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GeoEdu Insight Journal: Geography and Education Geography

an Open Access Journal

Spatial Analysis of Residential Fire Vulnerability Using Geographic Information Systems for Disaster Mitigation in Tambora District, West Jakarta

Fransiskus Emanuel
Widya Mandira Catholic University
Indonesia
fransiskusemanuell11@gmail.com
Natalia Yosefina Dula
Giovanni Catholic Senior High School
Indonesia
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  • Purpose of the study: Aim of this study was to analyze the spatial distribution of residential fire vulnerability in Tambora District, West Jakarta, and to identify vulnerability levels using Geographic Information Systems as a basis for supporting disaster mitigation and urban fire risk management strategies.

    Methodology: Quantitative descriptive research with a Geographic Information Systems approach was employed in this study. ArcGIS 10.8 software developed by Esri was used for spatial data processing. Overlay analysis, scoring techniques, field observations, and secondary data obtained from Google Maps imagery and related institutions were utilized to assess residential fire vulnerability.

    Main Findings: Results revealed that residential fire vulnerability in Tambora District was spatially distributed into low, moderate, and high categories. High-vulnerability areas were generally characterized by dense settlements and limited accessibility. GIS-based overlay analysis successfully generated a fire vulnerability map and identified priority areas requiring disaster mitigation measures and improved fire management strategies.

    Novelty/Originality of this study: Novel contribution of this study lies in the application of GIS-based spatial analysis to evaluate residential fire vulnerability in densely populated settlements of Tambora District. Spatial visualization produced through overlay analysis provides more comprehensive information for supporting evidence-based disaster mitigation and contributes to the development of urban fire vulnerability studies.

  • How to cite

    Spatial Analysis of Residential Fire Vulnerability Using Geographic Information Systems for Disaster Mitigation in Tambora District, West Jakarta. (2026). GeoEdu Insight Journal: Geography and Education Geography, 1(2), 61-68. https://doi.org/10.37251/gedij.v1i2.3542

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    1. S. Puttinaovarat and P. Horkaew, “Internetworking flood disaster mitigation system based on remote sensing and mobile GIS,” Geomatics, Nat. Hazards Risk, vol. 11, no. 1, pp. 1886–1911, 2020, doi: 10.1080/19475705.2020.1815869.
    2. K. Wang, Y. Yang, G. Reniers, and Q. Huang, “Understanding spatiotemporal patterns of typhoon storm surge disasters based on their tropical cyclone track clusters in China,” Geomatics, Nat. Hazards Risk, vol. 12, no. 1, pp. 2736–2754, 2021, doi: 10.1080/19475705.2021.1973120.
    3. W. Sibanda, G. Mukwada, and M. M. Hansen, “Disaster (Un)preparedness under cyclone Idai: Revisiting women activities in water and sanitation at tongogara refugee camp, Zimbabwe,” Cogent Soc. Sci., vol. 8, no. 1, pp. 1–19, 2022, doi: 10.1080/23311886.2022.2137964.
    4. X. Chen, X. Li, and Z. Liu, “Evaluation of earthquake disaster recovery patterns and influencing factors: A case study of the 2008 Wenchuan earthquake,” All Earth, vol. 35, no. 1, pp. 132–148, 2023, doi: 10.1080/27669645.2023.2207942.
    5. H. T. Luong, T. Q. Le, T. Van Nguyen, and V. K. Luong, “Community-based policing of natural disasters in Vietnam: Analysing the ‘four-on-the-spot’ model,” Polic. Soc., vol. 1, no. 1, pp. 1–15, 2024, doi: 10.1080/10439463.2024.2319819.
    6. J. Gerster and E. Maly, “Japan’s disaster memorial museums and framing 3.11: Othering the fukushima daiichi nuclear disaster in cultural memory,” Contemp. Japan, vol. 34, no. 2, pp. 187–209, 2022, doi: 10.1080/18692729.2022.2112479.
    7. M. Z. N. V. Kodur, “Vulnerability of structures and infrastructure to wildfires : A perspective into assessment and mitigation strategies,” Nat. Hazards, vol. 121, no. 8, pp. 9995–10015, 2025, doi: 10.1007/s11069-025-07168-5.
    8. A. T. Tjitrawati and M. K. Romadhona, “Affliction in the post Palu disaster: State failure to implement human rights standard on disaster management,” Cogent Soc. Sci., vol. 9, no. 1, pp. 1–20, 2023, doi: 10.1080/23311886.2023.2233255.
    9. O. Joseph, F. Samuel, and B. Agbola, “Institutional capacity and the roles of key actors in fire disaster risk reduction : The case of ibadan , Nigeria,” Int. J. Disaster Risk Sci., vol. 13, no. 5, pp. 716–728, 2022, doi: 10.1007/s13753-022-00440-3.
    10. R. Ba, Q. Deng, Y. Liu, R. Yang, and H. Zhang, “Multi-hazard disaster scenario method and emergency management for urban resilience by integrating experiment – simulation – field data,” J. Saf. Sci. Resil., vol. 2, no. 2, pp. 77–89, 2021, doi: 10.1016/j.jnlssr.2021.05.002.
    11. D. Zhang and J. Wang, “Research on the optimization of urban emergency shelters considering flood disaster risks,” Geomatics, Nat. Hazards Risk, vol. 16, no. 1, pp. 1–18, 2025, doi: 10.1080/19475705.2025.2585171.
    12. Y. J. McDonald et al., “Community-based participatory geographic information systems: Informing a long-term drinking water research collaboration,” Ann. Am. Assoc. Geogr., vol. 116, no. 4, pp. 1–22, 2026, doi: 10.1080/24694452.2025.2601315.
    13. W. Zhu and J. Chen, “The spatial analysis of digital economy and urban development: A case study in Hangzhou, China,” Cities, vol. 123, p. 103563, 2022, doi: 10.1016/j.cities.2022.103563.
    14. E. T. Mutch and A. B. Newsam, “Hand-drawn historic maps: Utilization and conversion of unique features into geographic information systems (GIS),” J. Map Geogr. Libr., vol. 20, no. 3, pp. 117–136, 2024, doi: 10.1080/15420353.2024.2399714.
    15. I. Zangana, J. C. Otto, R. Mäusbacher, and L. Schrott, “Efficient geomorphological mapping based on geographic information systems and remote sensing data: An example from Jena, Germany,” J. Maps, vol. 19, no. 1, pp. 1–13, 2023, doi: 10.1080/17445647.2023.2172468.
    16. T. M. McGuire, C. J. Newell, X. Osorio, K. L. Walker, and A. J. Keat, “Allocating remedial costs at a superfund site using risk magnitude, geographic information systems, and Monte Carlo analysis,” Environ. Forensics, vol. 21, no. 2, pp. 223–235, 2020, doi: 10.1080/15275922.2020.1728435.
    17. M. H. Aliyu et al., “Enhancing physician scientists’ skills in geographic information systems: Insights from an interactive workshop,” Ann. GIS, vol. 31, no. 4, pp. 713–721, 2025, doi: 10.1080/19475683.2025.2548205.
    18. A. Hani Al-Tamimi, A. A. M. Alnasrawy, M. Halais Al- Hatmi, N. AL-Ansari, S. K. Al-Mamoori, and Z. A. J. Jiddy, “Urban uses change an analytical study using geographic information systems/Kufa city as a model,” Cogent Eng., vol. 9, no. 1, pp. 1–31, 2022, doi: 10.1080/23311916.2022.2143065.
    19. S. Rusadi, R. Mulyawan, U. Suwaryo, and N. Y. Yuningsih, “Bibliometric analysis of abrasion and erosion disaster mitigation: Trends, key themes, and potential for global policy development,” Cogent Soc. Sci., vol. 10, no. 1, pp. 1–15, 2024, doi: 10.1080/23311886.2024.2430451.
    20. C. Kriel and C. D. van der Merwe, “Teaching geographic information systems in south african geography classrooms, using problem-based learning,” South African Geogr. J., vol. 107, no. 4, pp. 586–602, 2025, doi: 10.1080/03736245.2025.2472665.
    21. D. Rush et al., “Fire risk reduction on the margins of an urbanizing world,” Disaster Prev. Manag., vol. 29, no. 5, pp. 747–760, Oct. 2020, doi: 10.1108/DPM-06-2020-0191.
    22. C. M. de Carvalho, L. Luiz Giatti, N. Fagerholm, A. M. Bedran-Martins, and M. Kytta, “Participatory geographic information systems (PGIS) to assess water, energy and food availability in a vulnerable community in Guarulhos (Brazil),” Int. J. Urban Sustain. Dev., vol. 13, no. 3, pp. 516–529, 2021, doi: 10.1080/19463138.2021.2019041.
    23. B. Mishra, S. Panthi, S. Poudel, and B. R. Ghimire, “Forest fire pattern and vulnerability mapping using deep learning in Nepal,” Fire Ecol., vol. 19, no. 3, pp. 1–15, 2023, doi: 10.1186/s42408-022-00162-3.
    24. H. M. Tholo et al., “Web-based spatial decision support system for optimum route to forest fires: A case of viphya plantations,” Trees, For. People, vol. 19, p. 100740, 2025, doi: https://doi.org/10.1016/j.tfp.2024.100740.
    25. A. Tanoumand, M. Mashayekhi, S. Mona, and A. Majdi, “Development of a method for optimal location of emergency water reservoirs for FFE suppression using AHP and GIS,” Front. Built Environ., vol. 11, pp. 1–21, 2025, doi: 10.3389/fbuil.2025.1638961.
    26. S. I. Oktora, I. Y. Wulansari, T. H. Siagian, B. C. Laksono, N. N. R. Sugiandewi, and N. Anindita, “Identifying the potential participation in natural disaster insurance: First attempt based on a national socio-economic survey in Indonesia,” Int. J. Disaster Resil. Built Environ., vol. 15, no. 2, pp. 177–192, Aug. 2022, doi: 10.1108/IJDRBE-04-2022-0034.
    27. G. Chen and C. Li, “Thoughts on developing an early warning model for hospital violence risk events using geographic information systems,” J. Multidiscip. Healthc., vol. 19, pp. 1–10, 2026, doi: 10.2147/jmdh.s569538.
    28. E. M. Geraghty, “Enhancing cancer care, research, and engagement through geographic context: The role of geographic information systems in defining and serving cancer center catchment areas,” Prev. Oncol. Epidemiol., vol. 2, no. 1, pp. 1–8, 2024, doi: 10.1080/28322134.2024.2379437.
    29. S. Di Grazia and G. M. Tina, “Optimal site selection for floating photovoltaic systems based on geographic information systems (GIS) and multi-criteria decision analysis (MCDA): A case study,” Int. J. Sustain. Energy, vol. 43, no. 1, pp. 1–23, 2024, doi: 10.1080/14786451.2023.2167999.
    30. N. Ramírez Aranda, J. De Waegemaeker, V. Venhorst, W. Leendertse, E. Kerselaers, and N. Van de Weghe, “Point, polygon, or marker? In search of the best geographic entity for mapping cultural ecosystem services using the online public participation geographic information systems tool, ‘My Green Place,’” Cartogr. Geogr. Inf. Sci., vol. 48, no. 6, pp. 491–511, 2021, doi: 10.1080/15230406.2021.1949392.
    31. J. C. Kostelnick, J. B. Thayn, and K. Sinha, “Mapping and spatial analysis to expand rural broadband access,” Pap. Appl. Geogr., vol. 10, no. 2, pp. 154–175, 2024, doi: 10.1080/23754931.2024.2332238.
    32. X. Yan, Z. Ye, and S. C. Hsu, “Coupling CFD fire simulation with agent-based evacuation modelling for safety performance assessment in high-density residential buildings,” J. Build. Perform. Simul., vol. 14, no. 5, pp. 1–28, 2026, doi: 10.1080/19401493.2026.2665703.
    33. Y. X. Wu, Y. F. Zhao, Q. Zhang, J. W. Zhou, and H. G. Xing, “Risk assessment and response for personnel loss caused by debris flow disasters considering non-engineering disaster mitigation measures,” Geomatics, Nat. Hazards Risk, vol. 15, no. 1, pp. 1–20, 2024, doi: 10.1080/19475705.2024.2429179.
    34. N. R. Matandirotya, S. B. Opiyo, D. P. Cilliers, R. P. Burger, and S. J. Piketh, “Evaluation of aerial thermography as a tool for in-situ determination of thermal insulation status of residential dwellings in South Africa,” Adv. Build. Energy Res., vol. 19, no. 6, pp. 746–772, 2025, doi: 10.1080/17512549.2025.2540901.
    35. T. Akinboyewa, Z. Li, H. Ning, and M. N. Lessani, “GIS copilot: Towards an autonomous GIS agent for spatial analysis,” Int. J. Digit. Earth, vol. 18, no. 1, pp. 1–23, 2025, doi: 10.1080/17538947.2025.2497489.
    36. B. J. Fagbohun, A. A. Omitogun, F. J. Ayoola, and O. A. Bamisaiye, “Spatial analysis of gold occurrences in the Zuru Schist Belt, northwest Nigeria,” Geol. Ecol. Landscapes, vol. 9, no. 3, pp. 1015–1033, 2025, doi: 10.1080/24749508.2024.2373484.
    37. T. Clark, J. O. Baker, and C. D. Bader, “Mostly haunted: A socio-spatial analysis of ghost tourism in England and Wales,” Tour. Recreat. Res., vol. 0, no. 0, pp. 1–14, 2026, doi: 10.1080/02508281.2025.2611765.
    38. X. Li, C. Fei, and W. Fei, “The influence of Knightian uncertainty on sustainable financial welfare consequences,” Syst. Sci. Control Eng., vol. 13, no. 1, pp. 1–19, 2025, doi: 10.1080/21642583.2025.2467072.
    39. T. Dartanto, “Natural disasters, mitigation and household welfare in Indonesia: Evidence from a large-scale longitudinal survey,” Cogent Econ. Financ., vol. 10, no. 1, pp. 1–31, 2022, doi: 10.1080/23322039.2022.2037250.
    40. S. Uekusa, M. Wynyard, and S. Matthewman, “Reinvestigating social vulnerability from the perspective of critical disaster studies (CDS): Directions, opportunities and challenges in Aotearoa disaster research,” Kotuitui, vol. 20, no. 2, pp. 159–176, 2025, doi: 10.1080/1177083X.2024.2305639.
    41. M. A. Samad, K. Arifin, and A. Abas, “A systematic literature review on the challenges of Southeast Asian countries in natural disaster management,” Cogent Soc. Sci., vol. 11, no. 1, pp. 1–21, 2025, doi: 10.1080/23311886.2024.2435590.
    42. M. Muzani, I. B. Mataburu, and T. Tafiati, “Vulnerability and tsunami disaster on the west coast Banten province, Indonesia,” All Earth, vol. 36, no. 1, pp. 1–12, 2024, doi: 10.1080/27669645.2024.2323355.