|Ari Sandhyavitri||Department of Civil Engineering, Faculty of Engineering, Universitas Riau, Pekanbaru City, Riau 28292, Indonesia|
|Sigit Sutikno||Department of Civil Engineering, Faculty of Engineering, Universitas Riau, Pekanbaru City, Riau 28292, Indonesia|
|Rizki Sahputra||Department of Civil Engineering, Faculty of Engineering, Universitas Riau, Pekanbaru City, Riau 28292, Indonesia|
|Heru Widodo||BPPT, Building of Ir. Soebagio – Geotech PUSPIPTEK, Kawasan Puspiptek Gedung 220, Tangerang, Banten 15314, Indonesia|
|Tri Handoko Seto||BPPT, Building of Ir. Soebagio – Geotech PUSPIPTEK, Kawasan Puspiptek Gedung 220, Tangerang, Banten 15314, Indonesia|
|Rizki Ramadhan Husaini||Department of Civil Engineering, Faculty of Engineering, Abdurrab University, Jalan Riau Ujung 73, Pekanbaru City, Riau 28292, Indonesia|
Quick responses in managing peatfire disasters in Indonesia are one key success in mitigating and controlling the risk of peatfire disasters. The aim of this study was to simulate and identify the optimum numbers and locations of fire brigade posts for improving their response times in mitigating peatfire events in Bengkalis Island, Riau, Indonesia. Network analyses were applied in the case of peatfire events on this island. The results of this study may assist local governments and fire brigade teams in developing a strategy to manage peatfires systematically. Hence, the results may contribute to the body of knowledge as a reference in systematically controlling peatfire disasters elsewhere in the world. This study proposed five steps in the identification of appropriate locations of fire brigade posts and performs two main steps to achieve this objective: (i) evaluating existing fire brigade posts’ service coverages; and (ii) developing three scenarios for simulating additions of one, two, and three posts. The results of this study improve fire brigade dispatch time performances as well as expand their service coverage areas from 40.7% to 62.4% within 60 minutes of dispatch time.
Bengkalis; Brigade posts; Dispatched time; Network analyses; Optimizing; Peatfires
Figure 1 Research location on Bengkalis Island, Indonesia
A number of peatland fire incidents on Bengkalis Island have occurred in the period from 2012 to 2016 (WWF, 2016). The fire incidents spread to two main locations: the middle western and southern areas (Figure 2). Two existing fire brigade posts were located in the District of Bengkalis and Bantan in 2019 (Figure 2b). The objective of this article is to investigate to what extent network analyses may assist in simulating and optimizing the number and locations of fire brigade posts in mitigating peatfires. In the period from 2013–2016, the greatest number of fires (983) occurred in 2014 (WWF, 2016) (Figure 2a). Various efforts have been conducted to mitigate these fire disasters, such as establishing two fire brigade posts. However, it has been acknowledged that the number of these fire brigade posts was too limited to cover the entire island area (WWF, 2016) (Figure 2b).
In fact, no research has been conducted to optimize the appropriate number and locations of fire brigade posts to mitigate peatfire impacts in Indonesia. Hence, there was a need to conduct research to identify the appropriate number of brigade posts and their locations using network analyses.
Figure 2 (a) Hotspot locations from 2013–2016 in Bengkalis, Indonesia; and (b) existing fire brigade posts and road networks in 2017
The island’s government and the Local Disaster-prevention Agency (Badan Penanggulangan Bencana Daerah; BPBD) must develop a strategic plan for selecting appropriate locations for fire brigade posts in the case of fire disaster events in a large coverage area in time deployment of under 1 hour. This study could be used as a reference in systematically mitigating peatfire disasters, not only in Indonesia but across the world.
The application of various methods for evaluating and identifying appropriate routes, locations, and destinations have been reviewed in several publications, including spatial and travel time relationships, a digital route guided map approach, possible shortest traveling times, and network analyses (Kumar et al., 2014; Sutikno & Murakami, 2015; Beere, 2016; Ranya et al., 2016). This study thus applies network analyses as a method to evaluate and calculate fire brigade dispatch times in Bengkalis, as this application is well-known, generally adopted, and proven to help solve cases of route analysis.
Beere (2016) reviewed applications of road network layer analysis that encompassed spatial and travel time relationships to identify the shortest road access to the nearest health service locations under the uncertainty of traffic congestion. Ranya et al. (2016) explored digital route–guided maps capable of locating health services within a designated area in emergency cases by the application of geographic information systems (GIS) using network analysis based on the shortest possible traveling time under time constraints in Khartoum, Sudan. Kumar et al. (2014) evaluated the safest, fastest ways to transport students from their homes to schools in India. Various variables were considered in the network analyses, including street networks, travel time, speed, and turning movements. The application of GIS software assisted this study to find optimal routes to reach designated schools. Sutikno and Murakami (2015) also used network analyses to evaluate and optimize shelter locations in the case of tsunami evacuation in Japan. A number of service areas for safe tsunami evacuation caused by earthquakes in Indonesia were also discussed in this study, which considered the combination of spatial and network analysis using GIS to improve tsunami mitigation measures. Thawongklang and Tanwanichkul (2016) evaluated an application of production-scheduling techniques for dispatching ready-mixed concrete and indicated that delivery delays could be minimized by improving delivery times, cutting operational costs. This study also used network analyses that encompassed various data inputs, such as distances, travel speed, and travel times, determined by GIS software (ArcGIS). The results have been proven to improve the delivery process performance.
Few studies have reviewed the application of network analyses in improving fire brigade performance, however, especially in abating peatfire disasters. This study utilizes network analyses to optimize the number and locations of fire brigade posts in mitigating peatfire disasters based on GIS. As mentioned, these analyses are common and widely applied in the evaluation and identification of appropriate routes and locations of designated areas. Network analysis, one of the methods provided by GIS software, finds least-impeded paths, such as finding the shortest road networks to transport students to their schools or fire brigade teams to fires (Fischer, 2014; Longley et al., 2001; Miller & Shaw, 2001 Sutikno & Murakami, 2015). Network analysis creates a network dataset and analyzes the network, a method that builds on several ArcGIS virtues, such as ArcCatalog for creating a network dataset, ArcMap for analysis, and ArcMethodbox for geo-processing (Fischer, 2014;; Kumar et al., 2014). The relationship between nodes and arcs in the network analysis is known as network topologies (Fisher, 1995).
Network analysis may assist governments in developing strategies for improving service coverage areas of fire-prevention teams for constrained dispatch times. Based on the network area analyses obtained from the ArcGIS, ArcCatalog, ArcMap, and the ArcMethodbox, the geo-processing results show that the two existing fire brigade posts have service coverage in Bengkalis Island of only 40.7%. This study simulated the additions of one, two, and three fire brigade posts, which improved fire brigade service coverage by 55% (from 40.7% to 63.4%).
The author would like to thank the Bengkalis Regency and the Civil Engineering Department of the University of Riau for providing facilities and map data for this article. We also express our gratitude to Insentif Riset Sistem Inovasi Nasional (INSINAS) research grants for providing financial support for this research.
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