Maximum Entropy Based Urban Fire Risk Distribution Modeling Under Climate Influences in North, West, and South of Jakarta City

Abstract

Fire incidents in urban setting were influenced by many factors ranging from population, building density to climatic variables. Currently, fire incident can be estimated using various variables and modeling methods including maximum entropy approach. Then the aim of this study is to model the probable spatial distribution of areas in Jakarta City mainly in North, West, and South districts that are prone to the fire risks. The model was developed using maximum entropy approach using climatic variables as predictors obtained from WordClim database. The model then was confirmed using area under the curve (AUC) values. The climatic models show that North and West parts of Jakarta receiving lower rainfall than South parts. Based on modeled probability distributions of fire risks, North and West parts were having highest probability distributions of fire risks with value of 50%. The AUC validates the probability distributions of fire risks model with AUC value of 0.64 ± 0.07. The results obtained from this study then can be used planning fire prevention.