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The spatio-temporal analysis of residential fires could allow decision makersto plan effective resource allocations in fire management according to fireclustering levels in space and time. In this study, we provide guidelines forthe use of various methods in detecting the differences in clustering patternsof fire and non-fire (i.e., background residential) locations and how thesepatterns change over time. As a preliminary analysis step, various exploratorydata analysis methods, such as, intensity plots (i.e., kernel densityestimates) are used. Moreover, the use of Diggle's D-function (a second orderanalysis technique) is proposed for detecting the clustering of residentialfire locations (if any) and whether there is additional clustering (orregularity) in the locations of the fires compared to background residentialpattern. A test for trend over time (in years, months, and weeks) of the firelocation patterns are provided with a space-time interaction analysis byspatio-temporal K-function. Residential fire data from \c{C}ankaya Municipalityof Ankara, Turkey is used as an illustrative example. The presented methodologyis also applicable to residential fire data from similar urban settings.

Exploratory and Inferential Methods for Spatio-Temporal Analysis of Residential Fire Clustering in Urban Areas