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Integration of GIS and Spatial Stati...

Khan, Ghazan.

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Integration of GIS and Spatial Statistics---A New Paradigm in Crash Data Analysis.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Integration of GIS and Spatial Statistics---A New Paradigm in Crash Data Analysis./
Author:	Khan, Ghazan.
Description:	235 p.
Notes:	Source: Dissertation Abstracts International, Volume: 73-08(E), Section: B.
Contained By:	Dissertation Abstracts International73-08B(E).
Subject:	Engineering, Civil. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3505047
ISBN:	9781267289384

Integration of GIS and Spatial Statistics---A New Paradigm in Crash Data Analysis.
Khan, Ghazan.

Integration of GIS and Spatial Statistics---A New Paradigm in Crash Data Analysis. - 235 p.

Source: Dissertation Abstracts International, Volume: 73-08(E), Section: B.

Thesis (Ph.D.)--The University of Wisconsin - Madison, 2012.

The objective of this research was to advance the science of crash data analysis through the development of spatial statistical analysis in network space to take advantage of the geography of crashes in understanding the crash problem. A Spatial Analytical Framework was developed comprising of a number of methods and tools to extend the analysis of crash data into the realm of spatial data analysis. The framework takes advantage of spatial statistical methods integrated with Geographic Information System (GIS) models and analytical tools to analyze crash data spatially.

ISBN: 9781267289384Subjects--Topical Terms:

783781
Engineering, Civil.

Integration of GIS and Spatial Statistics---A New Paradigm in Crash Data Analysis.
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020 $a 9781267289384
035 $a (MiAaPQ)AAI3505047
035 $a AAI3505047
040 $a MiAaPQ $c MiAaPQ
100 1 $a Khan, Ghazan. $3 2102010
245 1 0 $a Integration of GIS and Spatial Statistics---A New Paradigm in Crash Data Analysis.
300 $a 235 p.
500 $a Source: Dissertation Abstracts International, Volume: 73-08(E), Section: B.
500 $a Adviser: David A. Noyce.
502 $a Thesis (Ph.D.)--The University of Wisconsin - Madison, 2012.
520 $a The objective of this research was to advance the science of crash data analysis through the development of spatial statistical analysis in network space to take advantage of the geography of crashes in understanding the crash problem. A Spatial Analytical Framework was developed comprising of a number of methods and tools to extend the analysis of crash data into the realm of spatial data analysis. The framework takes advantage of spatial statistical methods integrated with Geographic Information System (GIS) models and analytical tools to analyze crash data spatially.
520 $a The Spatial Analytical Framework consisted of two parts, Theoretical and Computational Framework. The Theoretical Framework consisted of new and modified methods based on different variants of K-Function (distance-based statistic) adapted to network space to resolve issues identified in the literature pertaining to network vs. planar space, the uniform and non-uniform network problem, anisotropy in transportation data analysis, and the need for variable distance based statistic. The Computational Framework consisted of specific programs and tools developed to facilitate the practical implementation of Spatial Analytical Framework while addressing issues relating to the analysis of multiple point patterns and computation of local network statistic. The Spatial Analytical Framework paves the way for a new paradigm in crash data analysis through the integration of GIS and spatial statistics in network space and encompasses solutions to a number of theoretical and computational issues as major contributions of this research.
520 $a The performance and effectiveness of the Spatial Analytical Framework was evaluated by analyzing the crossover median crash (CMC) problem in Wisconsin. CMCs were analyzed to identify hotspots and factors affecting the crashes from a new perspective identifying the magnitude and extent of spatial relationships; revealing results which were previously unknown. The results of the analysis of CMCs under the Spatial Analytical Framework provided new insight into the CMC problem. Crucially, the results clearly illustrated the advantages of GIS-based spatial statistical analysis in analyzing crash data in network space. The methods developed under the Spatial Analytical Framework are applicable to any network-based dataset.
590 $a School code: 0262.
650 4 $a Engineering, Civil. $3 783781
650 4 $a Geodesy. $3 550741
650 4 $a Statistics. $3 517247
690 $a 0543
690 $a 0370
690 $a 0463
710 2 $a The University of Wisconsin - Madison. $b Civil & Environmental Engr. $3 2097812
773 0 $t Dissertation Abstracts International $g 73-08B(E).
790 $a 0262
791 $a Ph.D.
792 $a 2012
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3505047