Monitoring land supply with geographic information systems: theory, practice and parcel-based approaches edited by Anne Vernez Moudon and Michael Hubner, John Wiley, New York, 2000. No. of pages: 335. Price: £58·50. ISBN 0 471 37163 7.

2001 ◽  
Vol 26 (4) ◽  
pp. 458-459
Author(s):  
D. Unwin
Author(s):  
Steven I-Jy Chien ◽  
Feng-Ming Tsai ◽  
Edwin Hou

A genetic algorithm (GA) was developed to optimize a bus transit system serving an irregularly shaped area with a grid street network. The developed objective total cost function was minimized subject to realistic demand distribution and street pattern. The service area in New York City was selected as an example to demonstrate the application of the developed model. With the application of geographic information systems, the street network within the service area was obtained and applied, while the passenger demand information was approximated based on the New York City census report of 1990. The optimal number of bus routes and their locations were found by applying the proposed GA, while the optimal headways of the routes were analytically derived. The method developed here can be applied to dynamic routing buses under various incident situations.


2007 ◽  
Vol 01 (04) ◽  
pp. 347-360
Author(s):  
SISSY NIKOLAOU

This paper presents integrated Geographic Information Systems (GIS) developed to perform seismic hazard and risk assessment. The systems can perform complex interactive computations which would be difficult and time-consuming to carry out manually, such as: (i) deterministic and probabilistic earthquake hazard analysis; (ii) evaluation of different ground motion and seismic source models; (iii) assessment of the effect of local geology; (iv) generation of design-compatible time histories; and (v) damage assessment of spatially distributed structural systems. An application for the New York City metropolitan area demonstrates that despite the scarcity of recorded data, incomplete knowledge of seismic wave propagation characteristics, and sometimes insufficient geologic data, it is possible to arrive at a rational estimate of the seismic risk potential in a probabilistic manner, combining available information and uncertainties in the GIS environment.


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