اطروة أستاذ أحمد_القزاز مقوم_علمي

Republic of Iraq
Ministry of Higher Education and Scientific Research
University of Babylon
College of Engineering
Civil Engineering Department
Spatial Analyses of Pavement Management for
Selected Signalized Intersections in Hilla City
A Thesis
Submitted to the College of Engineering/University of Babylon in Partial
Fulfillment of the Requirements for the Degree of Master in Engineering/
Civil Engineering/ Transportations
By
(B.Sc. in Civil Engineering 2005)
Supervised By
2020 AD 1441 AH

‫الرحيم‬‫الرحمن‬‫هللا‬ ‫بسم‬
﴿
‫نا‬َ
‫ت‬ْ
‫م‬َ
‫ل‬َ
‫ع‬ ‫ما‬ ‫إال‬‫نا‬َ
‫ل‬ َ
‫م‬ْ‫ل‬ِ
‫ع‬َ‫ال‬ َ
‫ك‬َ
‫حان‬ْ‫ب‬ُ
‫س‬ْ‫ا‬‫و‬ُ
‫ل‬‫ا‬َ‫ق‬
ُ
‫يم‬ِ
‫ك‬َ
‫الح‬ُ
‫يم‬ِ
‫ل‬َ
‫الع‬ َ
‫أنت‬ َ
‫إنك‬
﴾
‫العظيم‬‫هللا‬ ‫صدق‬
‫سورة‬
‫البقرة‬
‫االية‬
(
٣٢
)

Certification of the Examining Committee
We certify that we have read the thesis entitled (Spatial Analyses of
Pavement Management for Selected Signalized Intersections in Hilla City)
and as an examining committee, examined the student “ " “in its
content and in what is connected with it, and that in our opinion it is
adequate as a thesis for the degree of Master of Science in Civil Engineering.
Signature:
Name:
(Chairman)
Date: / / 2020
Signature:
Name:
(Member)
Date: / / 2020
Signature:
Name:
(Member)
Date: / / 2020
Signature:
Name:
(Supervisor and Member)
Date: / / 2020
Signature:
Name: (Member)
Date: / / 2020
Signature:
Name: Asst. Prof. Dr. Thair Jabbar Mizhir Alfatlawi
(Head of Civil Engineering Department)
Date: / / 2020
Signature:
Name: Prof. Dr. Hatem Hadi Obaid
(The Acting Dean of the College of Engineering)
Date: / / 2020

Supervisor Certification
We certify that this thesis which is entitled (Spatial Analyses of
Pavement Management for Selected Signalized Intersections in Hilla
City) has been prepared by “ " under my supervision at College of
Engineering, Babylon University, in partial fulfilment of the requirements
for the degree of Master of Science in Transportation Engineering.
Signature:
Name:
Date: / / 2020

Acknowledgements
Thanks and appreciation
Thank God Almighty and thanks to his help this work could be done.
Special thanks and gratitude to my supervisors: Prof. Dr. Hussein
Ali Awad for his great efforts, interests, follow-up, great help, valuable
expectations, and his continued scientific guidance throughout the course
of this study to obtain the best job. His dedication to academic work has
always been an inspiration for a better boom. It was my pleasure and
ambition to be the supervisor.
I also express my appreciation to the University of Babylon for
giving me this cosmetic opportunity for this study. Moreover, we thank all
the lecturers at the College of Engineering and especially the Department
of Civil Engineering under his leadership and professors for their continued
encouragement and support. And also to all of my colleagues.
As well as, Great thank for every person supporting me
during entire this project, especially my friends.
I would also like to thank the panelists who spent part of their
valuable time reading and discussing my thesis.
/ / 2020

Dedication
The deepest words of gratitude and appreciation are the gratitude and
dedication of a great person, if you are where I am today, then that is why
it deserves a special mention that it is my father. I will not forget to devote
the fruits of this effort to those who filled me with supplication and what
I am today is God's response to her prayers for me. She is my mother.
My great gratitude and gratitude for the companion of my way at
home and at work, who did her best to accompany me in completing this
extraordinary effort. She is my wife.
My sincere appreciation to my brothers, sister and daughters, I feel
very lucky that they have been in my life.
Sincerity to my family and friends goes for their love, support,
guidance, and endless patience in all my endeavours.
/ / 2020

Abstract
I
Abstracts
Road infrastructure is essential for safety and population growth in
every country. As the performance of road pavement infrastructures is
complex and is affected by many factors, and this impact varies greatly with
different methods and their uses. Because of these large differences, there is
an increasing need for large-scale spatial analysis to assess the performance
of road infrastructure for management, and therefore multiple sources are
collected, including remote satellite data and climate data, and monitoring of
vehicles whose freedom is monitored on these roads, as explanatory
variables. Unlike conventional geospatial assumptions based on an area or
point, the pavements infrastructure's performance is spatial data depending
on line segments. Therefore, a section-based spatial stratification
heterogeneity approach is used to investigate the following qualities of
automobiles, environment, road characteristics, and socio-economic cases
on the efficiency of pavement infrastructure. Section-based optimal
discretization is applied to discrete section-based pavement details, and a
section-based regional detection system is used to determine the spatial
effects and interactions of variables.
Repeated and periodic assessments of pavement conditions at
intersection sites to improve the serviceability of intersection, is an essential
component of the transportation system. Further, continuous maintenance of
deterioration and defects that appear on the surface layers of pavement at
intersection sites according to pavement condition indices (PCI), is a vital
process in pavement management. This research aims at conducting spatial
analysis for pavement conditions at intersection sites. The application of the
developed measure is demonstrated for three signalized intersections in Hilla
city, Iraq, by using distress definition. Point density Estimation (PDE) as
spatial analyses and interpolation tool (IDW) in ArcGIS software is used to

Abstract
II
estimate the position severity. PDE for Pavement condition applications
enables the visualization and extraction of distress density in a selected zone
or a network of road, which gives the makers of decision an advanced vision
to the problem within a location. In this paper, PDE is used to generate
potential distress heat maps based on distress definition data. The result of
this research shows the suitability of the heat map for the maintenance
entitlement of a particular intersection. It gives a clear indication of the
deterioration in the pavement layers depending on the severity of the colors
shown in the heat map. For instance, a section of a high score of PCI may
include very deteriorating units of low score of PCI due to the presence of
any defects. Hence, it can be concluded that it is doubtful that the PCI section
represents the reality of all units. As a sample section (D) of the AL Thawra
intersection where there were damaged units, PCI reached 55, 56, 59, while
the PCI of section (D) was 74. The developed heat map demonstrates
deterioration condition thoroughly for all units and provides the advanced
vision to pavement condition at the studied sites.
After that, a heat map was drawn with five hues, each color
representing a specific range of (PCI). The map includes a legend that shows
the maintenance mechanism according to each hue. The hue starts from
green, which indicates a high (PCI), and therefore it does not need
maintenance. Passing through several grades and finishing with a red, which
refers to low (PCI) in which the maintenance type is to re-create the damaged
tiled layers again.
Any engineer when reading heat map can easily get access to the
distressed places on the pavement of the intersection and the type of
appropriate maintenance for those defects.

Content
III
Contents
Contents
Abstracts ....................................................................................................................... I
Contents......................................................................................................................III
List of Figures........................................................................................................... VII
List of Plates ............................................................................................................VIII
List of Table.................................................................................................................X
List of Symbols and Abbreviations............................................................................. XI
Chapter One ..................................................................................................................1
Introduction...................................................................................................................1
1.1 Background.............................................................................................................1
1.2 The Explanation of Network of pavement................................................................2
1.2.1 Identification of the Network................................................................................2
1.2.2 Identification of the Branch ..................................................................................2
1.2.3 Identification of the Segment................................................................................3
1.3 Identification of the Problem ...................................................................................5
1.4 Goal and Objectives of the Thesis............................................................................6
1.5 The Components of Suggested PMMS.....................................................................7
1.6 PMMS Architecture.................................................................................................8
1.7 Outline of Thesis .....................................................................................................9
Chapter two.................................................................................................................11
LITERATURE REVIEW............................................................................................11
2.1 History of Systems for Managing Pavement (PMS) ...............................................11
2.2 PMS Integration with Maps...................................................................................12
2.3 PMS by GIS ..........................................................................................................14

Content
IV
2.4 Advantages of GIS/PMS Integration......................................................................16
2.5 The Use of GIS in Pavement Maintaining..............................................................17
2.6 Spatial Analysis.....................................................................................................19
2.6.1 Kernel density.....................................................................................................20
2.6.2 Formulations for Kernel Density calculating (KDE) ...........................................21
2.6.3 Line density........................................................................................................21
2.6.4 Point density Estimation (PDE) ..........................................................................22
2.7 Interpolation Methods............................................................................................23
2.7.1 Inverse Distance Weighted (IDW) ......................................................................23
2.7.2 Applying Spatial Analysis in Managing Pavement..............................................24
2.8 Pavement Distresses ..............................................................................................26
2.8.1 Flexible Pavement Distresses..............................................................................26
2.8.2 Assessment of Pavement Distress .......................................................................28
2.8.2.1 Detailed Manual Inspection: ............................................................................29
2.8.2.2 Windshield Survey:..........................................................................................29
2.8.2.3 Automated Distress Survey Techniques ...........................................................30
2.8.2.4 Other Approaches............................................................................................30
2.9 Index Condition of Pavement.................................................................................30
2.10 Micro PAVER and PAVER.................................................................................32
2.10.1 Determination PCI by PAVER 6 &5.7 Software ...............................................32
CHAPTER THREE.....................................................................................................35
METHODOLOGY AND DATA COLLECTION........................................................35
3.1. Introduction to the city of AL-Hilla ......................................................................35
3.2. General.................................................................................................................36
3.3. Methodology of the Study ....................................................................................36
3.3.1. Point density Estimation (PDE) .........................................................................37
3.2.1. Inverse Distance Weighted (IDW) .....................................................................38

Content
V
3.4. Study Area Description.........................................................................................39
3.4.1. Bab Al-Hussein Intersection ..............................................................................42
3.4.2
. The Intersection of Al-Thawra...........................................................................43
3.4.3
. The 40-St. Intersection.......................................................................................44
3.5. Data Collection.....................................................................................................45
3.5.1. The Data of Geometry .......................................................................................46
3.5.2. Dividing the Network into Manageable Units ....................................................47
3.5.3. Data Inspection..................................................................................................51
3.5.4. Coordinates Data Inspection (Inspection GPS Data)...........................................56
3.6. PAVER Software Capabilities ..............................................................................60
3.6.1. Inventory and Editing Data Inspected by Utilizing PAVER ...............................61
3.7. Techniques of Rehabilitation and Maintenance.....................................................65
3.7.1. Defects Categorization with Remediation Types and Reasons of Defects...........66
3.7.2 Maintenance of Distress in GIS Programs...........................................................74
Chapter Four ...............................................................................................................79
DATA PRESENTATION AND ANALYSIS ..............................................................79
4.1. General.................................................................................................................79
4.2 Hand Calculation of PCI........................................................................................80
4.3 Results of PAVER Software System Application...................................................84
4.4 Calculating PCI after Inspection ............................................................................86
4.5 Integration PAVER Software to GIS......................................................................88
4.5.1 Pavement Condition Index (PCI) by Symbology Tool.........................................88
4.5.2 Drawing heat map for intersection by point density tool......................................90
4.5.3 Drawing heat map for intersection by (IDW) tool ...............................................91
4.5.4 Drawing Heat Map for Intersection by (IDW) Tool with Maintenance:..............93
Chapter Five................................................................................................................95
Conclusions and Recommendations.............................................................................95

Content
VI
5.1 Conclusions...........................................................................................................95
5.2 Recommendation...................................................................................................96
Reference 97
Appendix A...............................................................................................................A-1
Appendix B...............................................................................................................B-1
Appendix C...............................................................................................................C-1
Appendix D...............................................................................................................D-1

List of Figures
VII
List of Figures
Figure No. Page No.
Figure (2.1) Sample of Vector Data and Raster (Hill, 2006). 14
Figure (2.2) Creation of Normal PMS for a Local location 15
Figure (2.3) Strategy of GIS Functionality. 17
Figure (2.4) Systems of Pavement Management Maintenance (PMMS)
Vs. System of Pavement Managing (PMS).
19
Figure (2.5) Screen for Inverse Distance Weighted (IDW) 24
Figure (2.6) Pavement Condition Index (PCI) Ranges (U.S Army Corps
of Engineers, 2012)
34
Figure (3.1) Location of Hilla City from Iraq. 35
Figure (3-2) Research Methodology 40
Figure (3-3) Location of Study Area and Sites 41
Figure (3-4) The studied intersections using (GIS) 42
Figure (3-5) GIS Map for the Selected Bab Al-Hussein Intersection 43
Figure (3-6) GIS Map for the Selected Al-Thawra Intersection 44
Figure (3-7) GIS Map for the Selected 40-St.Intersections 45
Figure (3-8) A Sample division of Intersection into Segments 47
Figure (3-9) Choose lowest Specimen Unit Number. 50
Figure (3-10) Divided sample units of ALThawra intersection at SB 49
Figure (3-11-1) The Distress Type in Field of Al-Thawra Intersection 53
Figure (3-12) Using Excel software to input X,Y coordinate 58
Figure (3-13) Pavement Maintenance and Rehabilitation Alternatives
(Garber, 2009)
75
Figure (4-1) Patching and Utility Cut Patching, Joint Reflection
Cracking, Block Cracking Distress Deduct Value curves
81
Figure (4-2) The Correction Curves for AC Surfaced road 82

List of Plates
VIII
List of Plates
Plates No. Page No.
Plate (3-1) Add X, Y Data. 59
Plate (3-2) Arc Map Toolbox Screen Point Density. 59
Plate (3-3) Arc Map Toolbox Screen IDW. 60
Plate (3-4) PAVER Screen for Defining Pavement Inventory (Network) 62
Plate (3-5) PAVER Screen for Defining Pavement Inventory (Branch). 63
Plate (3-6) PAVER Screen for Defining Pavement Inventory (Section). 63
Plate (3-7) PAVER Software Screen for Editing Inspection Dates 64
Plate (3-8) PAVER Software Screen for Entering Inspection Dates 64
Plate (3-9) Entering Inspected Data of Section and Calculating
Pavement Condition
65
Plate (4-1) PCI Sample of Calculation Result Using Software
(PAVER).
87
Plate (4-2) PCI Sample of Calculation Result Using Software
(PAVER).
88
Plate (4-3) Smbology of 40 St. Intersection. 89
Plate (4-4) Symbology of Al-Thawra Intersection. 89
Plate (4-5) Symbology of Bab-Al-Hussain Intersection. 90
Plate (4-6) Heat Map of Al-Thawra Intersection by Point Density Tool. 91
Plate ( 4-7) Heat Map of Al-Thawra Intersection by (IDW) Tool 92

List of Plates
IX
Plate (4-8) Heat Map of 40 St. Intersection by (IDW) Tool 92
Plate (4-9) Heat Map of Bab-Al-Hussain Intersection by (IDW) Tool. 93
Plate (4-10) Heat Map of 40 St. Intersection by (IDW) Tool with
Maintenance.
94

List of Tables
X
List of Table
Table No. Page No.
Table (2.1) PAVER Software Classification Distress for Flexible
Pavement highways and Parking (Shahin, 2005; Yoder and Witczak,
1975).
28
Table (2.2) Description for Paving situation Level (ASTM D6433,
2011).
31
Table (3.1) Brief Explanation of The Study 36
Table (3.2) The Intersections’ Geometrical Data 46
Table (3.3) Number of Sample Unit for Each Approach 51
Table (3.4) The Inspection Data for Section (A1) of AL-Thawra
Intersection at SB.
52
Table (3.5) Pavement Condition Index with general treatment
strategy
74
Table (3-6) Distress Rehabilitation and Maintenance (shahin, 2005). 75
Table (4.1) The PCI Hand Calculation Results for each Unit in
Section for Al-Thawra Intersection
83
Table (4.2) PAVER Distresses Categorization for Asphalt Flattened
Parking and highway lots (Shahin, M.Y., 2005; U.S Army Corps of
Engineers, 2011).
85

List of Abbreviations
XI
List of Symbols and Abbreviations
Symbols Details
AASHTO American Association of State Highway and
Transportation Officials
AC Asphalt Concrete
ASTM American Society for Testing and Materials
CBD Central Business District
CDV Corrected Deduct Value
FHWA Federal Highway Administration
GIS Geographic Information System
GPS Global Positioning System
M&R Maintenance and Rehabilitation
MP Maintenance Priority
PCI Pavement Condition Index
PDI Pavement Distress Index
PMS Pavement Management System
TDV Total Deduct Value
HM Heat map
IDW Inverse distance weight
PD Point density
KD Kernel density
LD Line density

Chapter One Introduction
1
Chapter One
Introduction
1.1 Background
No one disputes the network of pavement is one of the community's
key transportation tools. Maintaining and maintaining these essential
transport assets would be beneficial in achieving greater health, convenience
and efficiency in the area of public transport. Hence the proper managing of
their care is important for the society. The System of Pavement Managing
(PMS) is a device or systemic approach that could include an equitable
network of pavement product, and coordinate the work with time and energy
savings. As well as, The system gives the data referring to the existing state
for the system of pavement that have the capacity to collect historic data that
aids to estimate the future situation of the pavement. In fact, the program
should assess pavements and determine a suitable maintenance requirements
with goals within the funds available (Shahin, 2005a). The System of
Geographical data (GIS) is the technical method that aims to design, execute,
and handle PMS. PMS GIS is used to store, interpret and view the data of
pavement in a code color like maps-thematic. There are unusual reports on
the incorporation of GIS with PMS for lots of parking and highway on
university campus. Applying effective PMS for the Universities campus
network of pavement requires a similar approach to this system which is used
for towns and small towns. This work uses Micro PAVER and GIS tools to
develop System of Pavement Managing for the campus of the Eastern
Mediterranean University. For this report, Micro PAVER was used as paving
management tools by inserting the paving situation data that was obtained
visually on the campus for both lots of parking and asphalt road, as well as
ArcGIS is utilized for spatial analysis, pavement data display and

2
maintenance predicting for the campus network of pavement. The obtainable
or minimal budget cannot be adequate for maintaining roadways at the
campus. GIS based PMS therefore is a knowledgeable and suitable solutions
to this state.
1.2 The Explanation of Network of pavement
These instructions to classify and describe the networks, branches, and
parts of pavement. Such guidelines must be treated as guidelines and could
be amended when appropriate to accommodate unique circumstances or
different criteria for agencies. For every pavement segment the initial data
collection could be very time consuming. This usually happens when,
throughout the initial System’s setup of Pavement Managing (PMS), a
comprehensive coring or testing software package is undertaken
1.2.1 Identification of the Network
Network Recognition is the first step in creating a PMS. A network is
a logical bundling of R & M pavements’ management. The manager of the
pavement might be responsible for airfields, maintaining highways, lots of
parking, and other facilities of vehicular kinds that are paved or unsurfaced.
The manager will determine what categories of facilities to classify as
different networks. Certain considerations to consider beyond types of
facilities are sources of financing, minimum operating requirements and
geographic location.
1.2.2 Identification of the Branch
A branch is an easily recognizable the network of pavements part and
has a specific purpose. For instance, a car park or a single street will be
measured a distinct pavement network branch. Branch naming conventions

3
which are appropriate for the PMS consumers and managers of pavement
must be enforced.
To start with, every street in the map of the network is marked as a
distinct lane and provided the street’s name. The method could also be used
on parking lots; however, descriptive names may be granted to parking lots
that have not already allocated terms to identify them with their position. The
nearest numbers of building, for instance, may be utilized as a name’s part.
In addition, several lesser lots may be merged to create one lane, based on
their size and position if appropriate.
1.2.3 Identification of the Segment
A lane doesn't often a division has clear features over the whole length
or region. For administrative reasons, organizations are split into smaller
parts, named "units." When assessing the implementation and allocation of
specific repair and maintenance (R & M) remediation, a section will be
regarded as the smallest management entity. Only a section will be in similar
surface form (such as pavement, asphalt over stone, etc.). The lane consist
of at least one section which may be more if pavement characteristics vary
across the lane. While dividing branches into parts, the factors to consider
are: scale, condition, drainages of shoulders and facilities, pavement rank (or
functional categorizing), traffic, history building, and layout of pavement. A
summary of every of those variables follows.
1. The Structure of Pavement
Some of the most relevant requirements for separating a branch into
parts is structure of pavement. The structural composition (materials and
thickness) must be dependable thru the segment as a whole. Building records
are a good knowledge of that source. The documents may be confirmed by a
small number of cores being taken. In the outset of PMS implementation, a

4
comprehensive coring program must be avoided, unless resources are
limitless.
2. Construction history
Separate parts must be listed for paving built during various years, by
various contractors or utilizing various methods. Areas that have undergone
significant repairs could also be separated into different parts, like certain
slab patches or replacements.
3. Traffic
Load intensity and traffic volume must be regular across every single
segment. Of roads and streets the truck traffic and lanes number must be
given primary consideration. In the streets that have two traffic directions
with four or more lanes, a separate segment for every direction could be
established, particularly if the highway is split. In segment description a
substantial difference in wagon volume between directions must be a main
consideration. An intersegment should only be viewed as a distinct segment
when it is possibly to undergo significant repairing independently of the
pavement adjacent it.
4. The Categorization of the Pavement Functional (Rank)
A variation in rank is typically indicative of a variation in traffic.
When the rank shifts along the length of the branch (for instance, from
arterial to collector, or from main to secondary), a separation of the segment
must be made.
5. The Drainage’s Facilities and Shoulders
Such requirements should be consistent over a section, to the extent
that shoulder and drainage requirements impact pavement efficiency.

5
6. Conditions
Systematic changes in the condition of pavement must be considered
if identify pavement segments of. Condition is a significant variable since it
redisplays several factors that mentioned previously. Variations in forms,
amounts, or reasons of distress must be considered. Experience has
demonstrated that a grouping of NDT profiles and a distress state index leads
to very good segment descriptions.
7. Segment Size
Segment size may have considerable effect on implementation
economics. Defining very short parts needs a higher cost and effort of
enforcing to ensure uniformity. The segments might also be too limited for
efficient scheduling of individual M&R works. The characteristics could not
be compatible across the entire region if they are too large. This situation
could lead to non-uniform parts resulting in ineffective budget decisions and
design in turn. Parking lots are subject to the same rules about road and street
segment sizes. The small lots of parking may be gathered into one segment
in the situation of very small lots of parking (implemented for specific cars)
It is often recommended that segments be numbered uniformly. For e.g, east
to west, south to north, and for circular roads in clockwise direction.
1.3 Identification of the Problem
The display threats to Babel City pavements are as follows:
• Increasing the rate of decay. (Pavings worsen rapidly)
• Engine overloading; (No formal loading commitment)
• A fast increase in traffic. (Great rise in ownership of vehicles)
• Low retention. (Inappropriate fabrics, improper execution, etc.)
• Specification and execution insufficient.

6
• Assets limited (geometry, funds, supplies, materials etc.)
• Insufficient information to make decisions.
• Conventional management system pose ineffective.
• The traditional maintenance method currently in use in the
municipality of Babel demonstrates that:
• Documentation is in short supply.
• The Road Maintenance Department does not use the computer
programs to store and process device data.
• The program is not robust enough to adjust work timetables and
schedules to accommodate changing conditions.
• The program is weak in helping decision-making.
• From the previous points, the need for a comprehensive PMMS is
high, involving:
• Databases: enable the management of device physical data and allow
data to be stored, retrieved, displayed, modified, and queried.
• The abilities of GIS: permit for the representation of geographic
reports and inventory data.
• Assessment of system: helps in creation prompt, decisions to reduce
effective cost related to surface repair and repairing.
• Device Modeling: gives information on goals, costs, maintenance
requirements, etc.
1.4 Goal and Objectives of the Thesis
The main objective of this work is to establish a PMS that provides a
systematic methodology for road protection, promotion and control in a GIS
setting. To order to achieve these aims, the following targets must be found:
• Create an inventory of routes at different intersegments.

7
• Establish a geo-referenced GIS profile with a suitable database which
could be modified.
• Use a roadside assessment solution.
• Integrating pavement management tools such as MicroPAVER with
ArcGIS for displaying, reading and analyzing decision-making help
results.
• Recommend maintenance care options and forecast prioritization of
possible maintenance jobs.
• Report and record analytical findings with presentation of various
tables, graphs and thematic maps.
1.5 The Components of Suggested PMMS
Usually a PMMS primarily consists of two main components:
• An operating network for the data and knowledge processing, storage
and management.
• Decision support system for collecting and assessing such decision-
making results.
The suggested PMMS components mainly depend on the following
three applications for management:
1. Micro PAVER
It is used as a paving management tool to store the values of inventory
information, distress data and the Paving Condition Index (PCI). It helps in
assessing pavements in the area. Using this app, condition assessment could
be done conveniently and swiftly.
2. GeoMedia Professional
It is used as a GIS tool offering a full range of spatial analysis and
providing a framework for high-performance decision taking. Clearly, the
above-mentioned components use the format of the Access database and thus

8
the information system is stored, although they do have the capability to
perform full analysis.
1.6 PMMS Architecture
GeoMedia Professional and GUI has been integrated for supporting:
• Maintenance works performing.
• Management of maintenance operations.
Every of the PMMS software modules provides features to help the
specific PMMS process tasks. Gaza PMMS is based on direct integration of
the programs Micro PAVER and GeoMedia Professional. Micro PAVER
gathers and processes inspection data to assess network of pavement. Results
are stored in the PAVER database, and then linked via the Warehouse
Connection Wizard to GeoMedia. Joining PAVER and GeoMedia databases
is defined in both on the basis of the identical segment ID. This will allow
the data and condition results to be updated into the GeoMedia database after
every periodic inspection. A simple GUI, called PMMS, was created to help
explain the findings of the PMMS and justify the decisions taken. This
Interface includes user-friendly menus which could be called Micro.
PAVER and data with GeoMedia. This also has the capability to
conduct fast queries and different reporting styles. Documents could also be
exported in various types of document format (PDF, Excel, Word, etc.). With
this tool the GUI will provide answers to every of the following questions:
1. The Kind of Pavement: Which segments are closed unpaved, or
paved?
2. Situation of Pavement: Which segments or branches are with
excellent, poor, failed cases, etc?
3. The Maintenance of Pavement: Which segments require routine
maintenance, reconstruction or overlaying?

9
4. The Cost of Remediation: What are the remediation cost for every
segment, every branch or overall?
The PMMS software provides both the Micro PAVER and GeoMedia
info. Its basic concept of analysis is focused on information about the PCI
magnitudes, location, functional categorization and other information for
every segment of the network of pavement in Gaza. The required form of
condition and method of remediation could then be defined. PMMS also
requires the inclusion of unit costs for every service type and this will help
measure cost of repair for every segment.
1.7 Outline of Thesis
Seven chapters make up the paper. The first chapter displays the
context and inspiration behind this thesis; a brief overview of the general
insight into the current state of crash data in Iraq and hill City, a statement
issue, and the thesis objectives.
Chapter two consists of a literature review conducted prior to
beginning this thesis. Discussion an application of spatial analyses and the
relation between the operating performance measure and PCI performance
measure.
Chapter three explains what data were required and how they were
collected with a brief description of the data.
Chapter four focuses on the implementation of both Micro PAVER
and GeoMedia. The basic research theory is focused on information of the
PCI meaning, location, functional description and other details to every
segment of the hilla city network of pavement intersegment.
Chapter five includes analyses and sheets of PCI and paver softwar
based on data collected from study sites.

10
Chapter six: includes the development of a new index to measure and
assess PCI for intersegment and connect it with GIS utilizing spatial analysis
method.

Chapter Two Literature Review
11
Chapter two
LITERATURE REVIEW
2.1 History of Systems for Managing Pavement (PMS)
The System for Managing Pavement (PMS) is defined as: "a collection of
techniques or tools that could help makers of decisions in identifying
solutions of effective cost to give, assess and maintain pavement in a
working case" (AAShTO, 1990).
PMS may answer the following questions, based on the above description:
• What are the most cost efficient recovery and maintenance (R&M)
strategies?
• Where are M&R treatments needed (which paving segments)?
• When will the time (condition) to schedule a treatment be the most
appropriate?
In the recent economic environment era the idea of PMS took root in the
United States. In the mid-seventies the highways Department of Washington
State developed the early PMS model. This model included models of a cost
and performance predicting focused on a collection of data collected during
time ranging from (six to eight years) in Washington. Subsequently many
state transport departments created special PMS procedures suitable for their
own purposes and desires (Niju, 2006).
Sims and Zhang (2007) performed an investigation and found that running
the largest network of pavement in the United States along with more than
193,000 miles1 of road under their jurisdiction, Transportation Department
of Texas (TxDOT) was the biggest pavement managing champion and has

12
long been considering using PMS for the network of pavement in Texas. The
vast scale of this network and its related requirements have also provided an
incentive to think of these structures for additional-competent and efficient
making decisions, in addition to the fact that TxDOT paid annually
2,700,000,000 dollars in R & M pavements acts until 2007. The
comprehensive pavement disturbance data collection system in the
Transportation Department of Louisiana and Developing (DOTD) has
considerably advanced from storefront surveys in the main seventies to make
a video recording in 1992 after that to the Automatic Road analysis tool in
1995. The pavement network is assessed until 2008 after every two years of
application of such methods (Khattaket al., 2008).
Broten (1996) disputed that PMS could not make the ending decision that
the people or engineers who are using the data generated by this program
should make the decisions. In other words, PMS serves as a guide to help in
the making of the decisions (Bryar, 2013)
2.2 PMS Integration with Maps
Clear and updatable implementation of a good PMS for a particular network
of pavement should be. Linking PMS to maps in this situation could be
helpful in meeting these requirements.
Agencies have two simple choices to demonstrate PMS details on the maps.
The first is to construct an interface using one of the mapping tools, such as
AutoCAD, to the pavement database. This approach is both simple and
inexpensive, and aids display data of PMS on a map. Nevertheless, it could
not give whole supporting for data analysis. The second alternative is to
combine PMS with a Geographical Information System (GIS). With the
capability to analyzing the data and generate spatial enquiries, GIS-based
PMS could view both network of pavement map and paving situation

13
(Broten, 1996). It is extremely important to note that combining PMS by
GIS requires additional skills and requires more expense comparison with
automatic AutoCAD map "A System Geographical data (GIS) is a
calculated-based resource for information output, retrieval, administration,
storage and input " (Sikder et al., 2003). This knowledge is referring to
geographical location or similar characteristics place. As well as anyone can
assume that GIS would answer the questions about where items are or what's
located at a specific position. A GIS is composed of data attributes, spatial
geo-coded data, and two large data sorting. Spatial geo-coded data defines
objects in two or three-dimensional spaces which have an orientation and
relation. Attributes associated with the road segment might include its data
of traffic, history of construction, condition of the pavement, lanes number
and width. Information collected for an incident may include fields for type
of vehicle, environment, time of day and injury. This characteristic data is
connected to a topological object (polygon, line or point), which has a
location anywhere on the earth's surface; a well-GIS designed allows for the
incorporation of these data. The database of sophisticated inside a GIS has
the capability to link and monitor spatial controlled data variable sets that
were geo-coded to the popular controlling scheme (Jain et al., 2003). As
demonstrated in Figure 2.1 GIS consists of 2 types of spatial data, vector and
raster. A data of raster is some type of digital image, like a topographical
illustration or aerial photo. The drawn data as columns and cell rows has its
meaning for every single cell. In GIS, instead, these data cells are used to
construct specific thematic maps. The vector data on the other hand is that
system data demonstrated in GIS. Vectors are referred to as shape files and
consist of dots, lines, and polygons. A point of GIS reflects the feature
location on the geographic control grid, like the position of the bridges. A
line is utilized to display linear features, like a road or lake. Furthermore, a

14
polygon is utilized to redisplay a 2D element such as a region of particular
part of the earth, or country borders. Figure 2.1 displays data for both the
vector and the raster.
Figure (2.1) Sample of Vector Data and Raster (Hill, 2006).
2.3 PMS by GIS
As with every managing program, the managing of pavements needs an
efficient decision support system. GIS could be an essential element of the
decision support system by allowing the planning, review, demonstration,
and management of geographic data. GIS will significantly improve the
research and display the information in PMS. Figure (2-2) demonstrates the
local location with typical PMS formation (Jain et al., 2003).

15
Figure (2.2) Creation of Normal PMS for a Local location (Jain et al., 2003).
GIS was used in several fields since the mid-1990s that deal with data
comprising a spatial object, and one of those applications was the use of GIS
in PMS. It offers, for example, the capability to imagine spatially related
pavement details on a map to determine a network's condition quickly. Since
transport authorities have collected enormous quantities of data concerning
the state of the pavement; GIS has become a practical resource for the
managing program. This made it necessary for relating to find a way for
firstly saving and handling like enormous amount of data, and moreover to
have the capacity to use such data effectively to make decisions that
characterized as cost-competent and reasonable in the R & M phase (Grass,

16
2007). Otherwise, in 1997, the Public Services Department in the town of
high Point, North Carolina implemented a network-level PMS that gave it
the capability to conduct both collection data and evaluation alongside GIS
assistment. The data displayed were important when presenting data to
members of the Mayor and Metropolitan Council, Citizen Commissions, and
non-expert individuals (Thomas, 1998).
It's important to note that United State departments aren't the only ones who
use GIS to handle paving. Grass (2007) stated that this definition was
pursued and learned in Japan as well as in India. Nagoya town in central
Japan's Aichi area, used GIS as an instrument inside their PMS throughways.
The plan of GIS has been developed for its spatial capabilities analyzing that
included presentations of GIS for the chosen road network pavement and
area boundaries.
2.4 Advantages of GIS/PMS Integration
Many of the benefits of alignment with GIS / PMS include:
• Capacity to analyze data concerning Pavement Managing (PM) based
on geographic location.
• Demonstrate on the network map results of database queries and PM
studies;
• Showing ground conditions and predicting job schedules on a road
map.
• Capability to view conditions in the pavement through other
georeferenced material, such as zoning and traffic.
• Capability to view and edit map of pavements network.
In fact, it could help PM knowledge by using a method that managers and
the public understand easily (Broten, 1996).

17
Figure (2.3) Strategy of GIS Functionality.
2.5 The Use of GIS in Pavement Maintaining
Because geographic systems information suit the geographic complexity of
road networks with their spatial analysis capabilities, they are measured to
be the utmost suitable devices to improve processes of pavement managing,
with characteristics like graphical demonstration of pavement conditions.
At the present time, as the use of GIS in public authorities is increasing, there
is a growing movement towards incorporating PMS data into the GIS. This
integration is becoming more practical, with the technical advancements in
computer hardware and software. Benefits of this integration involve
versatile database editing and the capability to display data base query results
visually, charting and statistics, pavement managing analyzes on a highway
network map, displaying network conditions via dynamic color coding of

18
highway parts, and accessing segmental data through the graphical map
interface.
Spatially techniques, like Systems of Geographical data (GIS), are especially
suitable for incorporating data of highway and improving the usage and
demonstration of these data for road managing and activity through the use
of spatial relations to connect geo-metric and geographic objects and events
high-way management issues, such as pavement management, include two
different degrees of relationships between events and objects situated in
various spatial locations. The networks of road cover a large area and
connect with different elements of the land, involving houses, mountains,
rivers, and other roads. Due to the spatial components of the data used in the
decision-making process, the using of spatial technology is emerging as a
very desirable option. Spatial techniques will improve the study of many
transport-related problems and increase the efficiency of decision-making
processes (Gary, 2004).
There is no question that road quality and productivity impact the life quality,
the wellbeing of the social system and the sustainability of industry and
economic activities. Such roads could cause degradation and catastrophic
failure due to mismanagement, misuse, overuse, and / or aging. Pro-grams
timely maintenance of pavement will minimize degradation levels, extend
pavement life, reduce vehicle running costs and ensure protection for road
users. In general, treatment methods for pavement could vary from over-
laying, regular patching, sealing, and restoration as a last resort.
GIS apply as a coordinate scheme to determine where every function of the
network of pavement is located. It is an important visual aid for reflecting
both current and future cases of pavement. Arc-view was used as the GIS
development device for sequentially designing the architecture system,
incorporating formats of data, importing databases, and programming all

19
models. Through this method, integrating road maps with all the related
through structure, not only could pavement engineers track paving situation
at any time, but also estimate maintenance budgets. As a guide for advanced
exploration, PMMS-GIS offers authorities and could definitely boost the
pavement maintenance consistency and efficiency by advanced subtractions.
One should not confuse a Pavement Maintenance Management System
(PMS) with a System of Managing Pavement. A PMMS is a part of a PMS
system which means that they supplement rather than replacing every other.
Figure 2.4 illustrates PMMS versus PMS and the overlaying definition
between them (Jendia and Al Hallaq, 2005).
Figure (2.4) Systems of Pavement Management Maintenance (PMMS) Vs. System
of Pavement Managing (PMS).
2.6 Spatial Analysis
Several analytical approaches are available at GIS for spatial analysis and
data integration, grouped under the general heading "overlay analysis." GIS
offers tools for merging data, defining data overlaps, and merging data sets
attributes using location of features and scale as selection criteria. Overlay
methods could combine spatial data in certain ways, such as features that

20
could be merged to simply add one set of spatial data to another, or
modifying or replacing parts of one set of data with another set. Using
overlay analysis, spatial data could be combined by merging two or more
spatial data sets to create a new spatial data set where the function attributes
are a union of input data sets.
In ArcMap, heat maps are generated to redisplay spatial data density. By
using the Space Analyst extension's Density toolset, heat maps are created
from points with either the Kernel Density device or the Point Density
device, and lines with either the Kernel Density device or the Line Density
device.
When the Space Analyst extension is not usable, the data (points, lines, or
polygons) may be symbolized with the use of graduated colors or symbols
to look as a heat map symbology. Use graduated-colours, ArcMap: Use
graduated symbols, and ArcMap: About symbolizing layers to reflect a heat
map layer utilizing the Density toolset for more detail.
2.6.1 Kernel density
The Kernel Density instrument measures the number of characteristics
around certain features in a neighbourhood. This could be measured for
features on both points and lines. Possible applications include assessing
population density or planning community violations, or investigating how
wildlife habitat impact roads or power lines. The field of population may be
utilized to weigh some characteristics more heavily comparison with others,
or to allow one point to reflect many explanations. A divided highway could
have more effect for line features than a narrow dirt path, (Silverman, 1986.)

21
2.6.2 Formulations for Kernel Density calculating (KDE)
The following formulations describe how to measure the kernel density for
points, and how to assess the default seek radius in the formulation of
kernel density.
∫(x, y) =
1
nh2
∑ k
n
i=1
(
di
h
) (1)
Where:
fi(xi, y) redisplays the density predicted at the point (xi, y);
k: is the kernel function,
n: is the number of the observation,
The distance between (xi, y) point and the (i remark) point is called (di),
and
h: is the kernel size or bandwidth.
2.6.3 Line density
The line density function tests the linear character density within the
neighborhood of any output raster cell. The density shall be expressed in
units’ length/ unit area. Functionally, a circle is drawn around the middle of
the raster cells using the Quest radius. The position in the Inhabitants sector
defines the portion length of every line falling within the ring. These
numbers are rounded up, and the number is divided by circle size.

22
Lines L1 and L2 are the length of the portion of every line falling within
the circle. The corresponding field values for population are V1 and V2.
2.6.4 Point density Estimation (PDE)
The Point Density device tests the characteristics of point density around
every raster output circuit. Themically, unit distress is defined around every
center of the raster cell, and the unit area sums and divides the number of
points within the units. An equation below [Silverman B W 1986] calculates
the predicted density at a new location (x, y):
Density=
1
(radius)2
∑ .
n
i=0 [
3
π
. popi (1 − (
disti
radius
)
2
) ^2] (2)
Whereas:
• i = 1,…,n are the points of input. Involve points in the sum only if they
are within the position radius distance (x, y).
• popi: is the inhabitant's field point I value that is an optional parameter.
• disti: is the distance between the point (i) and the (x, y) position.
The distinction between the methods for line density and point density is that
first and second point features are introduced, and second dimensional
features. The two calculate the sum that the PCI sector specifies, which falls
within the defined segment, divides the sum by the region of the device. The
variance between the output of these two tools and that of the Kernel Density
is that a segment is specified in the density of point and line, which measures
the density of segment around of cell. The kernel density extends the known
amount of distress at every point-out from the point position. The resulting
surfaces at every kernel density point are depending on a quadratic formula
with maximum value in the center of the surface (point position) and at the
distance of the search radius tapering to zero. For every output cell, the total

23
number of cumulated intersegments of the individual distributed surfaces
will be determined. For this study, point density is used as it requires weights,
which is defined by the value of PCI for and defect within the device, which
gives high accuracy for drawing the heat map, as well as the kernel density
mainly concerned with traffic studies and events.
2.7 Interpolation Methods
The Spatial Analyst extension applies one of many interpolation
methods to build a surface grid in ArcGIS. Interpolation is a method used to
estimate cell values in positions where sampled points are missing. This is
depending on the spatial autocorrelation or spatial dependency theory that
tests the relationship / dependency degree between close and distant objects.
Spatial auto-correlation describes how meanings interrelate with one
another. When magnitudes are interconnected it may determine if there is a
spatial trend. This connection is used to measure I Subject similarity within
area I. The degree to which a spatial effect is associated with itself in the
degree of interdependence between variables I Evolution and the level of
interdependence will almost certainly yield opposite findings (Colin Childs,
2004).
2.7.1 Inverse Distance Weighted (IDW)
When the range of points is large sufficient, the IDW function must be
utilized to capture the local surface variance degree required for analyzation.
IDW measures the cell values using a constant weighted set of combinations
of sampling points. The allocated weight is a distance function between an
input point and the output cell location. The distance, the less impact the
output value has on the cell. Using variables from identical measured
locations (PCI value), an approximate value for unsampled places is
determined by the IDW process. The weights are comparable to the

24
similarity of the sample points to the unsampled location, and the IDW
power coefficients could be established. The higher the power multiplier,
the higher the weight of the neighboring points gleaned from the following
equation, calculating the value z at the unsampled location j:
Zi =
∑ Zi
dj
n
⁄
i
∑ 1
dj
n
⁄
i
(3)
Figure (2.5) Screen for Inverse Distance Weighted (IDW)
2.7.2 Applying Spatial Analysis in Managing Pavement
The technologies of Spatial analysis are valuable alternative resources for
PMMS since pavement and asset systems of managing are assisted by
collecting a vast amount of knowledge, accessible in a widespread variety of
media, formats, and referencing systems (Flintsch and Chen, 2007). The
app helps in analyzing many operational and planning issues on managing
pavement including format, time, and size, while enhancing the estimation,
tracking, monitoring, and modeling of spatial phenomena (Miles and ho,

25
1999); this technology has the capability to incorporate, store and query
spatially-referenced data effectively to support several specific decision
processes.
Goodchild & Longley (1999) describes this as a set of appropriate spatial
data methods. These incorporate manipulations, transformations, and other
methods showing the less apparent trends and anomalies that could improve
and help prioritization decisions on road pavement. Such data shape
geographic feature that are Referred to in analog or readable digital formats
by positions and attributes (OMB, 2010). Spatial analysis makes user
questions, maps, generates and analyzes cell-based raster data, and performs
extensive the analysis of vector or raster.
Applications in this dimension enable data integration that may be a
background or inventory of traffic and Rehabilitation and Maintenance
(R&M), data collection that involves gap identification processing inter alia,
and performance display like mean pavement quality. Their roles are
comprehensive in order to be able to use even weather knowledge for
establishing pavement models of efficiency or applying land use policy and
traffic forecasts to provincial planning models (Flintsch et al., 2004).
A spatial instrument is designed to support spatially-referenced data
collection, manipulation, analysis, modeling, and display thru a network of
business processes, organizations, staff, computer software and hardware. It
is primarily used for the resolution of systematic management and planning
problems (Lewis & Sutton, 1993).
An important apprehension in the creation and application of spatial
supported Systems of Pavement Management Maintenance (PMMS) tools
(AASHTO, 2001) is the correct selection of spatial resources, the select of
the a proper base-map and correlation of these characteristics in cartographic
and spatial details.

26
2.8 Pavement Distresses
The word pavement distress applies, in terms of its general appearance, to
the state of a pavement surface. A level that has a continuous that unbroken
surface is an ideal pavement. A distressed pavement may also crack, distort,
or disintegrate in distinction. Both anxiety groups could be sub-divided
further. For example, fracture could be seen as cracks or spalling (paved
pavement surface chipping). In certain cases, the opposite sort may cause
one kind of failure, but there is only one kind of failure to a large extent.
Functional failure depends entirely on the degree of ruggedness of the soil.
Even due to fatigue, consolidation or shear, structural failure in a very
flexible pavement occurs within the subgrade, sub-level, base course or
surface (Garber, & Hoel, 1997).
Accordingly, the current study considers the state and results of Flexible
pavement alone; it does not seem to be thought of the distresses in rigid
pavement. Pavement distresses area unit divided into two entirely separate
groups the main is defined as functional failure. In this situation, the
pavement is not performing its supposed activity without either causing
passenger pain or high vehicle tension. The second, known as foundation
failure, involves a collapse of the pavement system or a deterioration of one
or more segments of the pavement of such severity that the pavement is
unable to maintain the hundreds of pavement that are mandatory on its
surface (Smith, et al., 1979).
2.8.1 Flexible Pavement Distresses
Pavement distress is caused by varied factors or a mixture of factors as well
as insufficiency structural capability, poor style, inferior material quality
(Kaloush; Sousa, et al., 2006), poor construction methods and/or
insufficiency preventive maintenance (Al-Mansour and Al-Mubaraky,

27
2007). The five main types of traditional surface disturbance asphalt
pavement are:
• Cracking
• Deformation of Surface
• Disintegration
• Faults of the Surface
• Other
1- Cracking
The furthermost popular kinds of cracks are: (1) cracks of Alligator (cracks
of Fatigue), (2) Longitudinal and crosswise cracks, (3) Block cracks, (4)
Slippage cracks, (5) Joint reflective cracks, and (6) Edge cracks.
2. Deformation of Surface
Deformation of the pavement is that the results of weakness in one or many
layers of the pavement have fully fledged movement when it is constructed.
It could also be the deformation during cracking. Surface distortions can
present a hazard for traffic. Basic surface deformation styles include: (1)
Corrugations (2) Rutting (3) Swell (4) Shoving (5) Depressions (6) Bumps
and Sags.
3. Unraveling
The gradual breaking up of the pavement into tiny, loose pieces is called
disintegration. If the disintegration is not fixed in its early stages, full
pavement reconstruction may be needed as well. The two most common
disintegration styles are: (1) potholes, (2) fixation, and fixing of the utility
cut.
4. Faults of the Surface
Surface defects are associated with issues within the layers of the surface.
The furthermost common of the surface distress styles are: (1) sprucing.
(2) Bleeding, and (3) Raveling and weathering

28
5. Other Lane /shoulder drop off.
Table (2.1) PAVER Software Classification Distress for Flexible Pavement
highways and Parking (Shahin, 2005; Yoder and Witczak, 1975).
Table (2.1) lists all doable kinds of distress or failure in versatile pavements
and indicates whether or not they are structural or practical failures and cause
(load, elimate, or other) IKulkarni, and Miller, 2003, Adlinge, and Gupta,
2015.
2.8.2 Assessment of Pavement Distress
Pavement analysis is that the initiative within the method of developing
pavement maintenance alternatives as a result of it's necessary to spot the
condition of the defective pavement phase before assessing every
maintenance alternative. Paving situation and performance area unit topic of
central concern in pavement management as a result of most pavement
designers and maintenance personnel should take into account paving

29
situation in their activities [Haas, and Hudson, 1978]. Pavement state
surveys have an important function in maintaining a network of pavements.
The pavement state survey offers the most reliable data for roadway
performance evaluation and is critical in forecasting pavement efficiency,
assessing rehabilitation and maintenance requirements, identifying potential
for rehabilitation and maintenance, and allocating funding [Timm, David
and McQueen, 2004]. The following articles pavement strategies and
completely various equipment utilized for paving situation surveys:
2.8.2.1 Detailed Manual Inspection:
A number of cautious analysis techniques can be achieved in accordance
with the following (Hoque, 2006): United States PAVER technique. Army
civil engineering and construction Research Laboratory (APWARF, 1983;
Shahin, and Kohn, 1984; Shahin, and Walther, 1990) COPES methodology
developed during the National Cooperative Road Analysis Program Study
(Darter, et al., 1985) U.S.-LTPP Distress Survey Methodology developed for
collecting pavement distress data from LTPP sites (Miller and Bellinger,
2003). Methodology by the Ontario Ministry of Transportation (Chong,
Phang, et al, 1989a; 1989b) covers four different types of pavements.
2.8.2.2 Windshield Survey:
A video survey is done by driving on the highway or on the highway's slope.
A rater grades the pavement through the vehicle's panel. This approach
allows for a greater amount of reporting in less time; however, the pavement
pain information quality is being undermined. This technique or surveys may
also be used (Timm, David and McQueen, 2004) would possibly be tested
as a whole network victimization.

30
2.8.2.3 Automated Distress Survey Techniques
There square measure various ways and instrumentation on the market
within the market move from optical device sensors high-speed contact-less
to devices footage of pictures of the surfaces of pavement. Whereas it's
attainable to analyze distress instantly knowledge composed exploitation
optical device sensors, knowledge composed exploitation footage of pictures
square measure typically post-processed within the workplace (Hoque,
2006).
2.8.2.4 Other Approaches
Other ways of post- distress processing information are wide utilized. These
approaches image processing technique, videotaping technique, and embody
photo-logging technique (Hoque, 2006).
2.9 Index Condition of Pavement
PCI is one among the foremost wide utilized pavements measurements for
performance, it utilizes as a sign of the paving situation (Susan, et. al, 2004).
The PCI is an analysis technique that's determined in accordance with
procedures contained (ASTM D6433, 2011), standard test methodology for
PCI Survey. This procedure is employed worldwide to supply an activity of
the pavements condition taking into consideration the useful performance
with implications of structural performance. Periodic PCI determinations on
constant pavement could demonstrate the modification in performance level
with time. As a result of the PCI.

31
Table (2.2) Description for Paving situation Level (ASTM D6433,
2011).
Paving situation
Index (PCI) Range
Condition
description
Percentage
of Network
Legend
86-100 Good 45.52%
71-85 Satisfactory 34.35%
56-70 Fail 12.93%
41-55 Poor 4.84%
26-40 Very Poor 1.85%
11-25 Serious 0.44%
0-10 Failed 0.07%
Total 100%
Procedure is designed to be objective and repeatable, it may also be
accustomed predict condition, The condition ranges from a PCI of zero
"Failed" to a hundred Good", with an "Good" situation such as the pavement
at the start of its life cycle, and a "Failed" condition representing a badly
deteriorated pavement with just about no remaining life. Table (2.2)
demonstrates the overall description for every pevement condition [ASTM
D 6433, 2011]. [United States Engineers Army Corps, 2003] describes the
PCI by default PAVER condition index. A numerical index, beginning at
zero for poor paving to one hundred in decent shape for a pavement. PCI
measurement depends on the findings of a noticeable condition survey
during which the form, intensity, and volume of distress are identified. It had
been built to gives steadiness for the structural pavement index and state of
surface activity. Shahin, (1982) demonstrates that the definition of distress
will involve three parameters: form of distress, frequency and quantity. The

32
weakness of every of these criteria will unite a definition of unrepeatable and
contradictory discomfort. These points are then added up and removed from
upper limit to qualify for an overall assessment of the structural state of a
pavement. The formulas which define the process to integrate an exact
distress to an indication from severity and degree, or the score differs from
case to case and may be very complex (Deighton, 1998).
2.10 Micro PAVER and PAVER
PAVER and MicroPAVER square measure built to create engineers with a
comprehensive method to determining demands for repair and
reconstruction, and pavement managing goals (Shahin and Walther 1990).
PAVER is the mainframe version while MicroPAVER is operating on a
wireless device. The PAVER is designed to maximize the usage of funds
provided for repairing and rehabilitating pavements. MicroPAVER is used
for the maintenance of roads, parks, parking heaps, and surface services. The
PAVER organization is based on the assessment and evaluation method
Paving Condition Index (PCI). The program often includes information
organization inside the network inventory to conduct network and project
analysis Project research provides consumers with careful existing pavement
state survey results, feasible repair and restoration alternatives. This is used
for the display year, so it needs to remain close term. Network modeling used
for planned long-term repairs and reconstruction would provide users with
long-term state of roads, expenditure coming up and project goals. The
PAVER program is written in FORTRAN and C languages and design to
operate on a 1BM or INorlela compliant Japtop machine, et al., 2009a).
2.10.1 Determination PCI by PAVER 6 &5.7 Software
To determine pavement quality, the PAVER program is capable of
conducting pavement quality analyzing, the appropriate network / branch /

33
segment should be checked and pavement segments inspection details could
well be used to approximate pavement status index (Obead, 2012). PAVER
resource control is depend on a system with hierarchical data of networks’
composed, divisions and units, with the group being the lowest segment
handled. This system helps consumers to arrange their inventory simply by
having specific areas and standards for storing pavement details. To add
analysis detail, first check that the selected product object window selects
the correct network/branch/segment, prompt the consumer to enter a
sampling description and move the sample sort between Extra (A) and
Random (R). Through selecting the form of distress and the required degree
of distress, the customer is prepared to insert specific distresses within every
sample item, so that the volume of distress is entered. The related degree
assessment results window enables the individual to analyze the status of a
particular segment directly after entering distress details by selecting the
measurement criteria in the inspection details input window. The
characteristics of the segment are demonstrated above the window. The price
condition, inspection time, and index of condition are demonstrated within
the middle of the screen. This window contains the fundamental details
regarding the segment being displayed together: indexes of condition,
specimen distress, specimen states, segment measurement distresses (United
States Engineers Army Corps, 2011). The PCI is measured with every
checked sample item, the PCI could not be determined for the whole
pavement segment until the sample unit PCI is scheduled.
Deduct values verify the PCI calculation and factors ought to be weighted
from zero to one hundred to point the impact on pavement conditions by
every distress As a symbol, deducting price of (100) implies that there's
extremely serious distress poignant the structural integrity of pavement
and/or surface operational conditions whereas deducting price of (0) implies

34
that there's no result of distress. The PCI will then be calculated utilizing
either a computer code program (utilizing PAVER System) or by hand
supported well established formulas (Shahin, 2005). PAVER gives
operators with the power to modify the rating classes of PCI situation as
demonstrate in Figure (2.10)
Figure (2.6) Pavement Condition Index (PCI) Ranges (U.S Army Corps of
Engineers, 2012).

Chapter Three Methodology And Data Collection
35
CHAPTER THREE
METHODOLOGY AND DATA COLLECTION
3.1. Introduction to the city of AL-Hilla
Al-Hillah is an Iraqi city and the center of Babil Province, with a
population of 455,700 people, according to the (2018) census. It was built
by Sadaqah Bin Mansour, Emir of the Emirate of Bani Mazyad in the year
1101AD. Away from Baghdad is about 100 km, and from Najaf is about
60 km as shown in Figure (3.1). It is also located near the ancient city of
Babylon, which is one of the most important ancient historical regions in
the world.
Figure (3.1) Location of Hilla City from Iraq.

36
3.2. General
This chapter presents the description of research methodology, the
investigation area, the methods utilized for data collection, dividing the
network into manageable units and, all other data necessary to determine
PCI for units and sections. Moreover, the data needed to determine how to
link the PCI values with the GIS program are collected to extract a thermal
map shows the severity of the defect of a road on the GIS map. This will
serve for the purpose of predicting future maintenance of the roads
according to the road priority in terms of the amount of damage. Both
programs are used to create a relation between pavement condition and heat
color map. The subsequent Table (3.1) shows a brief explanation.
Table (3.1) Brief explanation of the study.
Performance Measure Performance Index Software used
Pavement Condition Pavement Condition Index
(PCI)
PAVER
Spatial analysis Heat map
)colors are included)
GIS
3.3. Methodology of the Study
The research methodology presented in Fig. (3-2), shows the steps
of: the road network selection, pavement network division into branch and
section, data collection for each of PAVER software (type of distress,
diminution and severity) by using measurement tools and GPS. Data were
collected X and Y for each road unit of the sites under study to include in
GIS thermal mapping software in gradients according to the location of the
defect. The spatial analysis tool was used in the GIS program, the types of
which were mentioned in the second chapter (kernel density, line density,

37
point density) where the point density tool was used. We also used the
Interpolation tool, specifically the Inverse Distance Weighted (IDW) tool.
3.3.1 Point density Estimation (PDE)
The point density device measures the point density characteristics
around every raster output unit. Thematically, unit distress is specified
around each middle of the raster cell, and the points' number within the units
is summed and separated by the unit area. Then calculating the expected
density at (x, y), which considered as a new location using the following
formula [Silverman B.W. 1986]:
Density=
1
(𝑟𝑎𝑑𝑖𝑢𝑠)2
∑ .
𝑛
𝑖=0 [
3
𝜋
. 𝑝𝑜𝑝𝑖 (1 − (
𝑑𝑖𝑠𝑡𝑖
𝑟𝑎𝑑𝑖𝑢𝑠
)
2
) ^2]
Whereas:
i = 1,…, n are the input’s points. Points are not included in the total
unless they are within the distance of location radius (x, y).
The point (I) field value for inhabitant that is a probability parameter
is (popi)
The distance between the location (x, y) and point (i) is (Disti)
The distinction between the Line Density and Point Density methods
is that point features are added first and linear features second. The two
measure the amount defined by the PCI sector, which falls within the
segment described, separate that amount by the unit area. The difference
between the output of these two tools and that of Kernel Density is that a
section is defined in point and line density, which calculates the section
density around each output cell. At every point out from the point position,

38
the kernel density extends the known volume of distress. The resultant
surfaces at every kernel density point are centered on a quadratic formula
with maximum value in the surface center (the position of the point) and
tapering to zero at the distance of the quest radius. The cumulative number
of the cumulated intersections of the individual distributed surfaces is
determined for every output cell. The point density is used in this research
because it needs weights, which is represented by the value of PCI for each
defect within the unit, which gives high accuracy in drawing the heat map,
as well as the kernel density concerned with traffic studies and events
mostly.
3.2.1. Inverse Distance Weighted (IDW)
Utilizing variables from similar measured positions (PCI value), the
IDW method calculates an estimated value for unsampled places. The
weights are comparable to the similarity of the points of the sample to the
position of unsampled, and the power coefficients of the IDW could be
defined. The greater the power multiplier, the greater the weight of
neighboring points as gleaned from the following equation, which
calculates the value z at an unsampled position j:
𝑍𝑖 =
∑
𝑍𝑖
𝑑𝑗
𝑛
⁄
𝑖
∑ 1
𝑑𝑗
𝑛
⁄
𝑖

39
3.4. Study Area Description
This investigation involved three intersections located in the center
of Hilla, Babylon, Iraq, which mainly distributed in Al-Thawra intersection,
Bab- AL Hussain-40st (near to AL-Kahraba office street), and Bab- AL
Hussain (TAJNED) as demonstrated in Figure (3-3). The area of study is
considered a strategic location in center of al Hilla city. Each of the three
intersections that were mentioned in the study area was drawn and defined
using (GIS) and as shown in Figure (3-4). The intersection region
represented by the intersection body was taken, and a distance of (100 m)
for each intersection approach was taken for spatial analysis after it was
divided into units.

40
Figure (3-2) Research Methodology.
Pavement network division
to branches and sections.
Collect data using
measurement tool and GPS.
Data storage in Excel
Sheet.
Using GIS (ArcMap 10.7.1) to
put (X, Y) for unit
Put data of distress
table
Network Selection
Evaluate PCI for each section
and Link with GIS
Heat map
Drawing heat map
By (point density)
tool
Drawing heat map
By (IDW) tool

41
Figure (3-3) Location of Study Area and Sites.

42
Figure (3-4): The Studied Intersections Using (GIS)
3.4.1.Bab Al-Hussein Intersection
It is a three-legged intersection with three approaches, which is a very
important and vital intersection located within a commercial area. As the
southern side of it leads to the intersection of Street 40, the eastern side
leads to the AL Ray street and the western side connects the Sawob alkabir
to the Sawob Al-saghir through a bridge.

43
Figure (3-5) GIS Map for the Selected Bab Al-Hussein Intersection.
3.4.2.The Intersection of Al-Thawra.
It was a 4 intersections legged with four approaches, in addition to a
central bridge, which is a very important and vital intersection located
within a commercial area. As the northern suburb of it connects the city of
Hilla with a road leading to the governorate of Baghdad, while the southern
side leads to 60 Street, the western side leads to Karbala governorate and
the eastern side to the city centre.

44
Figure (3-6) GIS Map for the Selected Al-Thawra Intersection.
3.4.3.The 40-St. Intersection
It is a four-legged intersection with four approaches, three of which
have a light signal. The fourth approach, which is located next to the
Babylon electrical circuit, does not contain a light signal. This intersection
is an important and arterial intersection as it connects the city centre to the
important streets in it (Street 40, Street 60) and is located within a
commercial area. As the southern tip of it leads to the intersection of the
revolution and the northern side leads to the intersection of Bab Al-Hussein
(AL Tajned), while the eastern side leads to Street 40 and the western side
leads to Corniche Street.

45
Figure (3-7) GIS Map for the Selected 40-St.Intersections.
3.5. Data Collection
The Index of pavement Case (PCI) is an un-complex,
inexpensive and convenient method of measuring to evaluate road surface
situation, recognize rehabilitation and maintenance requirements and
ensure that budgets for maintaining roads are wisely spent. To accurately
determine PCI, the road network must be split into measurable sections.
Data required for the estimation of PCI are listed and explained as
follows:
• Geometric Data.
• Dividing the network into manageable units.
• Inspection data used in PAVER software.
• Inspection data used in GPS software.

46
3.5.1.The Data of Geometry
The data of geometry were obtained utilizing field measurements are
done for geometric characteristics of intersection, length of each approach,
approach width, inner intersection length and width (internal intersection
area) and median width. Also, other characteristics, which is not easy to be
calculated in field are gained like section length. Field survey is utilized to
acquire spatial properties which could not be derived from the satellite
picture since there is no change. Most of the streets geometric layouts are
unavailable in Hilla municipality. The major geometric characteristics of
investigation are illustrated in Table (3.2).
Table (3.2) The Intersections’ Geometrical Data.
Intersection
name
Approach
Width
of
entry
(We)
Lanes’
Number
of Entry
(Ne)
Exit
Width
Central intersection
Length Width
Median
Width
(m) No. (m) (m) (m) (m)
Al-Thawra S
15 4 15 50 40 6
W
20 4 20 2
N
15 4 15 6
E
20 4 20 2
40-St. S
8 3 8 44 31.5 6
W
6 2 6 5
N
10.5 3 10.5 2
E
10 3 10 3
S
10.5 3 10.5 50 38 2

47
Bab Al-
Hussein
W
13 4 9.5 3
13 4 - 3
E
12 4 12 ---
3.5.2.Dividing the Network into Manageable Units
It requires to be split into branches which can be taken as city streets
for managing roadway system. Even though a street does not always have
consistent features, and therefore does not necessarily involve the same
remediation of rehabilitation and maintenance during its total duration at
the same time. It is therefore split into smaller manageable pieces (sections)
as illustrated in Figure (3-8).
Figure (3-8) A Specimen Division of Intersection Into Segments.

48
Also it will enable in collecting of data and analyzing effectively
(Shahin, 2005). Pavements section zone with standard design, history of
usage, maintenance and situation (ASTM D6433, 2011). Sections are
described in such a way that the pavement is compatible in terms of
functional and physical features within their boundaries (Shahin, 2005).
Each section of the road must have an actual facts related to it:
• Length, width, and geometry.
• The kind of Pavement- composite, rigid, or flexible.
• Realistic date of building.
• The history of rehabilitation and maintenance.
The Review Team for System of Managing Pavement Guidebook
(1994) pointed out that one of the following features may possibly describe
the confines between two segments:
• Changing traffic lane number.
• A variation in the kind of pavement.
• A sudden variation in traffic volume or forms.
• A variation in drainage features (for example gutter and curb to ditch
part).
• A variation in the structure of pavement (material, thickness, etc.).
• A variation in normal subgrade features.
• Past projects of building (various projects involve specific designs,
years of construction, materials, and other variables).
Furthermore, geographical or manmade borders can offer or compel
borders to segments like railway crossings, county lines, limits of town or
city, bridges, streams or rivers, road intersections and existing conditions
depending on the last PCI.

49
The section of pavement should be separated into specimen units.
The specimen unit of asphalt surfaced roads is described (2500 𝑓𝑡2
)±1000
or (225𝑚2
) ± 90 as an area, and these units need to be investigated selected
as describe in (Shahin, 2005; ASTM D6433, 2011). Table (3-3) show
number of specimen unit for each approach. A plan of specimen for PAVER
software is utilized so as a rationally accurate PCI can be assessed depended
on studying of a selected specimen units’ number in the segment of
pavement.
For example the pavement divided into specimen unite to
ALThawra intersection south approach:
Length unit =
225
15
= 15 𝑚
Number of unit=
100
15
= 6.7 ≈ 7 𝑢𝑛𝑖𝑡 (for inflow approach &outflow
approach)
N=number of all specimen unit.
S= standard’s PCI deviation (assume ten)
e= Suitable error in PCI prediction (e was fixed = 5) curve of fig.
shahin book. Fig. (3-9)

50
Figure (3-9) Choose lowest Specimen Unit Number. (From Shahin et al. 1976-84)
𝑛 =
7 ∗ 102
(52 4
⁄ )(7 − 1) + 102
= 5
=
𝑁
𝑛
=
7
5
= 1.4 ≈ 1
Figure (3-10) Divided sample units of ALThawra intersection at SB.
15 m
100 m

51
Table (3.3) Number of Sample Unit for Each Approach.
Intersection
name
Approach
N n Central
intersection
No. No. N n
Al-Thawra S 7 5
9 6
W 9 6
N 7 5
E 9 6
40St. S 4 4
6 5
W 5 5
N 4 4
E 5 5
Bab Al-Hussein S 5 5
9 6
W 5 5
6 5
E 6 5
3.5.3.Data Inspection
Usually, the distress of surface of road pavements is measured utilizing the
PCI. ASTM D6433 (ASTM D6433, 2011) has developed the methodology
for testing the PCI. It is important of noting that ASTM implemented the
PCI as a base for road pavement quality rating. For each manageable unit
in a section of a road, the inspected data includes; type of distresses,
dimension and severity for each unit in the section roads. Appendix (A)
shows the details related to survey for each type of flexible pavement
distress, how taken the dimensions and severity. Table (3.4) shows section
sample of the distresses inspection data in the manageable pavement sample
unit of section (A1) of AL-Thawra Intersection at SB. Fig. (3-11) shows a
sample of failure in different sections in the study area (Al-Thawra
Intersection). The inspection data of all section at the study area are shown
in Appendix (B).

52
Table (3.4) The Inspection Data for Section (A1) of AL-Thawra
Intersection at SB.
No. Unit Code
distress
Type distress Severity Quantity
L M H Width Length
1 11 Patching and till cut √ 10000 c𝑚2
8 Jt. Reflection Cracking √ 1500 cm
3 Block Cracking √ 15000 c𝑚2
2
11 Patching and till cut
patching
√ 200 cm
3 Block Cracking √ 5000 c𝑚2
3
10 Lang and Trans Cracking √ 1500 cm
19 Weathering Raveling √ 100000 c𝑚2
4
patching
√ 10000 c𝑚2
patching
√ 10000 c𝑚2
6 Depression √ 30000 𝑐𝑚2
19 Weathering Raveling √ 200000 c𝑚2
patching
√ 300 cm
The levels of Severity: L, M & H which represent low, medium and high, respectively

53
(a) The Cracks of Alligator.
(b) Rutting Cracking.
(c) Polished Aggregate.
Figure (3-11-1) The Distress Type in Field of Al-Thawra Intersection

54
(d) Raveling.
(e) Transfer cracking.
(f) Block Cracking.

55
(g) Patch.
(h) Join crack.
(i) Edge crack

56
Tools for collecting data will improve and simplify the process of
inspection. For GIS, coordinates were selected to every unit (locations of
end and start) of a spitting began. The units of GPS are utilized to identify
unit locations, but pencil and paper even now work. The assessment steps
utilized to identify PCI shall be as follows:
1- The distress boundary of surface in the pavement sample units has
been calculated as width or length or area and is assessed
depending on kind, seriousness and frequency.
2- Utilizing GPS to pinpoint the location of distresses in the units.
3- Providing a lasting digital photo for every roadway section, which
considered as a record for the situation of the pavement.
3.5.4.Coordinates Data Inspection (Inspection GPS Data)
The receivers of GPS will simultaneously and automatically record the data.
Based on the model of the receiver, most of that data is kept in some
category till it is deliberately overwritten or removed. With an individual
turned on unit chooses a position and stops at a certain position. The
operator of GPS identifies the position as a control point. (We might also
like to cross verify GPS locations for certain reasons by utilizing a data
sheet to manual process record the statically-type data presented for the
location in the receiver of GPS). When recording all selected points the
operator could display the locational point characteristics as associated
obtained points demonstrated in the GPS. Substantial GPS operators would
most of the time like to convert the selected road points and associated
collected information in the GPS to electronic devices or computers in
outputs and formats, which proper to specific requirements like Lat Long,
UTM, comma delimited, shape files (A file created inside the database by a
program (Arc Catalog) for the purpose of entering data and drawing), etc.

57
The GPS data exporting is typically done utilizing commercial or free
software or device-included software to avoid the manual recording of GPS
information into the system requirements. We are using Excel sheet to
upload obtained data by a GPS into ArcGIS, because of the time limitation.
This data was already transformed to UTM coordinates from Latitude /
Longitude. The transformation is considered as an easy step, as explained
below: We will work on displaying GPS data in ArcMap with a GPS
available dataset. The data are recorded as a GPS reference points in the
road, which interpreted technically.
Stage 1: Utilizing spreadsheets, for creating a Table that imported onto
ArcMap. It should be placed the names of columns in the first row,
including “Latitude” and “Longitude” and the subsequent rows should be
data of GPS waypoint. The unit of waypoint should be placed in first
column, while the second and the third columns for the longitude and
latitude, receptively. Entering the data, and ensure that longitude and
latitude are placed in the right columns! As well as, ensure that placing a -
sign before the numbers of longitude! (Western Hemisphere). After that the
file could be saved in the pdf format in your workspace until finishing the
work. (ArcGIS 10.7.1 could be imported from Excel spreadsheets directly
without converting them to a DBF file)
• Opening a Spreadsheet that carry (NYC_UTM.xls) as a file name,
which presence in the c:unexerciseGPSdirectory.
• Column A Given name is "LOC" for position, Latitude in column B
"LAT", "Longitude" is placed in column C "LONG", and PCI value
placed in column D "PCI" Fig. (3-12).

58
Figure (3-12) Using Excel Software to Input X, Y Coordinate for of Al-Thawra
Intersection
Stage 2: Opening the GPS document of ArcMap. mxd, which
presence in the c:unexerciseGPS directory.
• To put in the GPS data, pick "Add XY info" from the menu of
"Tools". Selecting .dbf file, and selecting Add. Make sure you
compare the right columns (latitude and longitude) with the fields Y
and X. Picture. (3–1).

59
Plate (3-1) Add X, Y Data.
Stage 3: a) select Arc map toolbox → Density → point density→. Add
(X, Y), Plate. (3-2)
Plate (3-2) Arc Map Toolbox Screen Point Density.
b) Then select Arc map toolbox → Interpolation → IDW→. Add
point, Plate. (3-3).

60
Plate (3-3) Arc Map Toolbox Screen IDW.
3.6. PAVER Software Capabilities
PAVER Windows Software is a computerized PMS. It is a decision-
making method for designing less-cost repair and maintenance options for
roads and highways, car parks, and airfields. PAVER development platform
provides many essential features (United States Engineers Army Corps,
2014):
1. Inventory of the pavements network.
2. Check the condition of the pavement.
3. Developing of models of degradation of the pavement conditions
(Family curves).
4. Dedication of current and possible condition of pavement (Condition
assessment).
5. The repairing and maintenance (R &M) determination requires and
investigating the consequence of various scenarios of budget
(Planning of Work).
6. The preparation of the project.

61
3.6.1.Inventory and Editing Data Inspected by Utilizing
PAVER
PAVER software has been used to identify repair and maintenance
(R & M) needs and goals and to assess optimum repair period by forecasting
future condition of the pavement (Al-Mestarehi, 2009).
Manual measurement of a PCI for a few specimen units isn't a boring
process. However, the calculations can be time-consuming when the
amount of data produced from a survey is typically very high. Therefore,
calculations will be performed automatically after the distress data has been
inserted into PAVER software and the total PCI to every segment will be
determined and also the analyzed quantities of distress (Shahin, 2005).
PCI and pavement quality rating are determined using the following
steps:
A. The inventory of pavements is expressed in terms of segment,
branch, and network. A segment of pavement is the shortest
segment for a major repair and maintenance (R & M) project to
consider. Main attributes to be included in the segment description
include form of structure, pavement, history of construction,
functional categorization (or traffic) and current condition
(Shahin, 2005). Defining the pavement inventory (network,
branches, and sections) is shown in Plate (3-4) to (3-6).

62
Plate (3-4) Paver Screen for Defining Pavement Inventory (Network).
Plate (3-5) Paver Screen for Defining Pavement Inventory (Branch).

63
Plate (3-6) Paver Screen for Defining Pavement Inventory (Section).
B. Enter the inspect information and dates of samples.
The PAVER software inspection component could be
launched from the PAVER software button bar thru PCI,
utilizing the subsequent Stages:
1. Enter inspection dates via a click on the (edit inspection)
as shown in Plate (3-7).
2. Enter the survey information via a click on the (edit
sample unit) as shown in Plate (3-8).
3. Enter information on distress (Type, Severity, or Quantity)
as shown in plate (3-9).

64
Plate (3-7) PAVER Software Screen for Editing Inspection Dates.
Plate (3-8) PAVER Software Screen for Entering Inspection Dates.

65
Plate (3-9) Entering Inspected Data of Section and Calculating Pavement
Condition.
3.7. Techniques of Rehabilitation and Maintenance
Rehabilitation and Maintenance is what some agencies refer to as
repair and maintenance. The "R" in "R & M" may also be interpreted either
as a repair or a rehabilitation. In this chapter R & M techniques are described
in three categories: major, global and localized. Localized R & M covers
crack sealing and patching; global R & M covers the application of slurry
seals and fog seals; and significant R & M covers recycling and overlays
(Shahin 2005).

66
3.7.1.Defects Categorization with Remediation Types and
Reasons of Defects
The defects categorization (displayed in pictures) with measuring unit,
remediation and reasons is mentioned in following order:-
(1) Cracks:
a. Cracks in (Alligator shape).
b. Cracks in the longitudinal direction.
c. Cracks in the Block.
d. Cracking of the Edge
e. Cracking in Centre part.
(2) Shoving and Rutting:
a. Categorization of Rut.
b. Shove.
(3) Patching and Holes of Pot:
a. Holes of Pot.
b. Repairs and Deterioration of Patch.
1. Categorization of cracks:
(a) Cracks in (Alligator shape):
(i) Over-all Depiction:
Those are the intertwined cracks that mimic an alligator's fur, seen
in photos. These were described as follows:-
a. Set of interlocking cracks.
b. Several sided, sharp angled sides typically the longest edge
less than 1 ft.
c. Primarily appears cracks in the longitudinal direction.

67
(ii) Reasons:-
The explanations for the cracking here seem to be as described:
a. The ageing of the binder or original over loading results in the
binding fragility.
b. Insufficient thickness of pavement or unnecessary surcharge, or both.
c. Lower layers or unstable subgrade, resulting in excessive surface
deflection especially in the tracks of wheels. Due to poor drainage
conditions, saturation may cause difficulties in lower layers or
subgrade of the paving.
(iii) Remediation:-
The remediation of the alligator's cracking is addressed as following:
remediation for all cracks' forms based on whether pavement is extremely
durable or has been or has not been deformed. If the concrete is sturdy it
will fill in cracks with low binder-viscosity. Patching of slurry seals or sand
by bitumen premix could be utilized to fill large walls' cracks. If the breaks
are fine, a fog seal, or an emulsified bitumen or thin cut-back can be
browned onto the gaps and carefully filled with sand to discourage the
traffic from collecting the binder. The alligator's severe cracking in the
wheel's path would cause rutting, and thus the pavement might become
functionally obsolete. Unsound pavements broken will need repair or
reconstruction.
(b)Cracks in the longitudinal direction:
(i) Over-all Depiction:-
Such cracks are come fair parallels to the central roadway line, and
could appear either at the junction between the shoulder and roadway or at
the interface between two concrete lanes.

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