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Journal of Engineering Science and Technology Vol. 11, No. 5 (2016) 655 - 665 © School of Engineering, Taylor’s University
655
GEOSPATIAL ANALYSIS OF ROAD DISTRESSES AND THE RELATIONSHIP WITH THE SLOPE FACTOR
NOR A. M. NASIR1, KHAIRUL N. A. MAULUD
1,2,*, NUR I.M. YUSOFF
1
1Department of Civil and Structural Engineering,
Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600
Bangi, Selangor, Malaysia 2Earth Observation Center, Institute of Climate Change, Universiti Kebangsaan
Malaysia,43600Bangi, Selangor, Malaysia
*Corresponding Author: [email protected]
Abstract
A road is a medium that a person uses to move from one destination to another. A
good road can provide comfort and safety to users, however, poor maintenance of a road might cause danger to them. Therefore, a road maintenance management
system needs to be carried out to ensure the effectiveness as well as the efficiency
of road maintenance itself. In this era, there are so many systems created in order
to help data storage and analysis. One of the systems is the Geographic
Information System (GIS). Other than getting the location of distresses, GIS also
can help to classify the severity level of distresses and to correlate the distresses
occurring in Universiti Kebangsaan Malaysia (UKM) with the slope gradient.
Road distress data was collected using GPS applications supported by Supersurv 3
software. The study shows that the GIS method helps to produce a good spatial
database. The road gradient factor is related to the level of road damage.
Keywords: Geographic Information System (GIS), Road distress, SuperSurv 3, Road management.
1. Introduction
Maintenance defined by the engineering field as a term referred to a process of
maintaining construction elements in a safe condition can be used for a road
network. On the other hand, for a road network, a Pavement Maintenance
Management System (PMMS) can improve the efficiency of decision-making,
provide feedback on the consequences of decisions, control the rate of
deterioration, and limit maintenance costs [1-4]. A comprehensive, fully
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integrated PMMS is the key to better reconstruction, restoration and maintenance
decision making for pavements [2, 5-6]. Having limited funding, it is necessary to
identify the best road preservation projects that can provide the most benefits to
society in terms of the overall life cycle cost of a road network [7]. Verifying
long-term pavement performance, identifying pavement distress, predicting
pavement temperature and performing cost analysis of each pavement distress are
essential [8].
Since the spatial analysis in GIS can be matched with the geographical nature
of road networks, GIS can be considered as the most appropriate tool to improve
management operations. Nowadays, the use of GIS by local authorities in
pavement management activities is proven to be helpful in resolving problems.
Adding a geographic information system (GIS) to PMMS is a vital step in
supporting and improving decision-making [3, 9]. Spatial technology could
enhance the analysis of related transportation issues and might improve the
quality of the decision making process [10]. GIS is a combination of methods for
collecting, storing, retrieving, transforming and displaying all real spatial data
fora set of specific purposes [11-13].
The objective of this paper is to identify the locations of road distress in
UKM. The coordinates of the location in distress will be marked using GPS
technology. The second objective is to produce spatial data storage of road
distresses by using GIS, and the last objective is to classify the road distresses
into three severity levels and to study the relationship between the road distress
and the slope factor. At the end of this study, spatial data in the form of maps of
the critical area that needs to be maintained will be produced.
2. Methodology
2.1. Research area
The pavement maintenance management system (PMMS) was investigated in the
selected study area in UKM, as shown in Fig.1. The data, such as locations,
distress measurement and photos for the study area, were collected, and the
database was created. By using all the information from the survey, the severity
levels of the distress were identified by using a roadway distress guide. From the
guideline, the road distresses were categorised into three severity levels, which
are low, medium and high, with high being the poor condition and low being the
good condition. The created database was exported and displayed in GIS. The
display shows the locations and also all the information of the distresses.
2.2. SuperSurv
Recently, many researchers have proposed efficient system to collect data for
pavement condition using mobile devices [14-16]. The use of mobile device gives a
quick, easy to use and cost-effective method in road surface monitoring
[17].SuperSurv, as shown in Fig. 2, is a mobile GIS application specially designed
for Android and iOS platforms. Integrating with GIS and GPS technologies,
SuperSurv allows users to easily collect and survey spatial data in the field using
only a mobile phone or tablet device. This application serves as data collection,
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orientation, map display and waypoint guidance. It is an interesting application as
the data collected can be saved in SHP, GEO and KML formats.
Fig. 1. Study Area in UKM.
Fig. 2. Waypoint Data Collection by Using SuperSurv 3.
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2.3. GIS
Since the SuperSurv application collects all the data, GIS software will be the
main tool to analyse all the data and display the data in the form of a map. GIS
allows the user to interpret, question, track and visualize data in ways that will
establish trends, pattern and relationships in the form of maps, reports and charts
[18]. In other words, GIS helps to answer questions and solve problems by
looking at the data, and it is easier for users to comprehend the outcomes.
3. Results and Discussion
3.1. Road distress
Based on the field survey, a total of 185 road distresses were detected. They
consist of 11 types of distress as stated in Table 1. From the table, 51% of the
distresses in UKM were in the high severity level of distress. Thus, more than
50% of the roadways along UKM are in need of maintenance or reconstruction
for the user’s safety. Longitudinal crack sand patches recorded the highest
number of distresses, both recording 40 distresses. Also, both longitudinal cracks
and patches recorded the highest number of distresses with the highest severity
level, 22 and 31 distresses respectively. This shows that about 43% of the
roadway was affected by longitudinal cracks and patches. In addition, if
longitudinal cracks are not going to be maintained soon, this will lead to a high
severity of alligator cracks.
Table 1. Number of Road Distresses in UKM.
Type of Distress Severity Level Total
Low Medium High
Alligator Crack 8 8 5 21
Longitudinal Crack 7 11 22 40
Transverse Crack 4 3 - 7
Edge Crack 1 2 7 10 Block Crack 2 2 1 5
Crescent Crack 4 - - 4
Edge Drop 1 4 2 7
Patch 5 4 31 40
Pothole 2 7 8 17 Delamination 5 2 6 13
Rutting 2 6 13 21
Total 41 49 95 185
A longitudinal crack often happens due to a poorly constructed paving lane
joint or the shrinkage of the asphaltic concrete (AC) surface caused by a low
temperature or hardening of the asphalt [19-21]. Moreover, if a road was
constructed in a hill area, differential settlement between cut and fill during
construction and embankment failure could be factors influencing distress to
occur. Figure 3 shows the locations of longitudinal cracks in UKM. Referring to
the map in Fig. 3, the marked area is the road most affected by longitudinal cracks.
A patch is also one of the most common distresses in UKM. A patch is an area
of pavement that has been replaced with new material to repair the existing
pavement. However, although part of the road is patched, the solution to the
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distress is still unsolved. A study to investigate the factors influencing distresses
needs to be done at the particular area. Figure 4 shows the locations of the patches
in UKM. From Table 1, 31 out of 40 patches are in high severity levels, which is
in poor condition. Thus, they need to be replaced as soon as possible since this
can result in accidents and cause damage to vehicles.
Fig.3. Locations of Longitudinal Crack Distress in UKM.
Fig.4. Locations of Patch Distress in UKM.
3.2. The relationship between distresses and the slope factor
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Furthermore, with the sophistication of GIS technology, slopes on a road can be
identified easily by using the spatial analysis method. By exporting the spatial
data of height into the existing data in GIS, the slope gradient of a roadway can be
obtained easily by analysing the data of the slope. Road distress is commonly
related to runoff on the road surface. As the slope of a road increases, the velocity
of the surface runoff on the road will also be increased, causing the volume of
stagnant water on the road to decrease. Figure 5 shows the graph of distress due to
the gradient of roads. Based on this figure, the highest number of distresses is
detected between slopes 9° and 21° while the least severe distress happens
between slopes 27.1° and 42°. From the figure, the slopes 27.1° to 42° have the
smallest volume of stagnant water due to the high gradient of the slopes, thus
leading to less occurrence of distress.
Fig. 5. Graph of Distresses Due to the Gradient of Roads.
Table 2 shows the road distresses at specific slope gradients based on three
levels of severity.
Table 2. Level of Severity of Distresses Based on the Slope Gradient.
Slope gradient Low Severity Medium Severity High Severity
0–3.0 2 3 9
3.1–6.0 0 2 7
6.1–9.0 9 2 6
9.1–12.0 7 9 15
12.1–15.0 10 11 10
15.1–18.0 5 10 12
18.1–21.0 4 5 18
21.1–24.0 1 2 8
24.1–27.0 1 1 6
27.1–30.0 0 0 1
30.1–33.0 0 2 1
33.1–36.0 1 2 1
36.1–39.0 0 0 0
39.1–42.0 1 0 1
Based on Table 2, the critical slope is identified by Index Number. To
calculate the Index Number for each slope, the number of distresses at each slope
will be multiply with the weightage factors which are 1 for low severity, 3 for
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medium severity and 5 for high severity. Table 3 shows the results of the Index
Number for each slope gradient.
From the analysis, the critical slopes are at 9.1 degree to 12 degree and 18.1
degree to 21 degree since it gives the highest index number, which are 109.
Besides, slope gradient 12.1 degree to 15 degree and 15.1 degree to 18 degree
also give the high index number since both slope records index number more than
90. Therefore, these 4 slopes are very critical in UKM and need to be maintained
perfectly. UKM authorities need to put extra attention and provide some research
at those slope locations. Locations of distress in relation to the critical slope
gradient are shown in Fig. 6.
Table 3. Index Number for Each Slope.
Slope
gradient
(degree)
Low Severity
Weighting Factor = 1
Medium Severity
Weighting Factor = 3
High Severity
Weighting Factor = 5
Index
No.
0–3.0 2 9 45 56
3.1–6.0 0 6 35 41
6.1–9.0 9 6 30 45 9.1–12.0 7 27 75 109
12.1–15.0 10 33 50 93
15.1–18.0 5 30 60 95
18.1–21.0 4 15 90 109
21.1–24.0 1 6 40 47
24.1–27.0 1 3 30 34
27.1–30.0 0 0 5 5
30.1–33.0 0 6 5 11
33.1–36.0 1 6 5 12
36.1–39.0 0 0 0 0
39.1–42.0 1 0 5 6
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Fig. 6. Critical Slopes in UKM.
3.3. Advantages of SuperSurv and GIS software in mapping
SuperSurv 3 is mobile software which can be downloaded from Apple Store or
App Store (android). It comes in two versions which is free version and paid
version. The free version allows users to try the complete functions for 7 days.
The main function of this software includes data collection, orientation and map
display. Along with the GPS-function, the data of point, line and polygon can
all be marked quickly. Besides, users can apply Open Street Map as the base
map to collect spatial data and save the data as SHP files.
GIS is the main tool in mapping the road distresses in this project. Adding
the coordinates of the distresses that were collected, a full map of road distress
was produced. Using the map as a guide, the road authority can identify the
exact location of the distress with ease. Besides, data collected can also be
presented in a table form. The attribute table (Fig. 7) is flexible, and users can
edit it anytime. The map produced by GIS will show the current state of the
road or road distresses based on the latest data updated into the attribute table.
GIS has many functions that can be used to help users during analysis and
decision-making. By using Identify or Hyperlink, all the data of a distress, such
as the dimension and the photo of the distress, will be shown immediately. The
Identify icon is used to identify geographic features, and this can be done by
clicking or dragging a box around it. Meanwhile, Hyperlink is used to launch a
hyperlink to a website, document or script by clicking on the feature. These two
functions of GIS help users to get information quickly. Figures 8 and 9 show
how Identify and Hyperlink function in GIS.
Fig. 7. Attribute Table in GIS.
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Fig. 8. Information Produced by using the Identify Icon.
Fig. 9. Photo of Distress in UKM Linked with the GIS.
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4. Conclusions
A spatial analysis of the locations, severity levels and the gradients of slopes
along the roads in study area were carried out. The combination of the spatial data
and GIS successfully produced maps that show the exact locations of the
distresses in UKM. The maps will upgrade and improve the process of road
maintenance management, from collecting data to making decisions for road
repairs according to priorities.
The system is a collective effort utilising the available technologies of GIS
and its tools. GIS is believed to be the best system of road maintenance
management to be used in the future. GIS is not limited to road management only
and can also be applied to other systems as well. Examples that can be given are
sewage, waste management, water management and piping. In brief, GIS is a
system created to help users to keep, record, analyse and solve problems for the
convenience of users.
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