Geomatic Approach to Modelling Urban-Fire-Risk-Susceptibility in Akure, Ondo State, Nigeria

Abstract

Urban fire occurs primarily in cities or towns with a high potential of destroying homes, schools, commercial buildings, and vehicles. Cases of fire disasters in Nigerian cities have been experienced in the last decade with increasing frequency and severity with properties worth millions of naira destroyed in fire accidents nationwide. This study attempts to integrate a global positioning system (GPS) and geographical information system (GIS) to model areas vulnerable to fire hazards within the study area. The procedural methodology adopted consisted of spatial data acquisition, pre-processing (geo-reference), post-processing, and analysis. Here High-Resolution Google Earth image was used for dereferencing and digitization within the ArcGIS 10.3 version, Google Earth Pro, and AutoCAD 2007 software. Three- features- analysis (Fire Incidences Scenes, Fire Stations and Road Network) in terms of coverage and service-area-delivery was performed.  Findings of the study revealed that the year 2016 had the highest percentage (29%) of fire causes and occurrences; from 2016 to 2019, with Bush fire consisting of 25 (19.5%)  Gas explosion 2 (1.56%), undergrowth wood-burn 13 (10.16%), Electric fault 21 (16.41%), Car burning 7 (5.47%) and unknown engulfed 60 (46.9%); while the year 2019 had the lowest, with 20.09%. The results reveal Monthly fire-occurrences from January 2016 to September 2019 and fire-occurrence-response-rate from Airport Fire station, Akure metropolitan fire station, and UBA-FUT-Akure fire stations. Hence, this study presents a knowledge-based approach to modeling urban fire- Susceptibility, with the view to managing such incidences by the State, ensuring an increase in the ratio of fire professionals per population of 1:1000 to march global tactics.

Country : Nigeria

1 Tukka Apollos Audu

  1. Lecturer, Department of Surveying and Geoinformatics, Federal University of Technology, Akure, Nigeria

IRJIET, Volume 6, Issue 1, January 2022 pp. 102-109

doi.org/10.47001/IRJIET/2022.601018

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