title: The local spatial autocorrelation and the kernel method for identifying black zones. A comparative approach.
abstract: 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.
authors.affiliation: Department of Geography, Université Catholique de Louvain, Place Louis Pasteur 3, Louvain-la-Neuve 1348, Belgium. flahaut@geog.ucl.ac.be
authors.forename: Benoît
authors.initials: B
authors.lastname: Flahaut
authors.forename: Michel
authors.initials: M
authors.lastname: Mouchart
authors.forename: Ernesto
authors.initials: E
authors.lastname: San Martin
authors.forename: Isabelle
authors.initials: I
authors.lastname: Thomas
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D001530:Belgium; D016000:Cluster Analysis; D006801:Humans; D015233:Models, Statistical; D018709:Statistics, Nonparametric