WIT Press


Applying An Entropic Analysis To Locate Rapid Transit Lines In Sprawled Cities



Price

Free (open access)

Paper DOI

10.2495/SDP-V13-N4-626-637

Volume

Volume 13 (2018), Issue 4

Pages

11

Page Range

626 - 637

Author(s)

FRANCISCO A. ORTEGA, RAMÓN PIEDRA-DE-LA-CUADRA & SOLY VENTURA

Abstract

Urban sprawl is a phenomenon that leads to an extensive use of motorized transport modes with negative environmental impacts such as congestion, time wasted in traffic jams, air and noise pollution and additional costs incurred by using non-renewable energy. Increasing the existing infrastructures is a decision, which often generates the installation of new urban settlements, whose degree of isolation is mitigated with a new increase in the demand for transport. This vicious circle can be broken by reducing the need of transport imposed by the urban model, which is only possible by bringing citizens closer to those services they demand. In the model of sprawled city, housing predominates as land use in the residential areas, where other complementary uses (such as commercial, cultural, institutional and industrial ones) are excluded in the urban development. When the urban districts don´t present enough complexity, an increase in traffic density between different zones into the city arises. Such forced mobility could be reduced if the functional diversity of the districts were greater, or if there was an urban rapid transit system connecting the areas that generate the greatest imbalances. To measure the complexity of the urban districts system, the Information Theory developed in the 1960s proposes the use of urban entropy. The paper addresses the problem of locating a rapid transit line (metro, tram, BRT) with the objective of maximize the functional diversity of the districts traversed by the alignment. In order to illustrate the proposed model a computational experience is carried out by using data from the metropolitan area of Seville (Spain).

Keywords

entropic analysis, rapid transit line, urban diversity