Choice of Airport in Extinguishing Wildfires: Model and Cases

Louise Ekström and Christine Große

Department of Information Systems and Technology, Mid Sweden University, Holmgatan 10, Sundsvall, Sweden

Keywords: Balanced Transportation Problem, Wildfire, Regional Airport, Flying Forces, Real-life Application.

Abstract: This paper develops a model to support the optimal choice of an airport as a base for the flying vehicles that

are operated to extinguish wildfires and forest fires. Based on experiences from the two largest wildfires in

Swedish history, this study models the optimisation as a balanced transportation problem. In both cases, the

model selected the airport that is closest to the fire area. If the capacity of the chosen airport was insufficient

to host all of the flying vehicles, then the model added a second airport which is also nearby the wildfire area.

The cases demonstrate that the total cost of the operation is lower when the extinguishing work is concentrated

in an area that has a short distance between the airport and the fire, the fuel depots and the pilots’

accommodation. Improved access to relevant data in the context of crisis management by air could allow for

the inclusion of additional parameters and correct data in the optimisation model, which could in turn provide

more comprehensive decision-making support.

1 INTRODUCTION

Sweden consists of large forest areas, and woodland

comprises about 65% of the land area in the country.

A considerable number of wildfires occur in Sweden

each year, while severe forest fires emerge only once

or twice per decade (Hansen, 2003). However, in a

recent five-year period, two years witnessed heavy

wildfire seasons. In the summer of 2014, a large

wildfire occurred in Surahammar in the county of

Västmanland in Sweden. This fire destroyed about

14,000 hectares of forest (Länsstyrelsen i

Västmanlands län, 2014). Four years later, in 2018,

several large forest fires emerged throughout the

Swedish countryside. Many of them were difficult to

address because of the extent, location or scarcity of

resources. The four largest areas on fire were in the

Swedish counties of Gävleborg, Dalarna, Jämtland

and Västernorrland. These fires covered a total area

of more than 18,000 hectares (MSB, 2018).

To extinguish such large wildfires, firefighting

operations require many resources, such as trained

personnel, proper equipment and water. One of the

most effective resources for extinguishing forest fires

are the flying forces (Coen, 2008). These forces

include airplanes for extinguishing fires as well as

helicopters from civil organisations, public sources

and civil protection organisations of other countries.

https://orcid.org/0000-0003-4869-5094

Because of the vast distances and extent of roadless

areas in Sweden, the distances between airports and

wildfire sites significantly affect the economic losses

that accompany wildfires. Therefore, the selection of

an airport as a base for co-ordinating firefighting

activities impacts not only societal security but also

the cost of the fire extinguishing work and the

economic loss due to burned woodland.

In view of this, the aim of the present study is to

develop a model that supports the selection of the

optimal airport to act as base for flying resources

during fire extinguishing operations. To select the

ideal airport or combination of airports, this study

examines a balanced transportation problem that

minimises the cost of fire extinguishing.

The remainder of the article is structured as

follows. Following this introduction, Section 2 briefly

outlines air-based firefighting practices as well as

previous research on the topic. Then, Section 3

describes the construction of the model, including the

assumptions and delimitations. In addition to

presenting the applied data from two wildfires in

Sweden, Section 4 provides the results and discusses

certain implications. The conclusion summarises the

article and indicates areas for improvement and

further research.

364

Ekström, L. and Große, C.

Choice of Airport in Extinguishing Wildﬁres: Model and Cases.

DOI: 10.5220/0009166703640371

In Proceedings of the 9th International Conference on Operations Research and Enterprise Systems (ICORES 2020), pages 364-371

ISBN: 978-989-758-396-4; ISSN: 2184-4372

2 BACKGROUND

2.1 Air-based Firefighting

Flying forces are effective and efficient because they

perform aerial firefighting that can approach remote

areas that are difficult to access with land-based

resources. In addition, airplanes and helicopters can

quickly transport a large amount of water to the site

of the fire and unload it from an overhead position.

Such vehicles can collect water from a lake or other

watercourse in the surrounding area without landing.

Sweden currently maintains no flying resources that

are entirely dedicated to firefighting. Instead, such

resources are borrowed from several partners in the

public and private sectors at both the national and

international levels, including from other countries in

the European Union, such as France, Italy, Spain and

Germany. Helicopters are also loaned by civil and

private organisations, the military or even other

countries (Hansen, 2003).

In the practice of fire extinguishing by flying

resources, regional airports provide bases at which

the flying forces can, for example, receive service,

refuel and access parking. To fulfil this role, airports

must meet several requirements, such as an adequate

capacity for the airplanes and helicopters which will

be used for firefighting. In addition, they must

maintain access to fuel, support lodging for pilots and

staff, and provide the necessary service and logistics

for the flying resources.

Another factor that influences the selection of an

airport as a base for fire extinguishing is its location

in relation to a particular wildfire area. From a

strategic point of view, it appears relevant to use an

airport that is centrally located in relation to

interdependent infrastructures and services as well as

proximal to site of the fire, as such characteristics can

reduce irrelevant flight time. Since airplanes and

helicopters for firefighting are rather slow-flying

vehicles, the distance between the airport and the

wildfire significantly affects the flight time. These

conditions encourage the selection of an airport that

is located as close as possible to the wildfire area.

2.2 Previous Research

There are many studies in the field of wildfires and

fire extinguishing. For example, previous research

has examined effective and efficient strategies for

firefighting operations (Mendes, 2010). Other

research has investigated the performance of such

operations and identified areas for improvement in

these approaches (Coen, 2008). Moreover, some

studies have developed models for risk analysis to

analyse the extent of the risk of a wildfire in certain

areas and, on this basis, create prognoses that can

support decisionmakers in planning risk reduction

strategies and crisis management (Ekström, 2003;

Pandey and Ghosh, 2018). In the context of

firefighting operations in forest areas, another study

has explored how to optimise the combination of

different resource types (Donovan and Rideout,

2003).

Previous research has also targeted other societal

sectors to examine optimised resource allocations.

For example, in the context of emergency medical

care, studies have applied decision models to

investigate ideal locations for rescue services (Yang

et al., 2007) or appropriate allocation of resources to

various stations to reduce response time while

achieving maximum area coverage (Liu et al., 2017;

McCormack and Coates, 2015). In this context, Liu et

al. (2017) have considered which rescue service

stations to utilise as well as how many vehicles to

place at the stations to reduce stand-by costs and

increase the efficiency of emergency response.

Several studies on wildfires have applied

simulation and optimisation approaches to determine

how to allocate resources of various types. Their aim

has been to support preparatory emergency response

planning to facilitate firefighting operations that are

as effective as possible in the event of a wildfire (Lan

et al., 2011; Rodríguez-Veiga et al., 2018). Many

studies have focused on preparatory emergency

response in terms of, for instance, where to place

airplanes for fire extinguishing in advance to reduce

stand-by costs. Such studies have assessed at which

airport to station the airplanes to decrease the

response time and the distance to areas that have a

high risk of wildfires (Bilbao Marón, 2013; Fiorucci

et al., 2005). Bilbao Maróns (2013) has conducted

forecasts that identify areas with a higher risk of

forest fires and account for the airport capacity and

distance to a potential fire to determine the optimal

solution.

However, few studies have examined the ideal

placement of flying resources to minimise costs

during a wildfire which must be extinguished by

flying resources. This study addresses this gap by

considering examples from the major wildfires in

Sweden in 2014 and 2018 and examining the issue as

a balanced transport problem. It ultimately proposes

a model for the selection of airports as bases for

firefighting by flying forces.

Choice of Airport in Extinguishing Wildﬁres: Model and Cases

365

3 MODELLING OF THE

TRANSPORTATION PROBLEM

3.1 Foundations

A transportation problem is a specific minimum-cost

flow problem (MCFP) for determining the optimal

solution to a problem. The method is popular because

it can be applied in several ways and to many domains

(Sonia, 2012).

A MCFP sends a flow from a number of supply

nodes to one or several demand nodes through the

arcs in a network at the lowest possible total cost

(Sonia, 2012). The subject of a transportation

problem is often cargo that moves alongside the arcs.

Each supply node provides a restriction to the amount

of goods that it can supply, while the demand nodes

have a limit to the minimum amount that they must

receive. If the total demand and total supply are equal,

then the problem is called a balanced transportation

problem.

The arcs between the nodes specify how the goods

can be transported. In addition, each arc in the

network reports the cost of shipping the goods

between the connected supply and demand node. At

times, arcs can demonstrate a constraint to the number

of units that can be transported via the specific arc.

A solution for this problem indicates the number

of units that can be transported on each arc. A general

formulation can be created to minimise the total cost

for the particular transportation problem. In addition

to such general formulation, sets of constraints aim to

ensure that the provided solution does not exceed the

maximal possible supply and simultaneously fulfils

the demand as fully as possible (Winston, 2004).

This paper applies an optimisation model in the

form of a transport problem to examine the optimal

airport or combination of airports to act as a base for

fire extinguishing by flying forces. The following

section describes the model and its particular

delimitations and assumptions.

3.2 Model and Conditions

3.2.1 Mathematical Model

This section details the mathematical model for the

optimisation. Equation 1 presents the objective

function that minimises the total cost of the

transportation problem, while Equations 2 and 3

specify the constraints. Table 1 outlines the sets,

variables and parameters that appear in the model.

Table 1: List of sets, variables and parameters.

Ter

Descri

tion

∈

Set of flight vehicle types

∈

Set of airports

Total cost that is minimised

umber of flying vehicles of type f at airport a

Cost for parking flying vehicles of type f at airport a

Capacity of airport a

Distance from airport a to the forest fire

Distance from airport a to the nearest city

Distance from airport a to the stock of aviation fuel

Total number of flying vehicles in use

Total number of transports to fulfil demand of

aviation fuel during the extinguishing operation

Fuel consumption of flying vehicles of type f

Fuel consumption of trucks transporting aviation fuel

Fuel consumption of vehicle transporting pilots

Price of aviation fuel

Price of diesel

First, the following model accounts for several

aspects, such as the cost of storing the vehicles at an

airport, the cost of flying to approach the wildfire and

to return to the airport, the cost of transporting pilots

between the airport and their accommodation, and the

cost of transporting aviation fuel to the airport.

min𝑧 = 𝑥



∈∈

(1)

∙𝑝



+2𝑛𝑐



𝑑



+4𝑚𝑜𝑒



+𝑏𝑙𝑠





The model applies the constant 2, which conveys

that the cost of flying appears twice: first when

airplanes or helicopters fly to the fire and again when

they return to the airport. The constant 4 indicates that

there are two routes for land-based transport of pilots

and staff—the route from the airport to the city in

which their accommodation is located and the return

route—and that there at least two pilots for each

flying vehicle.

Second, two constraints are formulated to frame

the transportation problem.

∀𝑎 ∈

𝐴

;0≤𝑥



≤𝑘



(2)

𝑥



∈∈

=𝑡

(3)

As Equation 2 demonstrates, the first constraint

indicates that the number of flying vehicles that are

placed at an airport cannot be less than zero or greater

than the maximal capacity of the airport. Equation 3

states that the sum of the flying vehicles that are

stationed at all airports must be equal to the total

ICORES 2020 - 9th International Conference on Operations Research and Enterprise Systems

366

number of vehicles that are in use during firefighting

operations.

3.2.2 Delimitations and Assumptions

The model development focused solely on cost-

effective selection of airports in the context of

wildfire extinguishing by flying forces. It considers

flying resources, including airplanes and helicopters,

which can collect firefighting water from a

watercourse. Accordingly, it excludes other

resources, such as ground-based firefighting

resources. In the Swedish context, such delimitation

is appropriate since the large forest areas contain few

roads, which significantly hampers time-efficient

emergency response by ground-based vehicles.

The model has been delimited to determine the

optimal airport or combination of airports. In Section

4, two Swedish cases are used to evaluate the

optimisation model. This study selected these two

areas, namely Surahammar and Ljusdal, because they

contended with major forest fires in 2014 and 2018,

respectively. For each area, three airports are

preselected that meet several requirements. First, they

have the capacity to act as a base during firefighting

efforts. Second, they are located near the forest fire

area. In fact, two of the selected airports were utilised

during fire extinguishing operations in the individual

cases. Third, the airports, which are national, regional

or military, are be regularly operated or classified as

emergency response airports. This selection is based

on the assumption that such airports provide adequate

facilities and services to act as a base for crisis

management in the event of a wildfire by, for

example, providing infrastructure for operations

management, ground service for flying vehicles and

around-the-clock manning. This third requirement

implies that closed or privately owned airports are not

considered. The preselected airports are Stockholm-

Västerås Airport, Sundsvall-Timrå Airport, Uppsala-

Ärna Airport, Åre-Östersund Airport and Örebro

Airport.

4 CHOICE OF AIRPORTS: TWO

SWEDISH CASES

4.1 Context and Data from Wildfires in

Surahammar and Ljusdal

This study applies the optimisation model to two

Swedish cases, namely Surahammar and Ljusdal.

Major wildfires occurred in both areas in recent years.

In 2014, a major wildfire raged in the area of

Surahammar and developed into the largest forest fire

in Swedish history at the time (Länsstyrelsen i

Västmanlands län, 2014).

In 2018, a combination of heat and drought caused

even more extensive wildfires. These fires burned

more than 25,000 hectares of forest, which

corresponds to almost twice the area that was on fire

in 2014. Compared to the 110 wildfires that occur in

an average season, more than 500 fires were detected

by the rescue service in the summer of 2018 (Sjökvist

et al., 2019). The most severe fires were concentrated

in the middle of Sweden, and the area of Ljusdal was

heavily affected (Ljusdals kommun, 2018).

Aviation—and, thus, the regional airports—had a

crucial role in combatting the forest fires.

Surahammar is located near several airports and

cities, including the Swedish capital, whereas Ljusdal

is situated further north at a greater distance from

cities and airports.

Apart from airports that are located nearby

Surahammar and Ljusdal, the pre-selection of airports

for the optimisation included those that were used

during the extinguishing operations in 2014 and 2018,

respectively. During the wildfire of Surahammar,

Stockholm-Västerås Airport (MSB, 2015) was the

base for the flying forces. In addition, this study pre-

selected Örebro Airport and the military airport Ärna

in Uppsala, Sweden, which fulfil the requirements in

Section 3.2.2. During the wildfire in Ljusdal, Örebro

Airport was the base for the flying resources. This

study also added the airports of Åre-Östersund and

Sundsvall-Timrå to the optimisation because they

meet the aforementioned criteria and are classified as

airports for emergency response.

The calculations apply data from public reports

regarding the extinguishing work, public statistics in

the context of aviation and a well-founded estimate of

completing aspects.

In the most intensive phase of the firefighting, 14

helicopters and four airplanes were used (Ljusdals

kommun, 2018; Länsstyrelsen i Västmanlands län,

2014). In the first case, airplanes were operational on

1,533 occasions, and the number of helicopter

operations was estimated three times as high as the

airplane operations. Airport capacity estimates were

based on the number of operations per flying vehicle

and the possible number of flights from the airport in

accordance with public statistics from the Swedish

Transport Agency (Transportstyrelsen, 2019). The

airport capacity was determined by dividing the

number of operated flights per day by the number of

operations per flying vehicle.

The calculation of staff transport between the

accommodations and airports included the fuel

Choice of Airport in Extinguishing Wildﬁres: Model and Cases

367

consumption of a minivan of the type Renault Traffic.

The transport of aviation fuel was based on fuel

consumption data for a truck of the type Scania S 500.

Since the public reports do not include any details

regarding the type of helicopter, this study assumes

that they were Blackhawk UH-60 aircrafts, which the

Swedish military operates. Aviation fuel

consumption was based on estimates (e.g. Military

Advantage, 2019). The airplanes for fire

extinguishing were Canadair CL-415 airplanes

(MSB, 2018). The municipality of Ljusdal has stated

that the wildfire was under control after a period of

21 days. This most intensive phase in the second case

was of approximately the same duration as the fire in

2014.

Other operational costs, such as those to land and

park at the airports, were collected from the pricelists

of the respective airports (Sundsvall-Timrå Airport,

2015; Swedavia Airports, 2019; Örebro Airport,

2014). Stockholm-Västerås Airport applies

Swedavia’s pricelist, whereas the state-owned

military airport of Uppsala-Ärna has not provided any

public prices. For the latter airport, this study

estimated the cost to be half of the lowest fees that

were specified by Stockholm-Västerås Airport. To

calculate the cost, the landing fees were multiplied by

the number of days of firefighting and the weight of

the flying vehicle. Parking fees reflect 24 hours.

The distance between the airport and a nearby city

for the accommodation of pilots was based on data

from Google Maps, which offered the fastest

connection. It remains uncertain which fuel depots

the airports use to refill their aviation fuel storage, but

this study selected Bromma Airport as the starting

point for the aviation fuel supply. The distances

between the airports and the two fire areas were set to

the linear distance between the respective airport and

the centrum of the fire-affected area according to

reports. The cost of aviation fuel was collected from

Hjelmco Oil (2017).

4.2 Results and Analysis

4.2.1 Case One: Surahammar (2014)

The optimisation model suggests that all airplanes

and helicopters that perform fire extinguishing work

should be placed at Stockholm-Västerås Airport to

realise the lowest possible cost. The model calculates

the total cost to be slightly more than 1 million

Swedish kroner (SEK). During the forest fire in 2014,

Stockholm-Västerås Airport served as the base for the

firefighting activities by air. The results of this

optimisation model confirm that the selection of

Stockholm-Västerås Airport was the optimal decision

with regard to the cost of the operations for three

reasons: it is closest to the area, it is the shortest

distance from the nearest city, and it has the capacity

for all flight vehicles.

4.2.2 Case Two: Ljusdal (2018)

The application of the optimisation model to the case

of Ljusdal returned a total cost of slightly more than

2.5 million SEK. For this case, the model identified a

combination of two airports as the optimal solution.

Specifically, all airplanes should be placed at

Sundsvall-Timrå Airport, while the helicopters

should be stationed at two airports, namely

Sundsvall-Timrå and Åre-Östersund. Since none of

the airports has the capacity to host all of the

firefighting helicopters, these aircrafts must be placed

at two airports. Sundsvall-Timrå Airport should be

filled with as many helicopters as possible, and the

remaining helicopters should be stationed at Åre-

Östersund Airport. In this case, the model still

recommends the airport that is closest to the wildfire

as the host for the airplanes, as it is the most expensive

factor in fire extinguishing operations.

The model did not suggest Örebro Airport as the

optimal choice for the flying resources in the second

case, which implies that the decision to use this

airport as the base for the extinguishing work in 2018

was not optimal. This result validates the criticism

that officials from the rescue service expressed

following the event. They noted, for instance, that the

choice was ineffective because of the significantly

greater distance of Örebro Airport from the fire area

compared with Sundsvall-Timrå Airport. In departing

from the choice in 2018 to locate all airplanes at

Örebro Airport, the optimisation model returned an

increase in the total cost to slightly over 3.5 million

SEK. This result demonstrates that the total cost of

the fire extinguishing work could have been

substantially lower if the airplanes had been moved to

Sundsvall-Timrå Airport instead. Discussions of this

issue occurred as the firefighting was ongoing, but

they produced no consequences for the operation.

One reason for the utilisation of Örebro Airport as the

operational base could be that the airplanes were

already stationed there and ready to participate in

firefighting operations. At the beginning of the

summer, the Swedish Civil Contingencies Agency

(MSB) sent a request to the European Union for the

placement of fire airplanes in Sweden with the

preventive purpose of enabling rapid emergency

operations (MSB, 2018). When the international

flying forces arrived, they were placed at Örebro

ICORES 2020 - 9th International Conference on Operations Research and Enterprise Systems

368

Airport, which was probably because it is centrally

located in the country. Even if aircrafts were located at

Örebro Airport before they started the extinguishing

operation in Ljusdal, they should have been moved to

a closer airport during the operation. In view of these

results, the idea to move the base for the flying

resources further north should have been considered at

an earlier stage once it became clear that the forest fire

was difficult to control and extinguish. Such movement

could have reduced the cost of the extinguishing work.

5 IMPLICATIONS FOR

AIR-BASED FIRE

EXTINGUISHING

In general, an appropriate preparedness is necessary to

host airplanes and helicopters at several airports in all

regions of Sweden and especially during the summer

period, when the risk of wildfires is high.

As the 2018 case of Ljusdal reveals, the aircrafts

that carried out the fire extinguishing work should have

been hosted at an airport that is closer to the fire area

as opposed to Örebro Airport. Although such

preparedness may generate costs, the results of the

optimisation model indicate that preparedness can

provide a benefit to society by saving time and, in turn,

decreasing the loss of economic value. Such

operational preparedness further includes proper co-

operation and co-ordination between airports, pilots

and the MSB, which can be difficult to maintain.

The proposed model of the transportation problem

is rather simple, and it poses some advantages and

disadvantages in comparison to more complex models.

First, the model deliberately neglects many real-life

constraints, which is mainly due to the scarcity of

publicly available data about the Swedish cases.

Despite such limitations, the model not only

emphasises the importance of airports as critical

infrastructure but also exemplifies the benefit of formal

methods for decision-making in the context of crisis

management to, for example, select the optimal airport

for extinguishing operations. The simplicity of the

proposed model therefore facilitates its application to a

particular case. Nevertheless, the presented model

could be improved. For instance, developments could

consider fees for landing and air traffic control at the

included airports, the stand-by costs of airports for

facilitating a swift establishment of operation

management, labour costs for all personnel who relate

to a certain operation and other costs that are relevant

to the logistics and administration of the operation.

The proposed optimisation model can support

decisionmakers in their assessment of which airport to

choose for operations. Such assessment would then use

data about the actual area. This study relied on data

about the forest fires in Surahammar and Ljusdal,

Sweden. In the context of these cases, some data were

available, but well-founded estimates were applied for

certain parameters, such as airport capacity. This study

experienced information scarcity in regard to several

important factors. Such data and information must be

available to researchers and decisionmakers to

heighten the quality of decisions about firefighting

operations by air. Access to relevant data is a

precondition to yield more accurate and insightful

results from the suggested optimisation model.

The design of the model considers the distance to

the fire as a key parameter. However, the use of

additional parameters is recommended to gain a more

nuanced understanding of the factors that affect the

choice of the airport. The model could provide a more

detailed and realistic result if it includes more

parameters and weights for the different parameters.

Such weighting can indicate that one parameter is

considered more important than another and is thus

preferred at a certain cost. The experiences from the

wildfires in Sweden reflect that factors beyond the

distance to the fire, the nearest city or the stock of

aviation fuel can affect the decision of which airport to

use for operations during fire extinguishing efforts.

Therefore, further improvements to the optimisation

model can include aspects concerning time or

geographical coverage.

The incorporation of a risk analysis could also

enhance the model application. The choice of airport

assumes that resources should cover large areas to

ensure adequate preparation in the event of a new forest

fire in another part of the area. A developed model

could simultaneously consider several fire areas and

use the enhanced coverage to determine the optimal

base for airplanes and helicopters. The model does not

account for the route of the flying resources between

the wildfire and the watercourses. In the two Swedish

cases, this aspect was not relevant, as the areas

provided abundant resources for refilling the water

tanks. However, this aspect can be significant if the

model is applied to areas with a scarcity of

watercourses. A model that includes this routing could

then identify the optimal watercourse for the

extinguishing work in the area.

Finally, the optimisation model in this study could

be combined with those of previous works which have

focused on the optimal placement of resources for

preventative purposes.

Choice of Airport in Extinguishing Wildﬁres: Model and Cases

369

6 CONCLUDING REMARKS

This study has developed an optimisation model to

select the most suitable airport to serve as a base for

flying vehicles that carry out extinguishing work in

the case of a wildfire. The model was applied to

evaluate two Swedish cases: Surahammar in 2014 and

Ljusdal in 2018. In both cases, the optimisation model

primarily chose the airport that is most proximal to

the site of the fire. If the capacity of the chosen airport

was not sufficient to host all of the flying vehicles,

then one additional airport was selected from the

remaining airports that are located nearest to the

wildfire. The examples demonstrate that the total cost

of the fire extinguishing operation would be lower if

the work is concentrated such that there is a short

distance from the airport to the fire, the aviation fuel

depot and the pilots’ accommodation. The

optimisation model provided a reliable result because

it identified the same airport for the case of

Surahammar that actually acted as the base for the

extinguishing work in 2014. In addition, it

recommended Sundsvall-Timrå Airport in the second

case of Ljusdal for the lowest possible cost of the

operation in 2018. Thereby, the optimisation model

reveals that the actual choice of Örebro Airport as the

base for the flying resources was an improper

decision from a cost perspective, which confirms the

perceptions of officials regarding that matter.

To enhance its usefulness for relevant

decisionmakers, the proposed optimisation model

should be subject to improvement. For example, the

model could further include the risk of wildfires

occurring simultaneously in different areas or of a

new wildfire arising while the extinguishing work is

still ongoing in some areas. Future analyses could

consider a larger number and variety of airports and

flying vehicles or extend the model to include

ground-based resources. In addition, the surrounding

conditions and their effects on the optimisation

should be a topic of further research. Examples

include the potential rationing of refuel, necessary

availability of both communication services for the

operative crisis management and maintenance

services for flying vehicles, and staffing of the

different functions that relate to the transportation by

air. The latter also encompasses issues such as regular

staff changes and recreation possibilities during long-

lasting operations, such as wildfire extinguishing

efforts.

The optimisation model and result accuracy could

significantly improve if data and information are

publicly available. Heightened access to relevant data

in the context of crisis management by air could allow

for the inclusion of additional parameters and correct

data in the optimisation model, which can in turn

provide more comprehensive decision-making

support.

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