In-Depth Analysis of Texas Accidents Using Data-Mining Techniques and Geo-Statistical Analyst Tools
General Material Designation
[Thesis]
First Statement of Responsibility
Faiz ul Islam
Subsequent Statement of Responsibility
Asa, Eric
.PUBLICATION, DISTRIBUTION, ETC
Name of Publisher, Distributor, etc.
North Dakota State University
Date of Publication, Distribution, etc.
2018
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
161
GENERAL NOTES
Text of Note
Committee members: Day, Stephanie; Stone, Matthew
NOTES PERTAINING TO PUBLICATION, DISTRIBUTION, ETC.
Text of Note
Place of publication: United States, Ann Arbor; ISBN=978-0-355-97684-7
DISSERTATION (THESIS) NOTE
Dissertation or thesis details and type of degree
M.S.
Discipline of degree
Construction Management and Engineering
Body granting the degree
North Dakota State University
Text preceding or following the note
2018
SUMMARY OR ABSTRACT
Text of Note
Traffic accidents have been a consistently growing problem in the United States. The road-safety issues have not been completely resolved and pose danger to people driving on the roadways. This research used various approaches and techniques to evaluate and analyze the Texas State traffic-accident dataset profoundly and meticulously. Data-mining techniques were used to analyze the accident dataset for Texas statistically, and information were collected. The resulting information from the analysis suggested that the city of Houston, Texas, was the point of persistent accidents and accounted for most accidents in all Texas cities. Therefore, Houston was analyzed further by using the geostatistical and geo-analyst tools in ArcGIS. The Geostatistical Analysis tools including Space-Time identified the key hotspot locations within the city to study the overall behavior, and developed prediction maps from the kriging tool. A similar approach can apply to other parts of Texas and any location in the United States.