Mapping Wind Energy Potential in New York City Using Geographic Information System Platform and Semi-Analytical Methods

2017 ◽  
Author(s):  
Samaneh Gholitabar ◽  
Fletcher H. Griffis
Keyword(s):  
New York ◽  
Information System ◽  
New York City ◽  
Geographic Information System ◽  
Wind Energy ◽  
York City ◽  
Analytical Methods ◽  
Geographic Information ◽  
Energy Potential ◽  
Wind Energy Potential

Using geographic information system analyses to monitor large-scale distribution of nicotine replacement therapy in New York City

2010 ◽  
Vol 50 (5-6) ◽  
pp. 288-296 ◽  
Author(s):  
Karen Davis Czarnecki ◽  
Chris Goranson ◽  
Jennifer A. Ellis ◽  
Laura E. Vichinsky ◽  
Micaela H. Coady ◽  
...  
Keyword(s):  
New York ◽  
Information System ◽  
New York City ◽  
Geographic Information System ◽  
Replacement Therapy ◽  
Nicotine Replacement Therapy ◽  
York City ◽  
Large Scale ◽  
Geographic Information ◽  
Nicotine Replacement

Optimization of Multiple-Route Feeder Bus Service: Application of Geographic Information Systems

2003 ◽  
Vol 1857 (1) ◽  
pp. 56-64 ◽  
Author(s):  
Steven I-Jy Chien ◽  
Feng-Ming Tsai ◽  
Edwin Hou
Keyword(s):  
New York ◽  
New York City ◽  
Information Systems ◽  
Geographic Information Systems ◽  
York City ◽  
Geographic Information ◽  
Service Area ◽  
Street Network ◽  
Transit System ◽  
Demand Distribution

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.

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