Network based kernel density estimation for cycling facilities optimal location applied to Ljubljana

Authors:
Nicolas Lachance-Bernard;Timothée Produit;Biba Tominc;Matej Nikšič;Barbara Goličnik Marušić
Affiliations:
Laboratory of Geographic Information Systems, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland;Laboratory of Geographic Information Systems, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland;Urban Planning Institute of the Republic of Slovenia, Ljubljana, Slovenia;Urban Planning Institute of the Republic of Slovenia, Ljubljana, Slovenia;Urban Planning Institute of the Republic of Slovenia, Ljubljana, Slovenia
Venue:
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part II
Year:
2011

Citing 3
Cited 0

Estimating probability surfaces for geographical point data: an adaptive kernel algorithm

Computers & Geosciences
A kernel density estimation method for networks, its computational method and a GIS-based tool

International Journal of Geographical Information Science
A network based kernel density estimator applied to barcelona economic activities

ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a methodology that use volunteered geographic information (VGI), cyclist GPS tracking and Open Street Map network, with network based kernel density estimation. It investigates optimal location for cycle paths and lanes development. Recently completed research provides cycling data for Ljubljana, Slovenia. It was conducted over two years and was commissioned by the Municipality of Ljubljana. The methodology combines and adapts these VGI data and is mainly based on open source software. It handles large datasets with multiscale perspectives. This methodology should help planners to find and to develop suitable facility locations corresponding to current user behaviors.