Industria

This section presents an overview of the approach adopted to achieve the objectives. A general overview of the research is described followed by the operational framework, which presents the technical flow of the research design. The dataset required for the research design is also reviewed to complete the description. An overview of the simulation method is then provided to give a logical flow to the model.

1.5.1 Overview of the Method

The methodology of this research relies strongly on ABM simulation based on the literature review and empirical study complemented by GIS analysis for the preparation and output analysis. The simulation was based on the assumption that risk perception will influence the population’s behaviour regarding decision-making during crises. This relates to the probability of people being impacted by the disaster. Behaviour is commonly influenced by the social and demographic characteristics of people. Moreover, spatial and environmental features, such as road networks, evacuation shelters’ location and accessibility can also contribute to populations’ capacity to cope with disaster.

The general concept of the ABM simulation is provided in Figure 1.9. In the ABM simulation, the synthetic population agents will be generated from census data, with a spatial distribution estimation using settlement areas drawn from a land use map. Regarding the evacuation decision-making processes, the spatial and environmental factors will be taken into consideration. A questionnaire survey with area sampling will be used to identify the household preferences regarding the decision-making processes

during evacuation. The identified result in the statistical data can then be used to characterise the agents’ behaviour during the simulation.

At the end of the simulation, the populations who remain in the hazard zones at the expected time of onset will be considered to be at-risk populations. The results are spatially visualized in GIS. Finally, the effectiveness of the disaster management plans is measured by the degree of the risk that can be reduced as well as the ability to reduce road traffic congestion during the evacuation process.

Figure 1.9 General concept of the involvement of the behaviour rule from the survey in ABM.

1.5.2 Overview of the Data Collection

Various data were involved in developing the model, both spatial and non- spatial, and also primary and secondary. A complete description of the dataset is provided in Chapter 3. Here, some additional information about the primary data collection (questionnaire survey) is elaborated.

The questionnaire was used to identify the variables that will be used in the simulation. There are five primary variables collected from the questionnaire

Census Data Synthetic Population Agent ABM Questionnaires Data Socio-economic Properties Perception, Evacuation Behavior Behaviour Rules Socio-economic Characteristic Perception, evacuation behavior Interaction

Interaction

Matching

surveys, namely: socio-demographic characteristics that express social vulnerability, perceptions of volcanic hazard, decision-making behavior, interaction during the crisis, and also past evacuation experience (see Appendix 1.1). These data (mainly the perception of volcanic hazard, decision-making behavior and interaction during the crisis) will be used to generate population agents for the ABM simulation (Figure 1.9). Stratified random sampling was applied to conduct the survey. A total of 120

household member samples, represented as building units, were selected randomly for each building block (dusun), with the distance from the volcano as the stratified value. This area segmentation is based on the consideration that each dusun will have one command (Rukun Tangga) and commonly, in rural areas of Indonesia, homogenous social characteristics. The following figure illustrates the sampling selection method.

Figure 1.10 Example of sampling selection.

The participants were distributed proportionally across all zones (Figure 1.10). Each zone consists of three villages (dusun) as a sample, which was selected randomly using the randomise tool in Quantum GIS (see Figure 1.11). For the first 5km zone, three relocation areas were used, as the people within this area had been relocated. A settlement (the building footprint) from each village from the selection set was extracted using intersect analysis. Similar to the village selection process, the buildings

group of each village was randomised to select 10 buildings which were used as samples. This random selection resulted in 120 buildings in total (Figure 1.12) (see Appendix 1.2 for the survey results). Finally, the selected buildings were exported to Keyhole Markup Languge (KML) to enable this to be imported into GPX Viewer (Android Application) for a field guide during the survey.

Figure 1.11 Household selection and field identification procedure.

Villages Randomised Selected Villages

Intersect Building Footprint Buildings within Selected Village Randomised Selected Building Export to KML Loaded in GPX Viewer (Android)

Figure 1.12 Distribution of the samples.

1.5.3 Overview of Model Development, Experiments and Output Analysis

Overall, the principle of this research follows the interaction of GIS

(preparation) – ABM (simulation) – GIS (output analysis) (see Chapter 2). First of all, GIS is used to provide data for the simulation input. It is followed by the development of ABM and the simulations. The development process of the ABM was documented using the Overview, Design Concepts, and Details (ODD) approach (Grimm et al., 2006; Polhill, 2010). The general framework of the model was documented as a guide to implement the model in AnyLogic (Borshchev, 2013). The principal framework of ABM consists of three main agents, namely: volcano, stakeholder, and people (population), that interact within the geographical environment. The volcano acts as an agent, which initiates the hazardous situation and influences the

environment as a potential threat to the surrounding population. The other agents in the interactions are the stakeholder and the population (people). The stakeholder, in this case the authorities (government), has a significant

role in observing and analysing the activities of the volcano and in issuing warnings to the population, whereby the human agent (population) is

assigned an evacuation decision rule (Chapter 3). All human agents are also characterised by an individual risk assessment rule that makes it possible to capture the spatiotemporal dynamics of risk-taking during crises (Chapter 4). Based on those models, two scenarios (namely, the simultaneous and

staged strategies) are used to evaluate which is more effective in diminishing risk and reducing traffic congestion during evacuation processes. The whole simulation outcome can be exported to enable spatiotemporal analysis using GIS or statistical software. Various software packages were used to support the preparation, development and analysis, including ArcGIS, AnyLogic, R and R studio, Quantum GIS, Map Info Pro, Map Comparison Kit 3.2 (Visser and Nijs, 2006), and Origin Pro.