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. © 2003 Elsevier Science Ltd. All rights reserved.
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Título según WOS: | The local spatial autocorrelation and the kernel method for identifying black zones - A comparative approach |
Título según SCOPUS: | The local spatial autocorrelation and the kernel method for identifying black zones: A comparative approach |
Título de la Revista: | ACCIDENT ANALYSIS AND PREVENTION |
Volumen: | 35 |
Número: | 6 |
Editorial: | PERGAMON-ELSEVIER SCIENCE LTD |
Fecha de publicación: | 2003 |
Página de inicio: | 991 |
Página final: | 1004 |
Idioma: | English |
URL: | http://linkinghub.elsevier.com/retrieve/pii/S0001457502001070 |
DOI: |
10.1016/S0001-4575(02)00107-0 |
Notas: | ISI, SCOPUS |