The local spatial autocorrelation and the kernel method for identifying black zones. A comparative approach.
This article aims to determine the location and the length of road sections characterized by a concentration of accidents (black zones). Two methods are compared: one based on a local decomposition of a global autocorrelation index, the other on kernel estimation. After explanation, both methods are applied and compared in terms of operational results, respective advantages and shortcomings, as well as underlying conceptual elements. The operationality of both methods is illustrated by an application to one Belgian road.
Flahaut
Benoît
B
Department of Geography, Université Catholique de Louvain, Place Louis Pasteur 3, Louvain-la-Neuve 1348, Belgium. flahaut@geog.ucl.ac.be
Mouchart
Michel
M
San Martin
Ernesto
E
Thomas
Isabelle
I
D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D001530:Belgium; D016000:Cluster Analysis; D006801:Humans; D015233:Models, Statistical; D018709:Statistics, Nonparametric