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The computational testing of urban g...

Goldstein, Noah Charles.

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The computational testing of urban growth modeling.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	The computational testing of urban growth modeling./
Author:	Goldstein, Noah Charles.
Description:	247 p.
Notes:	Chair: Keith Clarke.
Contained By:	Dissertation Abstracts International66-12A.
Subject:	Engineering, System Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3199821
ISBN:	9780542463419

The computational testing of urban growth modeling.
Goldstein, Noah Charles.

The computational testing of urban growth modeling. - 247 p.

Chair: Keith Clarke.

Thesis (Ph.D.)--University of California, Santa Barbara, 2005.

Modeling spatial systems with the Complex Systems approach has been applied to many geographic phenomena with wide applications. Simulation modeling is a powerful tool in its ability to create a system in silico, and then test the outcomes of different scenarios. Simulation modeling can help understand the complex and complicated dynamics of a system, as well as lend insight to the role of the parts of the systems, and their context. Using Complex Systems Simulation (CSS) techniques to model urban regions has had a long and promising history. The unique fabric of the city, where people, nature, culture, technology, and government all meet, has provided a rich palette to examine major geographic issues. The spatial modeling of urban systems, with or without CSS approaches, has importance as the results of such endeavors can have far-reaching impacts in our most dominating human-created geographic feature, the City.

ISBN: 9780542463419Subjects--Topical Terms:

1018128
Engineering, System Science.

The computational testing of urban growth modeling.
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008 110927s2005 eng d
020 $a 9780542463419
035 $a (UMI)AAI3199821
035 $a AAI3199821
040 $a UMI $c UMI
100 1 $a Goldstein, Noah Charles. $3 1296159
245 1 4 $a The computational testing of urban growth modeling.
300 $a 247 p.
500 $a Chair: Keith Clarke.
500 $a Source: Dissertation Abstracts International, Volume: 66-12, Section: A, page: 4485.
502 $a Thesis (Ph.D.)--University of California, Santa Barbara, 2005.
520 $a Modeling spatial systems with the Complex Systems approach has been applied to many geographic phenomena with wide applications. Simulation modeling is a powerful tool in its ability to create a system in silico, and then test the outcomes of different scenarios. Simulation modeling can help understand the complex and complicated dynamics of a system, as well as lend insight to the role of the parts of the systems, and their context. Using Complex Systems Simulation (CSS) techniques to model urban regions has had a long and promising history. The unique fabric of the city, where people, nature, culture, technology, and government all meet, has provided a rich palette to examine major geographic issues. The spatial modeling of urban systems, with or without CSS approaches, has importance as the results of such endeavors can have far-reaching impacts in our most dominating human-created geographic feature, the City.
520 $a Even with their increasingly widespread application, no formal methodology exists for the rigorous testing of CSS models and their applications. This work presents a methodology to test certain aspects of CSS models, as they are applied to Urban Growth modeling. This will lead to (i) a greater understanding of the urban simulation itself, (ii) a greater understanding of the real urban system it represents, as well as (iii) a greater understanding of the usage of complex simulations in general.
520 $a This was accomplished by examining four components of the computational testing of the SLEUTH urban growth model. These chapters examine (1) the utility of CSS approaches to recreating historical urban extent, (2) the improvement of the calibration phase of an urban growth model, (3) a new metric of assessing the topological variety of the outputs of an urban growth model, and (4) the challenges and contextual issues surrounding the linking of and urban model to a wildfire risk model.
590 $a School code: 0035.
650 4 $a Engineering, System Science. $3 1018128
650 4 $a Geography. $3 524010
690 $a 0366
690 $a 0790
710 2 0 $a University of California, Santa Barbara. $3 1017586
773 0 $t Dissertation Abstracts International $g 66-12A.
790 $a 0035
790 1 0 $a Clarke, Keith, $e advisor
791 $a Ph.D.
792 $a 2005
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3199821