Voight 1990).

In 1990, the post-event hazard map was simplified by replacing individual probabilistic hazard paths with generalized hazard zones (high, moderate, and low) (Parra and Cepeda 1990). The revision aimed to develop a map that was “easily comprehensible to non-specialists and therefore less susceptible to misinterpretation” (Parra and Cepeda 1990, p. 117). Today, the most recent Nevado del Ruiz hazard map (SGC 2015; Fig. 2b) continues this generalisation approach. Efforts to design an “intuitive” (Parra and Cepeda 1990, p. 117) map for non-scientific audiences acknowledged the important crisis communication role of volcanic hazard maps and brought attention to the importance of considering audience perspectives in designing maps. The experience led to reflection about hazard map design in other volcanically active parts of
<figure><img src="image_198.png" /><figcaption>(b) Nevado del Ruiz hazard map 2015</figcaption></figure>

<figure><img src="image_199.png" /></figure>

**Fig. 2** Evolution of the volcanic hazard map for Nevado del Ruiz, showing a a simplified black-and-white version of the hazard map that was available during the time leading up to the November 1985 crisis (modified from

Parra and Cepeda 1990), and b the current, revised hazard map produced by the Colombian Geological Survey in 2015 (SGC 2015)
the world. For example, Nakamura et al. (2008) note that the crisis sparked an evaluation of Japanese volcanic hazard maps, resulting in a design change “from being specialist-oriented to being designed to be more easily understood” (p. 297).

The value of having simple and clear hazard maps for use in crisis communication has emerged in a number of other volcanic crises, including the eruption crisis on the Caribbean island of Montserrat. On 18 July 1995, a small phreatic explosion on Soufrière Hills volcano marked the start of an eruption that would go on to continue for nearly two decades. Episodes of andesitic dome-building and collapse produced rapid, hot pyroclastic flows that devastated nearly two-thirds

of the island (Aspinall et al. 2002). The people of Montserrat were badly affected by the disaster. More than 90% of the population was displaced, and communities suffered ongoing distress and uncertainty (Kokelaar 2002; Sword-Daniels et al. 2014). Over the course of the eruption, hazard maps and risk management maps were widely used in communication with authorities and local communities (Aspinall et al. 2002).

In an effort to minimise disruption and keep as much land open to utilisation as possible, early maps used a microzonation approach, where the island was divided into seven different zones reflecting gradual levels of risk, from A (more risk) to G (less risk) (Aspinall et al. 2002; Kokelaar 2002; Fig. 3a). Microzones were tied to

<figure><img src="image_200.png" /><figcaption>(b) Revised Montserrat map
September 1997</figcaption></figure>

<figure><img src="image_201.png" /><figcaption>(c) Examples of aerial and perspective photos of Montserrat tested in Haynes et al. (2007)</figcaption></figure>

<figure><img src="image_202.png" /></figure>

<figure><img src="image_203.png" /></figure>

**Fig. 3** Black-and-white versions of maps used to communicate with the public during the Soufrière Hills eruption crisis on Montserrat in a November 1996 and b September 1997 (modified from Kokelaar 2002); and

c examples of the aerial and perspective photographs of Montserrat, which were easier for participants to read and use than plan view maps (modified from Haynes et al. 2007)
access restrictions, which varied based on changes in an associated volcanic alert level system. However, the complex maps, together with their dynamic relationship to alert levels, were sometimes found to be “difficult to communicate to the public” (Kokelaar 2002, p. 12). Alert levels alone can be complex concepts to communicate (Fearnley et al. 2012; Potter et al. 2014). Recognising a need to simplify the maps for visual communication purposes, later versions of the map (September 1997 onwards) generalised the microzones into two to three larger zones representing different levels of access, including an exclusion zone around the volcanic edifice (Fig. 3b). The responsive change illustrated an audience-driven shift in map design, but also highlighted the challenges associated with communicating complex and interdependent content about hazard and risk.

While the Montserrat experience highlighted the importance of considering how key volcanic hazard and risk information is generalised and displayed on a map, Haynes et al. (2007) found that other fundamental elements of hazard map design can also play a role in crisis communication. Haynes et al. (2007) developed several different versions of the Montserrat hazard and risk maps that utilised a variety of different visual formats. They found that visual design elements, such as the choice of base map, influenced how local audiences used and understood the information. For example, participants were able to better identify spatial features and orient themselves with the information when it was portrayed on aerial or perspective photographs (Fig. 3c). While plan view or topographic contour maps may be an intuitive choice for an earth scientist, it may not be the most suitable choice for communicating spatial hazard information with other audiences (Haynes et al. 2007). Nave et al. (2010) found similar results in a study of Stromboli volcano hazard map styles, recommending plan view contour hazard maps for government officials, but perspective displays for non-specialist audiences. Collectively, these, and many other past volcanic crises have contributed valuable knowledge about the ways that different

audiences respond to certain hazard visualisation approaches and how this may influence crisis communication efforts.

## 2.2 Considering Audience Perspectives

In order to share valuable and useful knowledge about a hazard or risk with an audience, it is first important to understand the audience's existing knowledge and perspectives regarding the hazard or risk, and what information is valued and needed (Bostrom and Löfstedt 2003; Perry et al. 2016). The way that different audiences perceive volcanic hazard and risk can have an important influence on how they respond to hazard and risk communication efforts (Johnston et al. 1999; Paton et al. 2008; Gaillard and Dibben 2008; Doyle et al. 2014). Engaging with hazard map audiences to better understand their existing knowledge and perceptions of volcanic hazard and risk can therefore help guide and inform approaches to hazard and risk communication, including hazard map design. Integrative engagement with audiences can also facilitate constructive dialogue about volcanic hazards and help engender trust in the resulting maps and communication products (Cronin et al. 2004; Haynes et al. 2008; Leone and Lesales 2009; Pierson et al. 2014).

Audience perception of volcanic hazards played a key role in the redesign of the volcanic hazard maps for Mt. Ambae, the largest active volcano of the Pacific island nation of Vanuatu. Cronin et al. (2004) found that the existing scientific volcanic hazard map (Fig. 4a) was poorly understood by most people living near the volcano because of differences in the ways that the scientists and local communities perceived hazardous volcanic phenomena. In order to create a hazard map design which better aligned with audience perspectives, the scientists engaged with the local communities to better understand how locals viewed and conceptualised volcanic hazard. The hazard map was then revised to assimilate both local and scientific worldviews. For example, while scientists and locals believed the
(a) Mt. Ambae volcanic hazard map 1995

<figure><img src="image_204.png" /></figure>

(b) Revised Mt. Ambae hazard map Cronin et al. 2004

<figure><img src="image_205.png" /><figcaption>**Fig. 4** Volcanic hazard maps for Mt Ambae. **a** The former scientific-style hazard map (modified from Monzier and Robin (1995)), and **b** The revised hazard map, which was developed through engagement with</figcaption></figure>

communities, and represents an integration of both local, traditional perspectives and outside, scientific perspectives (modified from Cronin et al. 2004)

summit area of the volcano was dangerous for different reasons, both groups acknowledged that the summit crater was a highly dangerous place. Similarly, although the scientists and locals believed in different causes of lahars, valleys were seen as particularly dangerous areas by both

groups (Cronin et al. 2004). The resulting map (Fig. 4b) represents a visual integration of both traditional and outside scientific worldviews about hazardous volcanic areas, and is an example of how engagement can help achieve common ground for visual communication.
While technical scientific hazard maps are still an essential tool for certain specialist tasks and stakeholders, different types of hazard map content may be prioritised for communication with other audiences who visit, work, and live in volcanic areas. For example, engagement with audiences in outdoor recreation areas near volcanoes in New Zealand and the United States has led to an emphasis on including life safety advice on volcanic hazard maps to share knowledge about what to do in the event of volcanic activity. Ruapehu is an active volcano in New Zealand with ski fields located on its summit and flanks. Annual engagement with audiences on the ski slopes has been used to guide visual design and content of the volcanic hazard map posters displayed in ski areas on Ruapehu (Leonard et al. 2008). The hazard maps are tailored specifically for winter sport audiences, illustrating valley areas exposed to lahar hazard and providing advice about how to evacuate valleys in the event of an eruption. Engagement with local audiences also led to integration of preparedness and evacuation advice into large interpretive outdoor signs about volcanic hazards for volcanoes of the Cascade Range in the United States, such as Mount Baker, Glacier Peak (Eske et al. 2015), and Mount Rainier (Schelling et al. 2014) (Cadig et al. *this volume*, Driedger et al. *in prep*). Combining volcanic hazard maps with supporting information about hazard phenomena and advice for increasing personal response capacity may encourage engagement and elaboration with hazard map information among some audiences (Paton 2003; Rakow et al. 2015). Although engaging with audiences can be time and resource intensive, carrying out work to understand audience perspectives in times of dormancy may prove useful in times of crisis communication.

In 2012, consideration of audience communication needs became a key consideration during response to the Te Maari eruption crisis at the Tongariro Volcanic Centre (TgVC) in New Zealand. While the Te Maari eruption was altogether small in scale, consisting of two phreatic explosions several months apart (Jolly et al.

2014a), it generated a high level of stress and uncertainty surrounding a potential increase in volcanic risk. The eruption vents were located within 2 km of New Zealand's most popular day track, the Tongariro Alpine Crossing, which averages up to 1500 visitors a day during the peak summer season. The TgVC is also a complex stratovolcano system capable of much larger, sub-Plinian eruptive activity (Moebis et al. 2011; Jolly et al. 2014b). While there was an existing series of background hazard maps that were designed for communicating with non-specialist audiences (Fig. 5a) (Leonard et al. 2008, 2014), the eruption meant that a new, event-focussed, crisis hazard map needed to be developed rapidly in order to provide information and life-safety advice directly related to the activity unfolding at the Te Maari vents (Fig. 5b).

Developing an audience-focussed hazard map under the stress and time pressures of a crisis situation was complex and taxing. Leonard et al. (2014) note that between the first and second versions of the map “at least 147 emails were sent by 23 different people across 9 different agencies and groups over a 24 day period” (p. 219). These numbers reflect the high level of engagement and interaction between various groups involved in management of the crisis, but also the complicated nature of rapidly compiling, synthesizing, and deciding on the content, messaging, and design of a hazard map during a crisis. The rapid, high-stakes nature of volcanic crises means that there are often limited resources to dedicate towards revising hazard map design during an actual event. During the Te Maari crisis, the relationships formed through past engagement were valuable in facilitating map development and design (Jolly et al. 2014b; Leonard et al. 2014). For example, one of the main populations affected by the event was a local indigenous group who provided valuable feedback into the final map design style (Leonard et al. 2014). In addition, the team relied heavily on resources that had been pre-prepared, emphasising the value in planning and considering approaches to map design during times of dormancy.
<figure><img src="image_206.png" /><figcaption>(a) Background hazard map TgVC 2005</figcaption></figure>

**Fig. 5** Tongariro Volcanic Centre volcanic hazard maps for a typical background levels of activity (GNS Science 2005) and b during the Te Maari eruption crisis in 2012 (GNS Science 2012). Background hazard maps are long-term maps that are used to communicate potential

<figure><img src="image_207.png" /><figcaption>(b) Crisis hazard map Te Maari 2012</figcaption></figure>

hazards during times of volcanic dormancy, while crisis hazard maps are temporary event-specific maps that are developed in response to imminent hazards (modified from Leonard et al. 2014)

A number of lessons regarding crisis hazard maps emerged from the Te Maari experience, including the value of using version numbers, disclaimers, and providing metadata, and these are put forth as a set of recommendations by Leonard et al. (2014) (p. 225). In this list, they note the importance of considering the visual design of the map image itself. While the map images were presented with legends, descriptive text, and explanatory information, a number of media outlets clipped away this accompanying documentation and context when circulating and disseminating the map. Accordingly, in some cases, interpretation of the hazard map information relied almost wholly on the map image alone (Leonard et al. 2014).

## 3 Visual Design

Communicating with map images relies on visual perception and cognition. The map reader's eyes must sense and interpret visual variables such as

shape, size, colour, texture, and orientation, and then cognitively process this information to create meaning (Bertin 1983; MacEachren 1995; Perkins et al. 2011). Well-designed visualisations can augment and enhance this cognitive processing by reducing cognitive load and facilitating inductive reasoning (Hegarty 2011; Patterson et al. 2014). Accordingly, visual map products have been found to improve comprehension of hazard information when compared to non-visual communication formats such as text and tables (Severtson and Vatovec 2012; Cheong et al. 2016; Cao et al. 2016). However, there are many variables to consider when visually designing a map, and it can often be difficult to determine which combination of variables will support cognition and reasoning. Further, map designs which are aesthetically appealing or intuitively preferred by map makers and users are not necessarily the most effective for decision-making tasks (Hegarty et al. 2009; Mendonça and Delazari 2014). Engaging with map audiences and carrying out empirical research into how people
read and process map information can help confront these challenges by giving insight into the ways that different variables in visual design influence communication and decision-making. In addition, experimenting with innovative map visualisation formats can help also help create new ways of capturing audience attention and facilitating engagement with hazard information.

## 3.1 Exploring and Testing Different Designs

Research surrounding information visualisation is carried out in many different disciplines, including human computer interaction, human factors, cognitive psychology, semiotics, visual analytics, graphic design, cartography, and geo-visualisation. Across these fields, a simple method used for evaluating the effectiveness of visual designs is to test how audiences perform in task-based exercises using different visualisations. However, in order to test effectiveness, a defined, measurable communication goal needs to be identified (MacEachren 1982), and in the case of volcanic hazard maps, this can often be multidimensional and nuanced. Accordingly, Haynes et al. (2007) propose a mixed methods approach for evaluating volcanic hazard map design that combines quantitative performance evaluations with qualitative investigations. Using this approach, Haynes et al. (2007) were able to capture the complexity of how local audiences engaged with volcanic hazard and risk maps on Montserrat.

Thompson et al. (2015) adopted a similar mixed methods approach to explore the influence of visual design on volcanic hazard map communication in New Zealand. Thompson et al. (2015) took one dataset, which showed the probability of accumulating volcanic ash in the event of a hypothetical eruption, and displayed it using several different visual design variables. More than 100 scientists and organisational stakeholders (e.g., emergency managers, government officials) in New Zealand responded to

quantitative and qualitative survey questions about the volcanic ash hazard using the different maps. The results showed that changing visual design elements, such as the data classification style or colour scheme, can have a significant effect on the way people understand the hazard. For example, participants were more accurate in quantitatively estimating the average probability of accumulating 1 mm of ash when they used a map that classified hazard data into discrete zones of probability (e.g., 5–14, 15–24 ... 65–75%) compared to a map that classified the data using gradual shading (Fig. 6a, b). Participants were most precise when these two approaches were combined, with discrete probability isarithms (e.g., 15, 25 ... 65%) overlain onto a gradual shading classification (Fig. 6c). Participants also had strong feelings about the user-friendliness of the different maps styles. Map which were easier to read were associated with increased confidence in ability to use and apply the hazard information. The findings suggest that simple choices in data classification could have a significant influence on the way people understand, interpret, and apply probabilistic hazard information (Thompson et al. 2015).

Thompson et al. (2015) also conclude that it is important to consider colour scheme choices when representing volcanic hazard information on a map. Colour is an important visual design variable, which can guide attention, emotional response, and interpretation of map features (Robinson 1967; Bertin 1983; Wolfe and Horowitz 2004). However, the strong connotations and meaning that colours often carry for map readers introduces potential for miscommunication (Monmonier 1996; Brewer 1994). For example, Thompson et al. (2015) found that using a red-to-blue diverging-hue colour scheme (Fig. 7a) communicated a qualitatively different type of message than a red-to-yellow sequential-hue colour scheme (Fig. 7b). Participants tended to make interpretations about hazard state (presence/absence) when reading the diverging colour scheme map, but tended to
<figure><img src="image_208.png" /><figcaption>(b) Binned / Zoned</figcaption></figure>

<figure><img src="image_209.png" /><figcaption>(c) Gradational shading with isolines</figcaption></figure>

<figure><img src="image_210.png" /></figure>

◀ **Fig. 6** Three types of probabilistic volcanic hazard map data visualisations tested by Thompson et al. (2015). Participants struggled to read accurate probability values for the area outlined in *blue* when using *a* a gradational shaded data classification. Participants performed better using *b* a binned (zoned) data classification, and they performed best, with the most accurate and precise estimates of hazard values using *c* gradational shading with isolines. The results suggest that visualisation of hazard data on a map can influence the information that people take away. Modified from Thompson et al. (2015)

make interpretations about hazard degree (less/more) when reading the sequential colour scheme map. In addition, more than two-thirds of survey participants self-reported that the colour scheme influenced the level of hazard they perceived from the map (Thompson et al. 2015).

Similarly, while red-yellow-green “stoplight” colour schemes are applied in a number of volcanic hazard maps around the world, Olson and Brewer (1997) and Jenny and Kelso (2007) warn that red-and-green colour schemes may introduce problems for colour vision deficient map readers. Up to 8% of males have some form of colour-vision deficiency, with difficulty distinguishing between red and green colours being the most common type (Delepero et al. 2005). To this population, the highest (red) and lowest (green) hazard areas may appear the same colour and cause confusion. To assist map makers in choosing appropriate colour schemes for maps, Harrower and Brewer (2003) developed ColorBrewer (www.ColorBrewer.org), a research-backed tool for selecting map colour schemes with appropriate hue, saturation, and contrast to enhance visualisation of map information and prevent potential issues for colour vision deficient users.

Many of the challenges associated with visually designing volcanic hazard maps are faced in other fields of hazard and risk research, such as
<figure><img src="image_211.png" /><figcaption>**Fig. 7** Two hazard map colour schemes tested by Thompson et al. (2015). Participants were more likely to discuss a hazard state (e.g., present or absent) when viewing **a** the *red-to-blue* diverging hue colour scheme,</figcaption></figure>

and were more likely to discuss hazard degree when viewing **b** the *red-to-yellow* sequential hue colour scheme map. Modified from Thompson et al. (2015)

wildfire (e.g., Cheong et al. 2016), hurricane (e.g., Broad et al. 2007; Sherman-Morris et al. 2015), flooding (e.g., Strathie et al. 2015), sea level rise (e.g., Retchless 2014), and health (e.g., Severtson and Myers 2013). For example, researchers have found that visual design of wildfire hazard maps can influence people's interest and engagement with the hazard information and also how they use it to make decisions about evacuation (Cao et al. 2016; Cheong et al. 2016). Similarly, visual design has been found to influence emotional and behavioural responses to tornado warning maps (Ash et al. 2014). Visualising and communicating uncertainty in geospatial data also remains an ongoing challenge across many different fields (Aerts et al. 2003; Spiegelhalter et al. 2011; Kinkeldey

et al. 2014). As work in volcanic hazard map design continues to evolve, it is important to consider lessons learned from research and experience in these diverse fields, and drawn upon them to help inform and guide investigations of volcanic hazard communication.

In addition, contributions from cognitive science research can add new dimensions to understanding how visual design and visual perception of volcanic hazard maps can influence hazard interpretation and decision-making. For example, Hegarty (2011) summarises sixteen “principles of effective graphics” based on decades of cognitive science research into visual-spatial displays. Such principles, such as the relevance principle (Kosslyn 2006), which proposes that visual displays should present no
more or no less information than is needed by the audience, could help inform approaches to visual design of volcanic hazard maps. Investigations of weather map reading performance suggests that considering such graphic principles in map design can affect visual processing of map information (Hegarty et al. 2010; Fabrikant et al. 2010). Similarly, Patterson et al. (2014) propose six “leverage points” for augmenting human cognition through information visualisations, which also are likely to have relevancy for map design. For example, they suggest that certain visual design approaches can help capture visual attention and also guide and focus visual search for information.

## 3.2 Visualising Hazard in Different Formats

Although the 2-dimensional plan view paper map remains a common and useful visualisation method in hazard mapping, volcanic hazard concepts can be mapped and visualised in many other ways. For example, modern geovisualisation and geographic information system (GIS) techniques, such as interactive interfaces (Çöltekin et al. 2009; Roth 2013) will play a significant role in shaping the future of hazard map communication. Interactive and 3D visualisations can add new dimensions to natural hazard and risk maps, through providing location-aware, user-centred data, although further research about these emerging technologies is needed to better understand the way they affect hazard and risk communication (Lonergan and Hedley 2015).

As improved workflows and accessibility of such methods continue to be developed, new opportunities will arise for communicating volcanic hazard in innovative and engaging ways. In a study at Mount Hood volcano in Oregon, USA, Preppernau and Jenny (2015) tested new methods of visualising lahar hazard using 3-dimensional (3D) oblique perspective base maps with isochrones that represented lahar travel time. They found that participants preferred 3D isochrone lahar hazard maps to

traditional plan view contour maps, and that participants' performed better in interpreting terrain and evacuation routes with the 3D displays. Recent advancements in visual technology, such as eye-gaze trackers (devices that can be used to record a readers' eye movement across a visual or graphic), can also enable new forms of insight into map reading behaviour, visual attention, and understanding (e.g., Çöltekin et al. 2009; Meyer et al. 2012; Hegarty et al. 2010).

Innovative visualisations can also be developed with traditional, low-technology approaches. Hands-on, bottom-up, community-led participatory mapping exercises, in which tangible objects such as paper, pens, paint, and stones are used to visually represent and contextualise interrelationships between hazards and society, can help foster important dialogue about natural hazards and risk (Chambers 2008; Cadag and Gaillard 2012). For example, Cadag and Gaillard (2012) outline how participatory 3D mapping (P3DM) was used as an integrative tool for disaster risk reduction in Masantol, a small municipality on the island of Luzon in the Philippines. They found that collaboratively building a physical, 3D geographic model of place empowered the community to engage in constructive dialogue about hazard and risk. Such approaches also offer a way to integrate scientific and local knowledge in a way that is tangible and meaningful for many different people in the community, from government officials to school students (Cadag and Gaillard 2012).

## 4 Volcanic Hazard Maps into the Future

Volcanic hazard maps have transformed over the past several decades due to advances in hazard analysis methods, lessons learnt through past crises, and ongoing interdisciplinary research into how audiences engage and interact with hazard maps. Modern volcanic hazard maps will continue to evolve into the future as digital technologies, GIS, social media, citizen science, and globalisation have a growing impact on science communication and disaster management
<figure><img src="image_212.png" /><figcaption>**Fig. 8** Probabilistic volcanic hazard map showing global volcanic ash fall hazard. The map, which was produced for the UNISDR 2015 Global Assessment Report, is based on large-scale quantitative modelling, and shows</figcaption></figure>

(e.g., Webley and Watson *this volume*, Kuhn et al. *this volume*). In 2015, one of the first global volcanic hazard maps was created as part of the UNISDR (United Nations Office for Disaster Risk Reduction) Global Assessment Report (Jenkins et al. 2015; Fig. 8). The map represents the growing global collaboration effort in volcanic hazard analysis, as well as the expanding capabilities of hazard modelling and computation. Collaborative international online volcanology networks, such as Vhub (www.Vhub.org; Palma et al. 2014), local online hubs, such as wikis (Leonard et al. 2014), and interactive online tools for volcanic hazard assessment, such as G-EVER (Tsukuda et al. 2012), are helping to facilitate data-sharing and improve access to hazard modelling, enabling new levels of engagement and access to tools and information for map-making and design.

While visual design of hazard maps will continue to evolve with innovation of new technologies and hazard mapping approaches, hazard map audiences will also evolve. As globalisation and population growth continues, hazard map audiences will dynamically shift and become more diverse. For example, growth in volcano tourism could lead to higher numbers of tourists and non-native speakers in hazardous areas, and these populations are likely to have different perceptions of hazard and risk than local audiences (Bird et al. 2010). Future work exploring differences in the information needs and cultural

average recurrence interval (in years) between accumulating ash thicknesses exceeding 1 mm. Modified from Jenkins et al. (2015)

communication styles within and among these diverse audiences will be important for understanding how to adapt and grow approaches to volcanic hazard knowledge exchange.

Interdisciplinary research is becoming increasingly embraced within the field of volcanic hazard and risk (Barclay et al. 2008), and future volcanic hazard maps should continue to work towards integrating new interdisciplinary concepts from research fields such as sociology, communications, human factors, geography, design, and psychology to develop intuitive designs which maximise visual cues, minimise cognitive load, and increase the effectiveness of visual communication. Integrating tacit knowledge from relevant areas of practice (e.g., emergency management, national parks, conservation) in addition to theories and concepts from different areas of research can help ensure that volcanic hazard maps of the future are optimally designed in a way that makes them useful, usable, and used.

It is important to acknowledge that the case studies and research covered in this chapter rely principally on work and experiences published in the academic literature, and are not comprehensive. There is a wealth of tacit knowledge on audience-map engagement and hazard communication gained from practice that is not captured in this summary. However, a key theme which emerges from the case studies and work reviewed in this chapter is that an audience-based,
evidence-backed approach to visual design of hazard maps can help facilitate clear hazard communication. As with most communication approaches, hazard map design is not “one-size-fits all”, and cannot be guided by a single universal framework or design solution. Nevertheless, hazard maps that: (A) consider the audience and their messaging needs, and (B) use evidence from interdisciplinary research and experience to inform visual map design based on these needs, can help communicate information in a way that is accessible and useful to those who need it. While available resources, target audiences, and volcanic setting will uniquely guide and shape this process for each map, adopting such an approach can help create end results that are grounded in meaningful communication goals.

# 5 Summary

Volcanic hazard maps that are designed based on both the needs of the audience and evidence from practice and research can help support clear and effective messaging of critical hazard information. Engaging with audiences to explore how they understand and create meaning from hazard maps can foster constructive multi-way dialogue about volcanic hazards, and also help ensure that important messages are visually communicated in a way that is transparent and trusted by those potentially affected by a volcanic crisis. Although hazard maps represent just one component of a hazard assessment, their ability to comprise many types of information into a concise, visually salient graphic that can be shared across many types of media means that they are often used widely in crisis communication. Past volcanic crises across the world have underscored the important communication role of hazard maps, but have also highlighted the significant impact that visual design has on this exchange.

Visual representation of hazard information on a map can influence the way that people engage with the information, as well as the messages that people take away, and decisions

they make. Future work into the ways in which people read, process, and share visual information will open new opportunities for optimising volcanic hazard content for different audiences. This will continue to be important as advances in hazard modelling and visualisation technology introduce new ways of visually communicating hazard during a crisis. As the volcanology community works towards exploring new ways of developing and designing volcanic hazard maps, new levels of global collaboration through online data-sharing hubs will provide ways to connect, share, and integrate these emerging approaches. By considering audience needs and perspectives —how the information might be used, read, understood, and applied—hazard maps can be designed in a way that makes them accessible, relevant, and clear for the people who need them.

**Acknowledgements** The authors would like to acknowledge the many generations of volcanic hazard maps which have contributed valuable insight and knowledge regarding both the advantages and challenges of visually communicating volcanic hazard. The authors would also like to thank M Monsalve, H Murcia, and C Driedger for reviewing parts of this manuscript, and two anonymous reviewers for constructive and valuable comments on an earlier version of this chapter. MAT and JML gratefully acknowledge support from the New Zealand Earthquake Commission.

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# The Role of Geospatial Technologies in Communicating a More Effective Hazard Assessment: Application of Remote Sensing Data

P. W. Webley and I. M. Watson

## Abstract

Remote sensing data and the application of geo-spatial technologies have progressively been built into real-time volcanic hazard assessment. Remote sensing of volcanic processes provides a unique synoptic view of the developing hazard, and provides insights into the ongoing activity without the need for direct, on-the-ground observations. Analysis and visualization of these data through the geospatial tools, like Geographical Information Systems (GIS) and new virtual globes, brings new perspectives into the decision support system. In this chapter, we provide examples of (i) how remote sensing has assisted in real-time analysis of active volcanoes; (ii) how by combining multiple sensors at different spatial, spectral and temporal resolutions one is able to better understand a given hazard, leading to better communication and decision making; and (iii) how visualizing this in a common platform, like a GIS tool or virtual globe, augments effective hazard assessment system. We will illustrate how useful remote sensing data can be for volcanic hazard assessment, including the benefits and challenges in real-time decision support, and how the geo-spatial tools can be useful to communicate the potential hazard through a common operation protocol.

## List of Acronyms

AIRS Airborne Infrared Remote Sounder

ASTER Advanced Spaceborne Thermal Emission and Reflection Radiometer

P. W. Webley (✉)
Geophysical Institute, University of Alaska
Fairbanks, Fairbanks, AK 99775, USA
e-mail: pwwebley@alaska.edu

I. M. Watson
School of Earth Sciences, University of Bristol,
Bristol, UK

Adv in Volcanology (2018) 641–663
https://doi.org/10.1007/11157_2017_7
© The Author(s) 2017
Published Online: 22 June 2017
<table>
  <tr>
    <td>AVHRR</td>
    <td>Advanced Very High Resolution Radiometer</td>
  </tr>
  <tr>
    <td>CIMSS</td>
    <td>Cooperative Institute for Meteorological Satellite Studies</td>
  </tr>
  <tr>
    <td>CNES</td>
    <td>Centre National d'Etudes Spatiales</td>
  </tr>
  <tr>
    <td>COMET</td>
    <td>Centre for Observation and Modelling of Earthquakes, Volcanoes, and Tectonics</td>
  </tr>
  <tr>
    <td>CONAE</td>
    <td>Comision Nacional De Actividades Espaciales</td>
  </tr>
  <tr>
    <td>EDS</td>
    <td>Expedited Data Set</td>
  </tr>
  <tr>
    <td>EM</td>
    <td>Electromagnetic</td>
  </tr>
  <tr>
    <td>ENVI</td>
    <td>Environment for Visualizing Images</td>
  </tr>
  <tr>
    <td>ERDAS</td>
    <td>Earth Resources Data Analysis System</td>
  </tr>
  <tr>
    <td>ESA</td>
    <td>European Space Agency</td>
  </tr>
  <tr>
    <td>EUMETSAT</td>
    <td>European Organisation for the Exploitation of Meteorological Satellites</td>
  </tr>
  <tr>
    <td>GEOTIFF</td>
    <td>Geostationary Earth Orbit Tagged Image File Format</td>
  </tr>
  <tr>
    <td>GIS</td>
    <td>Geographical Information Systems</td>
  </tr>
  <tr>
    <td>GOES-R</td>
    <td>Geostationary Operational Environmental Satellite-R</td>
  </tr>
  <tr>
    <td>GOME-2</td>
    <td>Global Ozone Monitoring Experiment-2</td>
  </tr>
  <tr>
    <td>GPS</td>
    <td>Global Positioning System</td>
  </tr>
  <tr>
    <td>HDF</td>
    <td>Hierarchical Data Format</td>
  </tr>
  <tr>
    <td>IASI</td>
    <td>Infrared Atmospheric Sounding Interferometer</td>
  </tr>
  <tr>
    <td>ILWIS</td>
    <td>Integrated Land and Water Information System</td>
  </tr>
  <tr>
    <td>IMO</td>
    <td>Icelandic Meteorological Office</td>
  </tr>
  <tr>
    <td>KML</td>
    <td>Keyhole Markup Language</td>
  </tr>
  <tr>
    <td>KMZ</td>
    <td>Keyhole Markup Zipped</td>
  </tr>
  <tr>
    <td>KVERT</td>
    <td>Kamchatka Volcanic Eruption Response Team</td>
  </tr>
  <tr>
    <td>LANDSAT</td>
    <td>Land Remote-Sensing Satellite (System)</td>
  </tr>
  <tr>
    <td>MIR</td>
    <td>Mid-Infrared</td>
  </tr>
  <tr>
    <td>MODIS</td>
    <td>Moderate Resolution Imaging Spectroradiometer</td>
  </tr>
  <tr>
    <td>MTSAT</td>
    <td>Multifunctional Transport Satellites</td>
  </tr>
  <tr>
    <td>NASA</td>
    <td>National Aeronautics and Space Administration</td>
  </tr>
  <tr>
    <td>NERC</td>
    <td>Natural Environment Research Council</td>
  </tr>
  <tr>
    <td>NOAA</td>
    <td>National Oceanic and Atmospheric Administration</td>
  </tr>
  <tr>
    <td>NRT</td>
    <td>Near Real-Time</td>
  </tr>
  <tr>
    <td>OMI</td>
    <td>Ozone Monitoring Instrument</td>
  </tr>
  <tr>
    <td>OMPS</td>
    <td>Ozone Mapping Profiler Suite</td>
  </tr>
  <tr>
    <td>ORFEO</td>
    <td>Optical and Radar Federated Earth Observation</td>
  </tr>
  <tr>
    <td>RADAR</td>
    <td>Radio Detection and Ranging</td>
  </tr>
  <tr>
    <td>RGB</td>
    <td>Red, Green, Blue</td>
  </tr>
  <tr>
    <td>ROI</td>
    <td>Region of Interest</td>
  </tr>
  <tr>
    <td>SACS</td>
    <td>Support to Aviation Control Service</td>
  </tr>
  <tr>
    <td>SEVIRI</td>
    <td>Spinning Enhanced Visible and Infrared Imager</td>
  </tr>
  <tr>
    <td>SHP</td>
    <td>Shape</td>
  </tr>
  <tr>
    <td>SO2</td>
    <td>Sulfur dioxide</td>
  </tr>
  <tr>
    <td>SOPI</td>
    <td>Software de Procesamiento de Imágenes</td>
  </tr>
  <tr>
    <td>SPIRITS</td>
    <td>Software for the Processing and Interpretation of Remotely sensed Image Time Series</td>
  </tr>
  <tr>
    <td>SWIR</td>
    <td>Short Wave Infrared</td>
  </tr>
  <tr>
    <td>TIR</td>
    <td>Thermal Infrared</td>
  </tr>
</table>
<table><tr><td>URP</td><td>Urgent Request Protocol</td></tr><tr><td>USGS</td><td>United States Geological Survey</td></tr><tr><td>UV</td><td>Ultraviolet</td></tr><tr><td>VEI</td><td>Volcano Explosivity Index</td></tr><tr><td>VIIRS</td><td>Visible Infrared Imaging Radiometer Suite</td></tr><tr><td>VLP</td><td>Very long Period</td></tr><tr><td>VNIR</td><td>Visible Near Infrared</td></tr></table>

# 1 Introduction

Timely analysis of volcanic activity makes for enhanced hazard assessment, and provides the best available information to both mitigate the hazard and reduce the risk it could pose. For example, seismic data can be collected and processed with sub-second acquisition frequency (McNutt 1996) to assess earthquake location and signal changes relating to volcanic tremor (Aki et al. 1977; McNutt 1986; Zuccarello et al. 2013), and very long period (VLP) earthquakes (Jousset et al. 2013). Global positioning system (GPS) data can produce time series of vertical and horizontal motion at similar frequencies (e.g. Owen et al. 2000). These two datasets provide point location information of volcanic activity and often require modeling of the volcanic edifice (e.g. Poland et al. 2006) to correlate the data to large changes in the volcanic system. While not having the sub-second periodicity of these geophysical data, satellite-based remote sensing data can be used to examine the large scale spatial changes at a volcano, before, during and after a volcanic event (Rothery et al. 1988; Prata et al. 1989; Guo et al. 2004; Bailey et al. 2010; Thomas et al. 2011; Webley et al. 2013).

Real-time satellite data and new data visualization techniques and software allow the decision maker to evaluate the local, regional, country-wide, continental, and global scales of the volcanic events and impending volcanic crises. Enhanced visualizations of the remote

sensing data can be critical to communicate the scale and impact of the volcanic events and connect with those most at risk. Satellite remote sensing data have been readily available for several decades, and while no sensor has been specifically designed for volcanoes only, there are a large number of satellite-based sensors used to analyze volcanoes and detect and map their associated hazards. While listing all past, current and future sensors is beyond this chapter, we discuss the different regions of the electromagnetic spectrum that can be useful for monitoring volcanoes and the tradeoffs between spectral, temporal and spatial resolutions when assessing the most appropriate sensor for the type of hazard assessment. Some satellites and their sensors are useful for mapping ground deposits and studying the volcano as it inflates and deflates under changing volcanic activity, while others are most applicable to detecting atmospheric emissions, such as volcanic ash and sulfur dioxide ($SO_2$).

# 2 Remote Sensing Basics

Lillesand et al. (2015) define remote sensing as “the science and art of obtaining information about an object, area or phenomena through the analysis of data acquired by a device that is not in contact with the object, area or phenomena under investigation”. Satellite remote sensors are either an active system, like RADAR (Radio Detection and Ranging), that sends a pulse and
<figure><img src="image_213.png" /><figcaption>**Fig. 1** Electromagnetic spectrum highlighting the regions, UV, IR and microwave, where remote sensing analysis from space is possible; last viewed February 17, 2015 (http://upload.wikimedia.org/wikipedia/commons/</figcaption></figure>

thumb/d/d9/Atmospheric_windows_EN.svg/2000px-Atmospheric_windows_EN.svg.png). Dashed line represents the scattering losses due to absorption across the full spectrum defined in the figure

waits for a return, or a passive system, that measures the response at a specific wavelength as radiation passes through the Earth's atmosphere. Wavelengths of emitted and reflected electromagnetic (EM) radiation, as measured by current satellite sensors, are divided into regions from ultraviolet (UV) to microwave (Fig. 1). Most, though not all observations, are made through 'atmospheric windows' where the absorption by the atmosphere is minimal. For some observations high opacity is useful such as infrared wavelengths around 7.3 µm where the absorption features of SO₂ can be used to measure the amount of SO₂ released by a volcano (Thomas et al. 2009, 2011). In order to undertake a volcanic hazard assessment, the type of satellite sensor is therefore determined by the process being examined and the availability of atmospheric windows (Thomas and Watson 2010).

When describing remote sensing satellites and their sensors, the terms ‘spectral’, ‘spatial’ and ‘temporal’ resolutions are often used to assess if the available data can provide the required coverage for the hazardous event. Sensors can have low spectral resolution, such as the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) with three broad range

channels in the mid and thermal infrared wavelengths of the EM spectrum (Fig. 2a). This is compared to the low spectral resolution sensors, like NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) with 11 broad and narrow range channels across this portion of the EM spectrum. These are compared to multi- or hyperspectral sensors, like the NASA Airborne Infrared Remote Sounder (AIRS), which has over 2000 channels from 3.7 to 15.4 µm.

Trade-offs in the best sensor to use will occur between pixel size and detail level required (Fig. 2b). Finer spatial resolutions are often a function of a narrower swath width, i.e. coverage across the satellite track. Therefore, there is a trade-off between the spatial resolution and the repeat rate of measurements from the same sensor, i.e. its temporal resolution. Differences in temporal resolution generally relate to the chosen orbits of the different satellites (Fig. 2c). Sensors on satellites with a polar orbit, like AVHRR and MODIS, have a longer repeat period than those from a geostationary orbit, such as the Geostationary Operational Environmental Satellite (GOES-R). However, these geostationary satellites, which remain stationary at one point above the equator, have as a consequence a coarser spatial resolution than from a polar orbit. The
Mid- and Thermal-Infrared Region

(a)

<figure><img src="image_214.png" /></figure>

<figure><img src="image_215.png" /></figure>

Polar-Orbiting and Geostationary Satellites

(c)

<figure><img src="image_216.png" /><figcaption>**Fig. 2** a Varying spectral ranges of satellite channels for AIRS, AVHRR and MODIS (NASA 2003)—note that AIRS data represents multispectral data with narrow bands while AVHRR and MODIS represent individual broad band channels; b Changes in image resolution ‘smooths’ out useful data (the same image is shown at</figcaption></figure>

5 × 5, 40 × 40 and 80 × 80 m pixels to illustrate the data smoothing at coarser resolutions); and c differences in polar and geostationary orbits for repeat coverage (adapted from http://www.meted.ucar.edu/satmet/npp/media/graphics/geo_leo_satellites.jpg)
spectral resolution is limited by available energy, and hence, as larger footprints provide more energy there is a trade-off with spatial resolution. The chosen applications of the satellite sensor inform the decisions around the spectral, spatial and temporal resolutions of the data available. NOAA (2015a) and JPL (2015) provide an overview of the NOAA and NASA satellite missions currently in operation, while WMO (2013) provide information on different satellites and their sensors specifically for detecting volcanic ash and SO₂ clouds. In the following section, we highlight some of the online tools currently available that routinely process satellite data and provide derived products for volcanic hazard assessment and decision support.

## 3 Accessing Real-Time Data

Gaining timely access to remote sensing for hazard assessment is essential for rapid analysis. Users can download available data from online sites provided by the satellite data providers (Table 1). To fully analyze the available data often requires access to expensive software, such as ENVI® (Environment for Visualizing Images), as well as proficiency in remote sensing image analysis (Table 2). Other projects and agencies

have provided online access to products from available polar, geostationary/geosynchronous satellite data (Table 3). These online services are often designed by specific groups or organizations for their own monitoring capabilities and so may not be optimally designed for others to use in their hazard assessment and mitigation. However, they do provide excellent routinely processed products that can be used in real-time to assess the hazardous events and mitigate their impact.

Other groups have set up their own receiving stations (Kaneko et al. 2002; Webley et al. 2008) for local access to data to reduce the time delay between acquisition and data processing. Again, as with accessing data from the services listed in Table 1, there is need for either a local remote sensing expert or a fully automated system and online tool for all to use the derived data during a volcanic event.

## 4 Applications During Volcanic Eruptions

To illustrate how remote sensing data have been successfully used during volcanic eruptions, the following section focuses on three different eruptive events (Fig. 3) with examples from

<table><caption>**Table 1** Some of the available online tools available for accessing the multispectral and high spatial resolution remote sensing data</caption><thead><tr><td>Primary Org.</td><td>Website/Tool name</td><td>Capabilities for the user</td></tr></thead><tbody><tr><td>NASA</td><td>https://earthdata.nasa.gov/data/data-tools/search-and-order-tools</td><td>Lists all possible online tools for search and ordering of data from NASA sensors</td></tr><tr><td>USGS</td><td>EarthExplorer http://earthexplorer.usgs.gov/</td><td>Search for data from archival and NRT data, view premade images, download data in HDF form</td></tr><tr><td>NASA</td><td>Reverb http://reverb.echo.nasa.gov/</td><td>Can search any data from NASA or affiliate agencies; download data in HDF form</td></tr><tr><td>USGS/NASA</td><td>ASTER EDS data https://astereds.cr.usgs.gov/</td><td>View all newly acquired ASTER data from urgent request, premade browse images, download HDF data</td></tr><tr><td>USGS</td><td>GloVis http://glovis.usgs.gov/</td><td>Java based interface for viewing archival data, premade browse images, request data in HDF format.</td></tr><tr><td>EUMETSAT</td><td>Earth Observation Portal https://eoportal.eumetsat.int/</td><td>Requires account, can view all EUMETSAT data, need specific agreement to download data</td></tr></tbody></table>

ASTER Advanced Spaceborne Thermal Emission and Reflection Radiometer, EDS Expedited Data Sets, NRT Near Real-Time and EUMETSAT European Organisation for the Exploitation of Meteorological Satellites
<table><caption>**Table 2** Example of remote sensing software that can be used to analyze spaceborne data and produce two-dimensional datasets and imagery per channel and satellite overpass</caption><thead><tr><td>Software</td><td>Manufacturer</td><td>Platform</td><td>Capabilities for the user</td></tr></thead><tbody><tr><td>BEAM/SNAP</td><td>ESA</td><td>Unix</td><td>Display, basic image processing, band arithmetic, rectification, ROI statistics</td></tr><tr><td>ENVI</td><td>Harris</td><td>Unix, Windows, MacOSX</td><td>Display, band arithmetic, rectification, ROI statistics, advanced algorithms for image processing</td></tr><tr><td>ILWIS</td><td>52 North</td><td>Windows</td><td>Digitizing, editing, display, GIS, basic analysis</td></tr><tr><td>Imagine</td><td>ERDAS</td><td>Unix, Windows, MacOSX</td><td>Display, band arithmetic, rectification, ROI statistics, advanced algorithms for image processing</td></tr><tr><td>ORFEO</td><td>CNES</td><td>Unix, Windows, MacOSX</td><td>Display, band arithmetic, rectification, ROI statistics</td></tr><tr><td>Opticks</td><td>BATC</td><td>Unix, Windows</td><td>Display, image manipulation, statistics</td></tr><tr><td>Geomatica</td><td>PCI</td><td>Unix, Windows, MacOSX</td><td>Display, Mosaics, DEM extraction, rectification</td></tr><tr><td>REMOTE-VIEW</td><td>Textron</td><td>Windows</td><td>Display, multispectral analysis, calibration</td></tr><tr><td>SOPI</td><td>CONAE</td><td>Unix, Windows</td><td>Display, basic image processing, rectification</td></tr><tr><td>SPIRITS</td><td>JRC</td><td>Windows</td><td>Display, basic image processing, band arithmetic, rectification</td></tr></tbody></table>

<table><caption>**Table 3** Sample list of online resources, specifically designed for volcanoes, for access to derived products from satellite data</caption><thead><tr><td>Name</td><td>Website/Tool name</td><td>Sensor/Satellite analyze</td><td>Focus/Details</td></tr></thead><tbody><tr><td>Volcview</td><td>http://volcview.wr.usgs.gov/</td><td>AVHRR/MODIS/MTSAT/GOES</td><td>Access to a number of satellites in near real time for the North Pacific region</td></tr><tr><td>Volcanic Cloud Monitoring</td><td>http://volcano.ssec.wisc.edu/</td><td>AVHRR/MODIS/MTSAT GOES/SEVIRI/VIIRS</td><td>NOAA-CIMSS satellite imagery pages. Includes a range of single, two and multi-channel products</td></tr><tr><td>ASTER Volcano Archive</td><td>http://ava.jpl.nasa.gov/</td><td>ASTER</td><td>Provides users access to search for all ASTER data for volcanoes</td></tr><tr><td>SACS</td><td>http://sacs.aeronomie.be/nrt/</td><td>GOME-2, IASI, OMI, OMP, AIRS</td><td>Near real time SO<sub>2</sub> and ash alert notification and imagery</td></tr><tr><td>NASA SO<sub>2</sub></td><td>http://so2.gsfc.nasa.gov/</td><td>OMI, OMPS</td><td>NASA Global SO<sub>2</sub> monitoring page</td></tr></tbody></table>

SEVIRI Spinning Enhanced Visible and Infrared Imager, IASI Infrared Atmospheric Sounding Interferometer, MTSAT Multifunctional Transport Satellites, VIIRS Visible Infrared Imaging Radiometer Suite and OMI Ozone Monitoring Instrument
<figure><img src="image_217.png" /><figcaption>**Fig. 3** a Indonesia and its volcanoes, highlighting Merapi volcano (modified from Gertisser and Keller 2003); b The volcanoes of Kamchatka emphasizing the location</figcaption></figure>

across the EM spectrum. Through these case studies, we show examples of available online data as well as post-processed data and imagery that encapsulate multiple sources (Table 4) and different types of analyses.

## 4.1 Merapi Volcano and Its 2010 Eruption

Merapi Volcano in Indonesia (Fig. 3a) has, since 1900, typical recurrence intervals of 4–6 years with lava dome generation that collapse to

of Plosky Tolbachik (adapted from Kirianov et al. 2002); and c Icelandic volcanoes and associated geology showing the site of Bárðarbunga volcano (GVP 2011)

generate pyroclastic flows and lahars (Surono et al. 2012). In 2010, the volcano erupted explosively with the main explosive events on October 26, 29, 31 and November 1, 3, and 4. Surono et al. (2012) along with Jousset et al. (2013) provide an excellent overview of the eruption. Here, however, we focus on the use of radar data, as this provided a spectacular view of the growing dome and was essential in aiding forecasting of the eruptive crisis in terms of predicting the impact that could be generated if (or when) the dome collapsed. After the first phreatomagmatic explosive phase on October 26,
<table><caption>**Table 4** All sensors described in chapter, for full names of sensors and agencies see descriptions within the chapter</caption><thead><tr><th>Sensor (Agency)</th><th>Spatial<sup>a</sup></th><th>Spectral</th><th>Temporal<sup>b</sup></th><th>References</th></tr></thead><tbody><tr><td>SEVIRI (EUMETSAT)</td><td>1–3 km</td><td>0.635–12.4 µm</td><td>15 min</td><td>EUMETSAT (2015a)</td></tr><tr><td>MTSAT (JMA)</td><td>1–4 km</td><td>0.55–12.5 µm</td><td>30 min</td><td>BOM (2015)</td></tr><tr><td>IASI (EUMETSAT)</td><td>25 km</td><td>3.6–15.5 µm</td><td>Twice a day</td><td>EUMETSAT (2015b)</td></tr><tr><td>OMI (NASA)</td><td>13 × 24 km (nadir)</td><td>0.27–0.5 µm</td><td>Daily</td><td>Krotkov et al. (2006)</td></tr><tr><td>AIRS (NASA)</td><td>13.5 km</td><td>3.7–15.4 µm</td><td>16 days</td><td>NASA (2003)</td></tr><tr><td>GOME-2</td><td>40 km (nadir)</td><td>0.25–0.79 µm</td><td>29 days<sup>c</sup></td><td>EUMETSAT (2014)</td></tr><tr><td>OMPS (NOAA)</td><td>50 km (nadir)</td><td>0.3–0.38 µm</td><td>16 days</td><td>NASA (2015a)</td></tr><tr><td>ALI (NASA)</td><td>10–30 m</td><td>0.48–2.35 µm</td><td>16 days</td><td>NASA (2011a)</td></tr><tr><td>HYPERION (NASA)</td><td>30 m</td><td>0.4–2.5 µm</td><td>16 days</td><td>NASA (2011b)</td></tr><tr><td>ASTER (NASA)</td><td>15–90 m</td><td>0.52–11.65 µm</td><td>16 days<sup>d</sup></td><td>USGS (2014a)</td></tr><tr><td>AVHRR (NOAA)</td><td>1 km</td><td>0.58–12.5 µm</td><td>Multiple a day</td><td>NOAA (2013)</td></tr><tr><td>MODIS (NASA)</td><td>250 m–1 km</td><td>0.459–14.3 µm</td><td>Twice a day</td><td>NASA (2015b)</td></tr><tr><td>GOES-R (NOAA)</td><td>500 m–2 km</td><td>0.47–13.3 µm</td><td>15 min</td><td>NOAA (2014)</td></tr><tr><td>TerraSAR (Astrium)</td><td>1–18 m</td><td>3.1 cm</td><td>2.5 days</td><td>Astrium (2015)</td></tr><tr><td>RadarSAT-2 (CSA)</td><td>1–8 m</td><td>5.6 cm</td><td>24 days</td><td>CSA (2015)</td></tr><tr><td>VIIRS (NOAA/NASA)</td><td>375 m (nadir)</td><td>0.412–12.013 µm</td><td>Twice a day</td><td>NOAA (2015b)</td></tr><tr><td>LANDSAT-8 (USGS/NASA)</td><td>15–100 m</td><td>0.43–12.5 µm</td><td>16 days</td><td>USGS (2014b)</td></tr></tbody></table>

remote sensing data became a critical tool in monitoring and guiding those in crisis management (Pallister et al. 2013). The availability of commercial satellite radar data from RADARSAT-2 and TerraSAR-X, at 0.5–3 m pixel resolution, provided a unique view of the summit activity and the data to analyze the dome growth occurring at the summit between each explosive event (Fig. 4).

Pallister et al. (2013) stated that the speed of availability for these data was critical in providing the best available analysis of the growing

dome for life-saving crisis response. For example, estimates based on radar data suggest that the dome grew 5 million m³ between October 26 (Fig. 4a) and November 4 and by the early hours of November 6, the dome was gone (Fig. 4b). However, a new dome of approx. 1.6 million m³ grew in the space of 11 h that same day (Fig. 4c). The fact that local volcanologists and emergency managers were able to examine the activity at the summit of Merapi at sub 3 m resolution enabled them to make short term assessments on the dome's stability. By

<footnote><sup>a</sup>Spatial resolution is defined as the range across swath unless specified</footnote>

<footnote><sup>b</sup>THIS is the orbital repeat time, rather than the time it takes to view the same point on the earth. Also, note that for several sensors, such as AVHRR, MODIS and GOME-2, the time is specified per sensor and there are multiple sensors in orbit on different satellites</footnote>

<footnote><sup>c</sup>GOME-2 images the same location more than once every 29 days but at different locations within the swath</footnote>

<footnote><sup>d</sup>ASTER sensor can be tasked and data can be requested to view specific locations more frequently than the 16 day orbit repeat time</footnote>
**Fig. 4** Merapi RADARSAT-2 and TerraSAR data, adapted from Pallister et al. (2013) showing data from **a** October 11 and 26, 2010; **b** November 4 and 6, 2010; and **c** November 6, 2010 at 11:08 and 22:07 UTC where *PF* pyroclastic flow, *K* Kali Kuning, *Kj* Kinorejo, *C* empty crater, *D* lava dome, and *S* surge deposits. On October 11 and 26, 2010, the *red arrow* highlights the 2006 dome while ‘G’ indicates the location of Kali Gendoi, where a pyroclastic density current flowed down. The 1 and 2 km distances are equivalent to the length of the *arrow line* segment

<figure><img src="image_218.png" /></figure>
measuring the extrusion rate of the dome as it grew between explosive events volcanologists were able to assess the likelihood of dome destabilization.

Radar data were just one form of remote sensing data that were available during the eruption. High temporal frequency visible and infrared data (see Sect. 5) were available to detect and analyze the location of the dispersing ash clouds for aviation safety. Time series analysis of the dome growth and its potential to destabilize provided the inputs to build probabilistic scenarios of the likelihood for an eruption (Pallister et al. 2013) and for a significant dome collapse that could impact the surrounding population centers.

## 4.2 Tolbachik Volcano and Its 2012–2013 Eruption

Tolbachik or Plosky Tolbachik volcano, situated on the Kamchatka Peninsula, is a massive basaltic volcano sitting at the southern end of the Klyuchevskaya volcano group. GVP (2017) state that the majority of its activity is relatively low level with volcano explosivity indices (VEI) of 1 and 2 (see Newhall and Self (1982) for explanation of VEI). However, it had a major fissure eruption in 1975–1976 (Fedotov et al. 1980) that was classified as a VEI 4. Tolbachik was quiet until late 2012, when the local volcano monitoring group, Kamchatka Volcanic Eruption Response Team (KVERT), reported that an eruption had begun on November 27.

We examine the mid and thermal infrared wavelength data from both high temporal (multi views a day), low spatial (one [1] km in IR) data and low temporal (one overpass every few days), high spatial (<100 m in IR). Figure 5a shows images from the NASA Advanced Land Imager (ALI) sensor, where differences in the extent of the fissure can be seen from choice of band combinations. Bands 3, 2, 1 represent a true color image. Switch the combination to bands 5', 4', and 4, and the red color in the RGB composite is enhanced. Finally, with the composite of Bands 7, 5', and 5 the thermal signals from the fissures

at Band 7, 2.35 µm, are close to saturation and therefore a ‘red glow’ effect occurs. These ALI data (Figs. 5a–d) illustrate that by using different band combinations and comparing signals at different wavelengths it is possible to determine the hottest part of the eruptive feature.

For example, Fig. 5b shows ALI data from December 1, five days after the first reported activity. The visible data show the steaming flows as they interact with the surrounding snow and ice, while the SWIR, right-hand side of Fig. 5b, shows the thermal signals being emitted from the flows. Combining visible and SWIR imagery, the ALI data is able to capture the location and intensity of thermal signals from the fissure eruption. Figure 5c shows visible and thermal infrared (TIR) data from the NASA Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor on February 13, 2013 ‘tasked’ using the ASTER Urgent Request Protocol (URP), see Ramsey and Dehn (2004). The TIR data shows the hottest part of the flow on the eastern side, noting the earlier western erupted flows are still warmer than the surrounding region. Compare to this to SWIR from the ALI data on December 1, 2012, Fig. 5b. This cooler material on February 13 corresponds to the hot active flows six weeks earlier. With its 10.6 µm data, the ASTER URP data could be used to determine the effusion rates from the fissure eruption and assess if the activity was increasing or waning.

With the chosen channels for the RGB composite (Fig. 5d), it is possible to differentiate the higher radiances at 2.193 µm, indicating warmer temperatures. This composite analysis for HYPERION shows how with hyperspectral data it is possible to assess subtle variations in the thermal signals of active flows. Additional analyses can include examining the full suite of 220 channels to determine the surface characteristics, such as rock type and mineral composition (see Hubbard et al. 2003).

The high spatial resolution imagery from ASTER, ALI and HYPERION were not the only thermal infrared data to capture the activity at Tolbachik volcano. The high temporal, lower spatial resolution data from the NOAA AVHRR
<figure><img src="image_219.png" /><figcaption>**Fig. 5** Different sensors over time for Tolbachik volcano in 2012–2013 where differences in the extent of the fissure can be seen based on the choice of band combinations. **a** NASA ALI on February 14, 2013 of Bands 3, 2, 1 (0.63–0.69 µm; 0.525–0.605 µm; 0.45–0.515 µm) showing a true color image; Bands 5', 4' and 4 (1.1–1.3 µm; 0.845–0.89 µm; 0.775–0.805 µm) and Bands 7, 5, and 5' (2.08–2.35 µm; 1.55–1.75 µm; 1.2–1.3 µm); **b** NASA visible and SWIR ALI from December</figcaption></figure>

1, 2012; c NASA ASTER Urgent Request Protocol (URP) data (visible and TIR) from February 13, 2013 with subset in the *red box* showing a thermal signal from the most active part of the fissure as the *red color* is elevated; and d NASA HYPERION RGB composite with Channels 204, 150 and 93 at 2.193, 1.649 and 1.074 µm from February 14, 2013 data showing the most active portion of the flows (*red* and *yellow regions* in the *inset*)

and NASA MODIS sensors provided a vital tool in monitoring the fissure eruption. March 2, 2013 provided an ideal opportunity to compare the thermal signals available from the three different sensors (Fig. 6) The ASTER data resolution allows finer details in the flow pattern to be captured and therefore is closer to the actual spatial extent of the flow. The MODIS and AVHRR data have much larger pixels, 1.1 km² at nadir that grows in size towards the swath edge impacting the ability to detect small scale (spatial and thermal output) thermal events.

The timely data from the MODIS and AVHRR sensor meant that they could be used to

assess relative changes from one overpass to the next, given the sub-daily temporal frequency of the available data. The ASTER data, while more accurate given its pixel size, is one point in time. Therefore, for enhanced hazard assessment the MODIS and AVHRR data, coupled to the finer spatial resolution ASTER for comparison, became a critical tool in the daily monitoring of the ongoing hazard. The MODIS and AVHRR data (Fig. 6) were routinely collected by KVERT for analysis of the ongoing hazard, while the ASTER data were acquired by NASA URP and the ALI/HYPERION data were available via the online tools from satellite providers. This satellite
<figure><img src="image_220.png" /><figcaption>**Fig. 6** Intercomparison of sensors on the same date: a ASTER Band 13 at 00:32 UTC; b AVHRR Band 4 at 01:18 UTC; and c MODIS Band 31 at 00:30 UTC on March 2, 2013. Here ASTER Band 13 data, 9.1 µm, is compared to AVHRR Band 4, 10.6 µm, and MODIS</figcaption></figure>

Band 31, 11.02 µm. ASTER with 90 m spatial resolution captures more of the flow's details, and shows an area of 30 km². Compare this with the MODIS data with an area of 54.8 km² and AVHRR with 47.3 km²

remote sensing data was useful to analyze the relative change in the fissure eruption and showed how, by coupling multi resolution data, one could assess if the eruption was over or if it was increasing towards a new level of heightened activity.

## 4.3 Bárðarbunga Volcano and Its 2014–2015 Eruption

Bárðarbunga volcano is situated beneath the northwestern part of Vatnajökull ice cap in south-eastern Iceland. In August 2014, the Icelandic Meteorological Office (IMO) reported increased seismicity at the volcano. By August 23, this activity had developed into a 150–400 m long dyke beneath the Dyngjujökull glacier, prompting a change in the aviation color code to red (GVP 2014). By August 29, IMO reported that a small fissure eruption had started in Holuhraun and lava started to erupt on August 31 along a 1.5 km long fissure (GVP 2014).

Following the eruptions from Eyjafjallajökull 2010 (Gudmundsson et al. 2010, 2012) and Grimsvötn 2011 (GVP 2011), there had been a lot of focus on the potential impact of another Icelandic eruption on Europe and its transportation infrastructure. Routine satellite remote sensing data were collected and processed to build derived products from ultraviolet data with Ozone Mapping Profiler Suite (OMPS) and Global Ozone Monitoring Experiment-2 (GOME-2) sensors, in addition to infrared data from VIIRS, AIRS and other geosynchronous/polar-orbiting sensors.

IMO provided daily online updates on the ongoing eruption from Bárðarbunga volcano (Holuhraun fissure) (IMO 2015), including any field observations and notes from meetings of the Scientific Advisory board. Satellite remote sensing data was an integral part of this monitoring and daily reporting of volcanic activity. For example, IMO used LANDSAT-8 (Land Remote-Sensing Satellite (System)-8) data to analyze the spatial footprint of lava flows,
<figure><img src="image_221.png" /><figcaption>**Fig. 7** Data from the Icelandic Meteorological Office (IMO) website a LANDSAT data as RGB composite of the flows on January 3, 2015; b as GIS layer see http://en.vedur.is/media/jar/myndsafn/full/20150115_afstodukort_ornefni_300dpi.png; and c ALI thermal from January 16, 2015 using the same geographical projection to allow comparison to the LANDSAT-8 data from January 3</figcaption></figure>
determine the most active portion (Fig. 7a) and develop a map of the ongoing activity for decision making (Fig. 7b). The combined images (Fig. 7a–c) show how IMO and other local authorities were able to use the high spatial resolution data to map out the full flow extent and also generate GIS data layers for use in comparison to other data from field observations and or seismic activity.

The activity from Bárðarbunga volcano along the Holuhraun fissure generated more satellite derived SO₂ imagery than for volcanic ash (Fig. 8). Figure 8a for AIRS on September 1 shows less detectable SO₂ than from GOME-2, Fig. 8b, and OMPS, Fig. 8c. Figure 8d–f, illustrate the influence of the sunlight on deriving UV satellite based measurements. For the OMPS sensor, Fig. 8f, the derived SO₂ is cut off as a result of the lack of sunlight. This impact can be significant for any northerly drift of the SO₂ cloud from the Holuhraun fissure.

Figure 8 shows the usefulness of using common spatial domains and temporal averaging of

satellite data to analyze for relative change. However, the background information on local infrastructure, populated locations, and transportation links as well as the ability to overlay mutli satellite data together is limited. Often Geographical Information Systems (GIS) are used to display different datasets together or to generate maps for hazard assessment. The need to compare different data sources and include supplementary information has led to the use of Virtual Globes.

## 5 Geo-Spatial Tools and Virtual Globe Applications

Satellite remote sensing has become an integral part of daily monitoring of volcanic activity (Webley et al. 2008) and is part of a suite of geophysical data utilized by volcano observatories (Webley et al. 2013). To combine all of these datasets together requires a Geospatial tool, remote sensing processing software or a virtual

<figure><img src="image_222.png" /><figcaption>**Fig. 8** Real-time daily Support to Aviation Control Service (SACS, http://sacs.aeronomie.be/) products, AIRS, GOME-2 and OMPS on September 1 (a, b, c) and October 1, 2014 (d, e, f) from Bárðarbunga/Holuhraun volcanic activity. Note these are daily composites given the polar orbiting nature of the satellites and that</figcaption></figure>

SACS (2015) have set both common geographical domains and measurement scales to ensure quick comparisons. These common geographical regions and temporal periods allow those in hazard assessment to compare the relative change in the SO₂ output without the need to process and/or re-project the data
globe. These Geospatial or Virtual Globe tools allow the user to overlay many different datasets and add in other geophysical data such as earthquake locations or GPS point data. To display remote sensing data within a Geospatial tool, the satellite imagery (often in Hierarchical Data Format [HDF], or Geostationary Earth Orbit Tagged Image File Format [GEOTIFF]) needs to be converted into shape (SHP) files with associated metadata. These files can be displayed along with other GIS data layers to produce hazard maps which can be used to assess the risk and mitigate impacts.

It is possible to use Virtual Globes to display the imagery and make rapid assessments of the hazard and its potential impact. Recently, Google Earth has been used for visualizing geospatial data (Webley et al. 2009; Prata and Prata 2012) but it requires the user to generate a Keyhole Markup Language (KML) or Keyhole Markup Zipped (KMZ) file of their own satellite imagery (Bailey et al. 2010). In early 2015, the ability for all to use Google Earth Pro was made possible (Google 2015) as it was publically available free of charge. This has the added advantage of being able to read in GEOTIFF and GIS SHP files, but there are still some limitations. Google Earth Pro will open automatically to its pre-defined start up. The user is then able to simply drag and drop their GEOTIFF or SHP file and Google Earth Pro will fly to the center location from the geospatial information in the associated file (Fig. 9). If the GEOTIFF file is too large in size or the SHP file has a large number of entries, the software will request the user to choose the desired image resolution. Once chosen, it will display the data, but as Fig. 9 shows, the scaling of the GEOTIFF data may lead to no useful information being shown in the overlay. By generating a GEOTIFF image file from ENVI or similar software rather than the default GEOTIFF data file, the user can display their data in Google Earth Pro with a more useful scaling for visualization. ENVI® is a geospatial product (see Table 2 for list) provided by Harris Geospatial (Harris Geospatial 2016) that combines advanced image processing and geospatial technology to allow the user to extract

useful information from remote sensing data and make better informed decisions.

Once the data are available in either a Geospatial tool or Virtual Globe, users can map the hazard and measure its spatial extent and potential for further impacts. Virtual Globes like Google Earth Pro bring a new mapping capability not available in Google Earth. Figure 10 shows how a hazard manager would load the data into ENVI or a similar image processing tool, and then map out a region of interest (ROI) using either points (red) or as a polygon (green). This can also be done in Google Earth Pro where the imagery is loaded and displayed as an overlay. Using the polygon tool, the hazard manager can map out the edge of the flow. Comparing the area from ENVI with its ROI tool and a pixel by pixel analysis to the results from Google Earth Pro with its polygon tool, the total mapped area for this flow was calculated as 76.13 and 76 km² respectively. The relative different was 0.13 km² or 0.02% difference, thus highlighting that Google Earth Pro allows those in hazard assessment and mitigation to quickly and accurately map out volcanic features, without the need for access to specific and often expensive remote sensing software.

Virtual Globes also allow for the intercomparison of satellite data from different sensors and across different spectral ranges with the same sensor. Figure 11 shows the ALI data, from Fig. 10, by displaying Band 1 (0.48–0.69 µm and 10 m spatial resolution panchromatic data) and a set of RGB composites using the VNIR, SWIR and MIR channels (0.43–2.35 µm and 30 m spatial resolution data). Note that the black area in the image overlay is a result of the satellite overpass and therefore no data is recorded in this region. It is important information for the decision maker as it shows that there is no satellite data but the flow could still exist in this location. More data is needed in this region to confirm the lack of lava flow. As the data are geolocated, the relative differences between channels can be easily compared and used to assess the location of the hottest part of the flow. Small, hot targets will produce the strongest
<figure><img src="image_223.png" /><figcaption>**Fig. 9** How to display GEOTIFF data in Google Earth Pro, using example from ALI Band 1 on January 16, 2015. Google Earth Pro allows the use of 'drag and drop', where the user can simply drop the GEOTIFF file into software. © 2016 Google Inc. All rights reserved. Google and the Google Logo are registered trademarks of Google Inc.</figcaption></figure>
<figure><img src="image_224.png" /><figcaption>**Fig. 10** ENVI® and Google Earth Pro workflow to analyze the spatial footprint of the flow from Band 1 ALI data on January 16, 2015. ENVI® analyzed area was 761,359 points or area of 76.13 km², Google Earth</figcaption></figure>

Polygon was 76 km². © 2016 Google Inc. All rights reserved. Google and the Google Logo are registered trademarks of Google Inc.

<figure><img src="image_225.png" /><figcaption>**Fig. 11** ALI data from January 16, 2015 displayed in Google Earth Pro®. a Band 1; b RGB Bands 432; c RGB Bands 543; d RGB Bands 654; e RGB Bands 765; and</figcaption></figure>

f RGB Bands 876. © 2016 Google Inc. All rights reserved. Google and the Google Logo are registered trademarks of Google Inc.

radiant signal in the SWIR and MIR data and by comparing the RGB data from the VNIR to the SWIR, operational hazard managers can assess the most hazardous parts of the flow and thus where to prioritize resources.

For some of the shorter wavelengths, the resultant satellite data may be saturated so longer wavelength data, greater than 2–3 µm, may be needed to assess subtle changes (see use of thermal infrared data (10 µm) over mid-infrared
data (3.7 µm) in Webley et al. (2013)). By combining the data together (both across different satellite sensors and across different spectral ranges), hazard managers can make a quick assessment that can assist those in the field and reduce the potential impact to local population or infrastructure.

Virtual Globes, like Google Earth Pro highlighted here, and GIS tools (see Fig. 7b) can be used as the interfaces for those in hazard assessment to visualize and analyze the available satellite data. From the analysis in Figs. 10 and 11, KMZ and KML data files can be generated for comparison to other geophysical data along with georeferenced maps, with associated data such as latitude/longitudinal grids, distance scale bars, population centers and transportation links (Fig. 12). As with Fig. 11, the black area highlights the region of no data due to the swath edges from the satellite data.

The insert in Fig. 12 shows how a user is able to define site visit locations using the place marker option in Google Earth Pro. The latitude and longitude location can be extracted and used for fieldwork planning and logistics. With more real-time geophysical data being developed for the Virtual Globe market, as well as the development of online geospatial tools, such as the Google Earth Engine and Google Maps Engine,

the use of the tool will continue to increase among the real-time hazard assessment community.

# 6 Summary

There has been an integration of remote sensing data and geospatial tools into day-to-day operations for volcano monitoring. They are used to perform a more effective hazard assessment of ongoing volcanic activity. Remote sensing data are now available from ultraviolet to microwave wavelengths (spectral); from m's to km resolutions (spatial) and from daily to weekly repeat times (temporal). There is a trade-off between the spectral, spatial and temporal and it has been the combination of all available data that has increased the uptake of the remote sensing data into routine volcano monitoring. Satellite data provides an overview of the local, regional, country-wide, continental, and global scale of the volcanic eruptive events. Effective visualization of these data can then significantly help decision makers to communicate the impact to those at risk in an effective and efficient manner.

This chapter highlights examples where satellite remote sensing was used during volcanic eruptions to: (1) improve the assessment of

<figure><img src="image_226.png" /><figcaption>**Fig. 12** ALI data from January 16, 2015 map as generated from Google Earth Pro. Map shows latitude and longitude grid, scale bar to show distances in km, North arrow to align image N-S, the locations of all the volcanoes, airports, roads (yellow lines) and also any</figcaption></figure>

population centers. Inset shows area zoomed in on the flow with user defined locations for site visits of Flow edge-North and Flow edge-South. © 2016 Google Inc. All rights reserved. Google and the Google Logo are registered trademarks of Google Inc.
potential for dome collapse using meter resolution radar data (Merapi 2010); (2) examine the changing shape and thermal properties of a large fissure eruption using multi wavelength and resolution data (Tolbachik 2012–2013); and (3) map the spatial extent of thermal activity from volcanic flows using high resolution data and routinely available volcanic gas measurements (Bardarbunga/Holuhraun 2014–2015). Additionally, the chapter shows how Virtual Globes have become an integral tool for hazard assessment and new developments will lead to a greater use of these in real-time assessments.

Remote sensing data and geospatial technologies are now critical parts of the monitoring toolbox. To be used in a real-time event, the data needs to be collected, processed and displayed routinely, i.e. for every possible satellite overpass and using the same geographical domain. Satellite data providers have created several online tools to undertake the initial hazard assessment. To combine all the data together, they need to be on common projections and have associated metadata on the spectral, spatial and temporal resolutions. Then the choice is on the best geospatial technology for the application and/or assessment required. This can be a GIS tool where ancillary data is already in a GIS format, or it could be a Virtual Globe where other data is in a KML/KMZ format. Using the new geospatial technologies to display, visualize and analyze the routinely (automatically) acquired and processed remote sensing data will provide the best tools for real-time hazard assessment, in essence building a system ready if an eruption occurs, rather than building the system as it is developing.

**Acknowledgements** We would like to thank the remote sensing students of the Geophysical Institute, University of Alaska Fairbanks for assisting us in acquiring and analyzing the Tolbachik AVHRR, ASTER and MODIS data. This work was undertaken partially as part of a graduate level class and allowed us to further analyze the most appropriate data for this manuscript. We thank the Natural Environment Research Council (NERC) Centre for Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET) for support for Dr. Watson.

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<figure><img src="image_227.png" /></figure>
# Re-enchanting Volcanoes: The Rise, Fall, and Rise Again of Art and Aesthetics in the Making of Volcanic Knowledges

Deborah P. Dixon and Daniel J. Beech

**Abstract**

Current day volcanology largely tends to an instrumentalist view of art as, in its mimetic form, capable of providing proxy data on the timing and unfolding of particular volcanic events and, in its impressionistic form, of conveying the sublime grandeur of volcanic events and scenes. In this chapter, we note that such a reductionist view of what science is unhelpfully glosses over a much more complex disciplinary lineage, wherein both art and aesthetics played a key role in knowledge production concerning volcanoes. Using the work of Sir William Hamilton and Mary Somerville as case studies, we emphasise that art and aesthetics were part and parcel of both an 18th and 19th century approach to the study of volcanoes, and the making of particular scientific audiences. What is more, it is this lineage that provides a creative reservoir for more recent efforts that cut across scientific and arts divides, such that the ‘communica-
tion’ of the nature of volcanoes becomes a multi-media, multi-affective endeavour that speaks to a diverse range of publics.

**Keywords**

Art • Aesthetics • Hamilton • Somerville • Art-science collaborations

# 1 Introduction

As many of the authors in this edited collection attest, communication is an embodied practice that serves to impart information, allowed for by sensory and cognitive modes of knowledge making. These modes are biologically as well as socially embedded, framing and valuing particular ways of knowing (or epistemologies) that

<footnote>D.P. Dixon
School of Geographical and Earth Sciences,
University of Glasgow, Glasgow, UK
e-mail: Deborah.Dixon@Glasgow.ac.uk</footnote>

<footnote>D.J. Beech (✉)
Department of Geography and Earth Science,
Aberystwyth University, Aberystwyth, UK
e-mail: dib8@aber.ac.uk</footnote>
tell us how to ‘see’ the world; they operate to
sustain or frustrate power relations between and
amongst people and things, mobilising a range of
affective relations and emotions. In this chapter,
we bear this expanded notion of communication
in mind as we outline something of the history of
how a knowledge of volcanoes was produced
and disseminated during the 18th and 19th cen-
turies—a crucial period during which volcanol-
ogy was to became a modern-day scientific
enterprise. As we go on to outline below, this
making modern of a discipline was predicated on
a shift in the way in which knowledge was col-
lected and disseminated. A combination of
institutional entities, theoretical frameworks and
methodological devices (Good 2000) led to a
reorganising of scientific communities and audi-
ences, but also the process through which sci-
entific practice was undertaken.

In the 18th century we could still observe a
Renaissance ‘truth-to-nature’ approach to
knowledge gathering that made little separation
between science and art. Where the artist pro-
vided a means of accurately observing and cap-
turing the complexity of a physical scene, the
scientist’s finer ‘touch’ teased out details that
escaped such vistas. Complementary to each
other, these efforts not only allowed for the
production of knowledge concerning the realities
of Nature, but its particular mode of dissemina-
tion, such as the exchange of letters and sketches,
as well as interesting objects, via scientific soci-
eties. Many scientific artefacts, representations
and antiquities emerged from the expeditions
embarked upon across Europe, and particularly
the Mediterranean, by scientists such as Sir
William Hamilton (1730–1803). Field-walking
in the volcanic landscapes of central and south-
ern Italy provided him the grounded knowledge
required to recreate volcanic environments in the
form of textual and visual illustrations, providing
a mechanism though which to report the
knowledge upon which volcanology is now lar-
gely predicated (Schnapp 2000; Vaccari 2008).

In the 19th century, however, we can discern
more of an emphasis upon a systematised
description and explanation of natural phenom-
ena that glossed over the individualised and

embodied presence of the scientist. Mary Som-
erville's (1780–1872) letters, for example,
remained testament to the visceral impact of
volcanic landscapes, but her textbooks—*Physi-
cal Geography* (1854) and *On the Connexion of
the Physical Sciences* (1858)—conveyed more of
a Gods-eye view of the cause-effect processes at
work. The cultivation of a mechanical mode of
objectivity reworked the communication of sci-
entific knowledge more broadly, as indicators of
the imaginative work of the scientist were erased
from the writing up process (as observed in the
emergence of the passive tense, for example, and
the valuing of a prescriptive report template), but
also in image-making. As the now iconic article
by Daston and Galison (1992) makes clear, there
was to emerge a polarisation of the personae of
the artist and the scientist; ideals of actuality,
accuracy and credibility had begun to be set apart
from the imaginative, descriptive realms of the
arts and humanities (Sigurdsson 1999). As the
21st century unfolds, however, we are witness to
more inter-disciplinary collaborations that do not
so much ‘bridge’ the arts and sciences divide, as
worry at their differences, and, often times, look
back into the history of both for inspiration.

Such a history is of interest in and of itself
insofar as it reveals the often overlooked yet
crucial role of not only sensory (or aesthetic)
experience in the making of a knowledge of
volcanoes, but of artistic practices also. The latter
not only provided for the dissemination of a
visual literacy concerning volcanic forms and
attributes, but also facilitated a scientific curiosity
and wonder. As Atkinson (1998) remarks, the
‘scientific approach’ that is so often taken for
granted today as a common sense, seamless
mode of knowledge production belies a rich,
often tension-ridden heritage of ‘science in the
making,’ as various tropes and techniques
emerged and became standardised at the expense
of others. The adventures of Hamilton and
Somerville were not the exception, but instead
typify modes of scientific exploration and
knowledge discovery of the 18th and 19th cen-
turies within the field of volcanology, each
helping to shape ‘a new science of mankind’
(Schnapp 2000: 123). The explorations of