GIS-Based Spatiotemporal Analysis of Property-Damage-Only Accidents Sharjah UAE =التحليل المكاني لبيانات الحوادث المرورية البسيطة للمركبات في إمارة الشارقة خلال الفترة الزمنية /
وكيل مرتبط
Al-Ruzouq, Rami Issa,, مشرف الرسالة العلمية
Hamad, Khaled., مشرف الرسالة العلمية
تاريخ النشر
2023
اللغة
الأنجليزية
الكلمة الدالة
نوع الرسالة الجامعية
Thesis
الملخص
Studying traffic accident's rates is one of the important indicators that governments and traffic safety authorities across the world rely on to be able to understand the causes and repercussions of this Man-made phenomenon. Recent studies have relied on scientific and technological methods to reach more accurate results and facts. The most effective method to study and analysis this phenomenon is to use geographic information systems (GIS), by studying the spatial relationship of the traffic accidents and performing temporal analysis. The main aim of this study is to analyze the spatial distribution of property-damage-only accidents thus a better understanding of the relationships between this type of traffic accidents vehicle type, drivers, road facilities and Land cover/ Land use across the Sharjah Emirate using eight years data between 2015 and 2022 based on accident records from Saeed and Rafid , while Road and Land cover/Land use provided by Department of Town Planning and Survey. Various data preprocess has been conducted to build a geodatabase of the study with additional attributes in obtained data. In this research Kernel density estimation, Moran's I method of spatial autocorrelation and Getis-OrdGi* statistic have been adopted to identify the critical spots and high-density areas. Some infrastructure's suggestion has been made based on these results that will help the road safety concerned authorities and decision makers in the Emirate of Sharjah to take appropriate actions and put in action plans to decrease rate of PDO accidents and increase road safety level across the emirate.
ملاحظة
A Thesis Submitted in Partial Fulfilment of the Requirements for Master of Geographic Information Systems and Remote Sensing, University of Sharjah, May, 2023.
القالب
أطروحات
تصنيف مكتبة الكونجرس
HE5614.U5 A45 2023
المعرف المحلي
b16375798