Emergency Response Demand and Supply: A GIS-Based Network Analysis for Fire Station’s Service Coverage Delineation in Kano Metropolis, Nigeria
Abstract
Inadequate fire emergency response infrastructure and a lack of defined service coverage remain key barriers to timely fire disaster response. This study is applied research which employed geospatial techniques and aimed at examining fire disaster emergency response demand and supply relationships with the view to delineating service coverage and locating more facilities for optimum coverage in Kano metropolis. Locations of the existing fire stations and fire incidents (2009-2019) were gathered through GPS surveying. Network data set were generated. Nearest Neighbor and Network Analysis (origin-destination, service coverage and location-allocation) were conducted to determine emergency response demand and supply relationships, service coverage area delineation and identifying best site for allocating new facilities within the metropolis respectively. It was found that no clearly defined service coverage exist as emergency response supply takes more than 4-8 times the NFPA travel standard, and with a great deal of overlapping response patterns. New service coverage areas were proposed and best sites for 8 firefighting facilities identified for optimum coverage. It is concluded that emergency fire disaster response demand and supply relationships within Kano metropolis is imbalanced, with extensive recurrent demand especially within the core area served by overstretched and inefficient response supply. This, therefore, implies continuous exposure of lives and properties to the menace of fire disaster in Kano metropolis.
References
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Fire Department of Ministry of Public Security (FDMPS) (2016). China fire yearbook (2016). in ChineseKunming, China: Yunnan People's Publishing House.
Ganeshkumar, B. & Ramesh, D. (2010). Emergency Response Management and Information System (ERMIS) – A GIS based software to resolve the emergency recovery challenges in Madurai city, Tamil Nadu. International Journal of Geomatics and Geosciences,1( 1).
Han, B., Hu, M., Zheng, J. and Tang, T. (2021). Site selection of fire stations in large cities based on actual spatiotemporal demands: A Case study of Nanjing City. ISPRS Int. J. Geo-Inf. 2021, 10, 542. https:// doi.org/10.3390/ijgi10080542.
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Kanoun, I., Chabchoub, H., & Aouni, B. (2010). Goal programming model for fire and emergency service facilities site selection. INFOR: Information Systems and Operational Research, 48(3), 143–153.
Kazemi, M., Kunt, M.M., Aghayan, I., Larijani, R.J., (2013). Optimization model for fire station location based on GIS and Python: a case study in North Cyprus. Applied Mechanics and Materials, Trans Tech Publ. 330, 1059–1064.
Kiran, K. C & Corcoran, J., (2017). Modelling residential fire incident response times: a spatial analytic approach. Applied Geography, 84, 64–74. https://doi.org/10.1016/j.apgeog. 2017.03.004.
Kiran, K. C., Corcoran, J., & Chhetri, P. (2018). Spatial optimisation of fire service coverage: A Case Study of Brisbane, Australia. Geographical Research, 56(3), 270-284. https://doi.org/10.1111/1745-5871.12288.
Li, X., Zhao, Z., Zhu, X. and Wyatt, T., (2011). Covering models and optimization techniques for emergency response facility location and planning: a review. Mathematical Methods of Operations Research, 74(3), 281–310.
Liu, N., Huang, B., & Chandramouli, M. (2006). Optimal sitting of fire stations using GIS and ANT algorithm. Journal of Computing in Civil Engineering, 20(5), 361–369.
Maigari A. I, (2014). Evolutionary trend, spatial distribution of, and issues associated with markets in Kano Metropolis: Research on Humanities and Social Sciences. 4(28) 2224-5766.
Mao, K., Chen, Y., Wu, G., Huang, J., Yang, W. and Xia, Z. (2020). Measuring spatial accessibility of urban fire services using historical fire incidents in Nanjing, China. ISPRS Int. J. Geo Inf. 2020, 9, 585. https://doi.org/10.3390/ijgi9100585.
Murray, A. T. (2010). Advances in location modeling: GIS linkages and contributions. Journal of Geographical Systems, 12(3), 335–354. https://doi.org/10.1007/s10109-009-0105-9.
Murray, A. T. (2013). Optimising the spatial location of urban fire stations. Fire Safety Journal, 62, 64–71. https://doi.org/10.1016/j.firesaf.2013.03.002.
Murray, A. T. (2015). Fire station siting. In H. A. Eiselt, & V. Marianov (Eds.). Applications of location analysis (pp. 293–306). Springer International Publishing.
Murray, A. T., & Tong, D. (2009). GIS and spatial analysis in the media. Applied Geography, 29(2), 250–259.
National Emergency Management Agency (2006). Industrial and Commercial Buildings Fire in Nigeria, NEMA, 2006.
National Fire Protection Association, NFPA (2010). Standard for the Organization and Deployment of Fire Suppression Operations, Emergency Medical Operations and Special Operations to the Public by Volunteer Fire Departments.
NFPA, (2003). Fire Loss in the United States, 2003 .
Nyimbili P. H. & Erden T. (2020). GIS-Based fuzzy multi-criteria approach for optimal site selection of fire stations in Istanbul, Turkey. Socio-Economic Planning Sciences 71 (2020) 100860, 1-13. https://doi.org/10.1016/j.seps.2020.100860.
Ogundele, J.A., Arohunsoro, S.J., Jegede, A.O., & Oni, B.B. (2013). Evaluating the operations of emergencies and disaster management agencies in Ekiti State, Nigeria. Journal of Natural Sciences Research, 3(15), 132-138.
Oladokun, V. O. & Ishola, F. A. (2010). A Risk analysis model for fire disasters in commercial complexes in Nigeria. Pacific Journal of Science and Technology. 11(2), 376-386.
Oladokun, V. O., & Emmanuel, C. G. (2014). Urban market fire disasters management in Nigeria: A Damage minimization based fuzzy logic model approach. International Journal of Computer Applications. 106(17), 975–8887.
Oladokun, V.O., Kolawole, A. & Emmanuel, C. G. (2012). Risk Analysis Models of Fire Accidents in Nigeria Commercial Complexes: A Fuzzy Logic Approach," in Proceedings of NIIE 2012 Conference, Benin.
Oppong, J.R., Boakye, K., Edziyie, R., Owusu, A.Y., Tiwari, C., (2017). Emergency fire response in ghana: the case of fire stations in Kumasi. 36, 253–261. https://doi.org/10.1080/19376812.2016.1231616.
Shahparvari S., Fadaki M., Chhetri P. (2020). Spatial accessibility of fire stations for enhancing operational response in Melbourne. Fire Safety Journal, 117, 103149. https://doi.org/10.1016/j.firesaf.2020.103149.
Wang, W., Xu, Z., Sun, D. & Lan, T. (2021). Spatial optimization of mega-city fire stations based on multi-source geospatial data: A Case study in Beijing. ISPRS Int. J. Geo Inf. 2021, 10, 282. https://doi.org/10.3390/ijgi10050282.
Wuschke, K., Clare, J. & Garis, L. (2013). Temporal and geographic clustering of residential structure fires: A Theoretical platform for targeted fire prevention. Fire Safety Journal 62, 3–12. http://dx.doi.org/10.1016/j.firesaf.2013.07.003.
Xin, J., & Huang C. (2013). Fire Risk Analysis of Residential Buildings Based on Scenario Clusters and its Application in Fire Risk Management. Fire Safety Journal 62, 72–78. http://dx.doi.org/10.1016/j.firesaf.2013.09.022.
Yao J., Zhang X., & Murray A. T., (2018). Location optimization of urban fire stations: access and service coverage. Journal of Computers, Environment and Urban Systems, 73, 184-190. https://doi.org/10.1016/j.compenvurbsys.2018.10.006.
Yu, W., Chen, Y., Chen, Z., Xia, Z., & Zhou, Q. (2020). Service area delimitation of fire stations with fire risk analysis: Implementation and case study. Int. J. Environ. Res. Public Health. 17(6). https://doi.org/10.3390/ijerph17062030.
Yu, w., zhang, y., & chen, z. (2019). automated generalization of facility points-of-interest with service area delimitation. IEEE access, 7, 63921-63935. https://doi.org/10.1109/access.2019.2916977.
Yunus, S. (2019). Response delay model: Bridging the gap in urban fire disaster response system. International Journal of Humanities and Social Sciences, 13(12), 1463-1468.
Yunus, S., & Falola, J. A. (2022). Analysis of Spatio-Temporal Pattern, Causes and Consequences of Fire Disaster in Kano Metropolis, Nigeria. Nigerian Journal of Environmental Sciences and Technology (NIJEST). 6(2), 478-492.
Zhang, X., Yao, J., & Sila-Nowicka, K. (2018). Exploring spatiotemporal dynamics of urban fires: A case of Nanjing, China. ISPRS International Journal of Geo-Information, 7(1), 7. https://doi.org/10.3390/ijgi7010007.
Zhibang, X., Liang, Z., Ting, L., Zhonghui, W., Li, S. & Rongwei, W. (2018). Spatial optimization of mega-city fire station distribution based on Point of Interest data: A case study within the 5th Ring Road in Beijing. Geogr. Sci. Prog. 37, 535–546.
Akta¸s, E., Özaydın, Ö., Bozkaya, B., Ülengin, F., Önsel, ¸S., (2013). Optimizing fire station locations for the istanbul metropolitan municipality. Interfaces, 43, 240–255.
Algharib, S.M. (2011). Distance and coverage: An assessment of location-allocation models for fifire stations in Kuwait City, Kuwait. Ph.D. thesis. Kent State University.
Ayila, A. E., Oluseyi, F. O., and Anas, B. Y. (2014). Statistical analysis of urban growth in Kano Metropolis, Nigeria. International journal of Environmental Monitoring an analysis, 2(1), 50-56.
Ayuba, H. K., Aguocha, O., and Medugu, N. I. (2016). Fire vulnerability assessment of the Federal Capital City, International Journal of Innovative Science, Engineering and Technology, 3(5), 39–46.
Bahri, S., (2016). 0-1 integer linear programming model for location selection of fifire station: A case study in Indonesia. AIP Conference Proceedings, AIP Publishing. p. 030004. https://doi.org/10.1063/1.4945062.
Barau, A. S. Maconacchie, R., Ludinc, A. N.M. and Abdulhamid, A. (2015). Urban morphology dynamics and environmental change in Kano, Nigeria. Land Use Policy, 42, 307-317. https://doi.org/10.1016/j.landusepol.2014.08.007.
Bolouri, S., Vafaeinejad, A., Alesheikh, A., Aghamohammadi, H., (2018). The ordered capacitated multi-objective location allocation problem for fire stations using spatial optimization. ISPRS International Journal of Geo-Information, 7, 44. https://doi.org/10.3390/ijgi7020044.
Brushlinsky, N. N., Ahrens, M., Sokolov, S. V., & Wagner, P. (2017). World fire statistics.
Çatay, B. (2011). Siting new fire stations in Istanbul: A risk-based optimization approach. OR Insight, 24(2), 77–89.
Center of Fire Statistics Report, (2017). http://www.ctif.org/sites/default/files/ctif_report22_world_fire_statistics_2017.pdf, Accessed date: 30 September 2021.
Ceyhan, E., Ertuǧay, K. and Düzgün, Ş. (2013). Exploratory and inferential methods for spatio-temporal analysis of residential fire clustering in urban areas. Fire Safety Journal, 58: 226–239. https://doi.org/10.1016/j.firesaf.2013.01.024.
Chen, C. & Yang, Q. (2018). Hotspot analysis of the spatial and temporal distribution of fires. Proceedings of the 4th International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM 2018), pages 15-21. DOI: 10.5220/0006638600150021.
Chen, H., Cheng, T. and Ye, X. (2018). Designing efficient and balanced police patrol districts on an urban street network. Int. J. Geogr. Inf. Sci. 33, 269–290. https://doi.org/10.1080/13658816.2018.1525493.
Chen, Z.F., Li, J.W., Lu, F.X. and Li, Q. (2018). Optimizing location of fire stations and it’ s enlightenments for Xiongan New Area. China Saf. Prod. Sci. Technol. 14, 12–17.
Chevalier, P., Thomas, I., Geraets, D., Goetghebeur, E., Janssens, O., Peeters, D., & Plastria, F. (2012). Locating fire stations: An integrated approach for Belgium. Socio- Economic Planning Sciences, 46(2), 173–182. https://doi.org/10.1016/j.seps.2012.02.003.
Chhetri, P., Kam, B., Lau, K., Corbitt, B., Cheong, F., (2017). Improving service responsiveness and delivery efficiency of retail networks. International Journal of Retail & Distribution Management, 45 (3), 271–291. doi:10.1108/IJRDM-07-2016-0117.
Church, R., & Li, W. (2016). Estimating spatial efficiency using cyber search, GIS, and spatial optimization: A case study of fire service deployment in Los Angeles County. International Journal of Geographical Information Science, 30(3), 535–553. https://doi.org/10.1080/13658816.2015.1083572.
Dogondaji A. Z, Ojonugwa E., Ibrahim A. A., and Mustafa A. (2017). P-Center problem of fire stations in Sokoto Metropolis. Asian Journal of Mathematics and Computer Research, 18(3): 143-151, 2017.
Dong X., Li Y., Pan Y., Huang Y., Cheng X., (2018). Study on urban fire station planning based on fire risk assessment and GIS Technology. 2017 8th International Conference on Fire Science and Fire Protection Engineering (on the Development of Performance-based Fire Code). Procedia Engineering, 211, 124–130.
Ejikeme, J. O., Igbokwe, JI. I. and Johnson, N. G. (2012). Application of GIS for effective management of fire disaster in Onitsha”, Nigerian Institute of Surveyors Technical Proceedings of General Meeting and Conference on Surveying Disaster Management and Global Warming held at Ilorin, Kwara State, June 25 - 29, 2012: 48 – 55.
Erkut, E., Fenske, R., Kabanuk, S., Gardiner, Q. and Davis, J. (2001). Improving the Emergency Service Delivery in St. Albert. INFOR. 39, 416 – 433.
ESRI (2007). GIS for Fire Station Locations and Response Protocol An ESRI® White Paper January 2007.
Fire Department of Ministry of Public Security (FDMPS) (2016). China fire yearbook (2016). in ChineseKunming, China: Yunnan People's Publishing House.
Ganeshkumar, B. & Ramesh, D. (2010). Emergency Response Management and Information System (ERMIS) – A GIS based software to resolve the emergency recovery challenges in Madurai city, Tamil Nadu. International Journal of Geomatics and Geosciences,1( 1).
Han, B., Hu, M., Zheng, J. and Tang, T. (2021). Site selection of fire stations in large cities based on actual spatiotemporal demands: A Case study of Nanjing City. ISPRS Int. J. Geo-Inf. 2021, 10, 542. https:// doi.org/10.3390/ijgi10080542.
Isa, U. F., Liman, M. A., Mohammed, M. U., Mathew, O. S., and Yayo, Y. R. (2016). Spatial Analysis of Fire Service Station in Kano Metropolis, Nigeria. IOSR Journal of Humanities and Social Science, 21(9), 42–52. https://doi.org/10.9790/0837-2109014252.
Kanoun, I., Chabchoub, H., & Aouni, B. (2010). Goal programming model for fire and emergency service facilities site selection. INFOR: Information Systems and Operational Research, 48(3), 143–153.
Kazemi, M., Kunt, M.M., Aghayan, I., Larijani, R.J., (2013). Optimization model for fire station location based on GIS and Python: a case study in North Cyprus. Applied Mechanics and Materials, Trans Tech Publ. 330, 1059–1064.
Kiran, K. C & Corcoran, J., (2017). Modelling residential fire incident response times: a spatial analytic approach. Applied Geography, 84, 64–74. https://doi.org/10.1016/j.apgeog. 2017.03.004.
Kiran, K. C., Corcoran, J., & Chhetri, P. (2018). Spatial optimisation of fire service coverage: A Case Study of Brisbane, Australia. Geographical Research, 56(3), 270-284. https://doi.org/10.1111/1745-5871.12288.
Li, X., Zhao, Z., Zhu, X. and Wyatt, T., (2011). Covering models and optimization techniques for emergency response facility location and planning: a review. Mathematical Methods of Operations Research, 74(3), 281–310.
Liu, N., Huang, B., & Chandramouli, M. (2006). Optimal sitting of fire stations using GIS and ANT algorithm. Journal of Computing in Civil Engineering, 20(5), 361–369.
Maigari A. I, (2014). Evolutionary trend, spatial distribution of, and issues associated with markets in Kano Metropolis: Research on Humanities and Social Sciences. 4(28) 2224-5766.
Mao, K., Chen, Y., Wu, G., Huang, J., Yang, W. and Xia, Z. (2020). Measuring spatial accessibility of urban fire services using historical fire incidents in Nanjing, China. ISPRS Int. J. Geo Inf. 2020, 9, 585. https://doi.org/10.3390/ijgi9100585.
Murray, A. T. (2010). Advances in location modeling: GIS linkages and contributions. Journal of Geographical Systems, 12(3), 335–354. https://doi.org/10.1007/s10109-009-0105-9.
Murray, A. T. (2013). Optimising the spatial location of urban fire stations. Fire Safety Journal, 62, 64–71. https://doi.org/10.1016/j.firesaf.2013.03.002.
Murray, A. T. (2015). Fire station siting. In H. A. Eiselt, & V. Marianov (Eds.). Applications of location analysis (pp. 293–306). Springer International Publishing.
Murray, A. T., & Tong, D. (2009). GIS and spatial analysis in the media. Applied Geography, 29(2), 250–259.
National Emergency Management Agency (2006). Industrial and Commercial Buildings Fire in Nigeria, NEMA, 2006.
National Fire Protection Association, NFPA (2010). Standard for the Organization and Deployment of Fire Suppression Operations, Emergency Medical Operations and Special Operations to the Public by Volunteer Fire Departments.
NFPA, (2003). Fire Loss in the United States, 2003 .
Nyimbili P. H. & Erden T. (2020). GIS-Based fuzzy multi-criteria approach for optimal site selection of fire stations in Istanbul, Turkey. Socio-Economic Planning Sciences 71 (2020) 100860, 1-13. https://doi.org/10.1016/j.seps.2020.100860.
Ogundele, J.A., Arohunsoro, S.J., Jegede, A.O., & Oni, B.B. (2013). Evaluating the operations of emergencies and disaster management agencies in Ekiti State, Nigeria. Journal of Natural Sciences Research, 3(15), 132-138.
Oladokun, V. O. & Ishola, F. A. (2010). A Risk analysis model for fire disasters in commercial complexes in Nigeria. Pacific Journal of Science and Technology. 11(2), 376-386.
Oladokun, V. O., & Emmanuel, C. G. (2014). Urban market fire disasters management in Nigeria: A Damage minimization based fuzzy logic model approach. International Journal of Computer Applications. 106(17), 975–8887.
Oladokun, V.O., Kolawole, A. & Emmanuel, C. G. (2012). Risk Analysis Models of Fire Accidents in Nigeria Commercial Complexes: A Fuzzy Logic Approach," in Proceedings of NIIE 2012 Conference, Benin.
Oppong, J.R., Boakye, K., Edziyie, R., Owusu, A.Y., Tiwari, C., (2017). Emergency fire response in ghana: the case of fire stations in Kumasi. 36, 253–261. https://doi.org/10.1080/19376812.2016.1231616.
Shahparvari S., Fadaki M., Chhetri P. (2020). Spatial accessibility of fire stations for enhancing operational response in Melbourne. Fire Safety Journal, 117, 103149. https://doi.org/10.1016/j.firesaf.2020.103149.
Wang, W., Xu, Z., Sun, D. & Lan, T. (2021). Spatial optimization of mega-city fire stations based on multi-source geospatial data: A Case study in Beijing. ISPRS Int. J. Geo Inf. 2021, 10, 282. https://doi.org/10.3390/ijgi10050282.
Wuschke, K., Clare, J. & Garis, L. (2013). Temporal and geographic clustering of residential structure fires: A Theoretical platform for targeted fire prevention. Fire Safety Journal 62, 3–12. http://dx.doi.org/10.1016/j.firesaf.2013.07.003.
Xin, J., & Huang C. (2013). Fire Risk Analysis of Residential Buildings Based on Scenario Clusters and its Application in Fire Risk Management. Fire Safety Journal 62, 72–78. http://dx.doi.org/10.1016/j.firesaf.2013.09.022.
Yao J., Zhang X., & Murray A. T., (2018). Location optimization of urban fire stations: access and service coverage. Journal of Computers, Environment and Urban Systems, 73, 184-190. https://doi.org/10.1016/j.compenvurbsys.2018.10.006.
Yu, W., Chen, Y., Chen, Z., Xia, Z., & Zhou, Q. (2020). Service area delimitation of fire stations with fire risk analysis: Implementation and case study. Int. J. Environ. Res. Public Health. 17(6). https://doi.org/10.3390/ijerph17062030.
Yu, w., zhang, y., & chen, z. (2019). automated generalization of facility points-of-interest with service area delimitation. IEEE access, 7, 63921-63935. https://doi.org/10.1109/access.2019.2916977.
Yunus, S. (2019). Response delay model: Bridging the gap in urban fire disaster response system. International Journal of Humanities and Social Sciences, 13(12), 1463-1468.
Yunus, S., & Falola, J. A. (2022). Analysis of Spatio-Temporal Pattern, Causes and Consequences of Fire Disaster in Kano Metropolis, Nigeria. Nigerian Journal of Environmental Sciences and Technology (NIJEST). 6(2), 478-492.
Zhang, X., Yao, J., & Sila-Nowicka, K. (2018). Exploring spatiotemporal dynamics of urban fires: A case of Nanjing, China. ISPRS International Journal of Geo-Information, 7(1), 7. https://doi.org/10.3390/ijgi7010007.
Zhibang, X., Liang, Z., Ting, L., Zhonghui, W., Li, S. & Rongwei, W. (2018). Spatial optimization of mega-city fire station distribution based on Point of Interest data: A case study within the 5th Ring Road in Beijing. Geogr. Sci. Prog. 37, 535–546.
Published
2023-04-18
How to Cite
YUNUS, Sulaiman; FALOLA, Julius Afolabi; JARO, Ibrahim Musa.
Emergency Response Demand and Supply: A GIS-Based Network Analysis for Fire Station’s Service Coverage Delineation in Kano Metropolis, Nigeria.
Geosfera Indonesia, [S.l.], v. 8, n. 1, p. 61-82, apr. 2023.
ISSN 2614-8528.
Available at: <https://jurnal.unej.ac.id/index.php/GEOSI/article/view/36694>. Date accessed: 30 dec. 2024.
doi: https://doi.org/10.19184/geosi.v8i1.36694.
Section
Original Research Articles
