DOI: https://doi.org/10.14256/JCE.1980.2017
Primljen / Received:
9.1.2017.
Ispravljen / Corrected: 6.10.2018.
Prihvaćen / Accepted: 20.2.2019.
Dostupno online / Available online: 10.5.2019.
Građevinar 4/2019
Application of GIS technology in
Pavement Management Systems
Authors:
Professional paper
Martina Zagvozda, Sanja Dimter, Vladimir Moser, Ivana Barišić
Application of GIS technology in Pavement Management Systems
Martina Zagvozda, MCE
University J.J.Strossmayer of Osijek
Faculty of Civil Engineering and Archit. Osijek
mzagvozda@gfos.hr
The Geographic Information System (GIS) is a useful technology for managing spatial
databases, which are the basis of the Pavement Management System. When creating a
pavement management system in GIS, the needs and available resources of individual
road authorities should be considered. This paper describes establishment of a simple
database management system for small city administrations. The database was created
by manual collection of pavement condition data at several unclassified roads in the city
of Osijek. Based on collected data, the system calculates the PSI index and compares
pavement condition.
Key words:
pavement maintenance systems, GIS, road infrastructure management, databases, pavement condition
Stručni rad
Martina Zagvozda, Sanja Dimter, Vladimir Moser, Ivana Barišić
Primjena GIS tehnologije u sustavima održavanja kolnika
Prof. Sanja Dimter, PhD. CE
University J.J.Strossmayer of Osijek
Faculty of Civil Engineering and Archit. Osijek
sdimter@gfos.hr
Geografski informacijski sustav (GIS) korisna je tehnologija za upravljanje prostornim bazama
podataka koje su osnova sustava za upravljanje kolnicima. Pri kreiranju sustava za upravljanje
kolnicima u GIS-u treba uzeti u obzir potrebe i dostupna sredstva pojedine uprave za ceste. U
radu je prikazana uspostava jednostavnog sustava za upravljanje i vođenje baze podataka za
potrebe malih gradskih uprava. Baza podataka stvorena je ručnim prikupljanjem podataka o
stanju kolnika nekoliko nerazvrstanih cesta u gradu Osijeku. Na osnovi prikupljenih podataka
sustav proračunava PSI indeks i uspoređuje stanje kolnika.
Ključne riječi:
sustavi održavanja kolnika, GIS, upravljanje cestovnom infrastrukturom, baze podataka, stanje kolnika
Vladimir Moser, MSc. GE
Fachbericht
University J.J.Strossmayer of Osijek
Martina Zagvozda, Sanja Dimter, Vladimir Moser, Ivana Barišić
Faculty of Civil Engineering and Archit. Osijek
Anwendung der GIS-Technologie in Straßenunterhaltungssystemen
vmoser@gfos.hr
Assist.Prof. Ivana Barišić, PhD. CE
University J.J.Strossmayer of Osijek
Das geografische Informationssystem (GIS) ist eine nützliche Technologie für die
Verwaltung der räumlichen Datenbanken, welche die Grundlage des Systems des
Fahrbahnmanagements bildet. Bei der Entwicklung des Fahrbahnmanagementsystems
im GIS müssen auch die Anforderungen und die Verfügbarkeit der Mittel einzelner
Straßenverwaltungsbehörden berücksichtigt werden. In der Abhandlung werden die
Einrichtung eines einfachen Systems für das Management und die Leitung der Datenbanken
für die Bedürfnisse kleinerer städtischer Behörden. Die Datenbank wurde durch
manuelles Zusammentragen von Daten über den Zustand von Fahrbahnen einiger nicht
kategorisierter Straßen in der Stadt Osijek erstellt. Aufgrund der zusammengetragenen
Daten berechnet das System den PSI Index und vergleicht den Zustand der Fahrbahn.
Faculty of Civil Engineering and Archit. Osijek
ivana@gfos.hr
Schlüsselwörter:
Straßenunterhaltungssysteme, GIS, Straßeninfrastrukturmanagement, Datenbank, Fahrbahnzustand
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Martina Zagvozda, Sanja Dimter, Vladimir Moser, Ivana Barišić
1. Introduction
The systematic pavement management and pavement
maintenance become increasingly important with the advancing
age of pavements and related degradation of pavement, which
is further aggravated by steady increase in traffic load and
infrastructure requirements. An important element in pavement
management and maintenance are financial resources, i.e. how
to optimally allocate limited resources. An efficient management
and maintenance of roads requires systematic and continuous
collection of various road condition data, particularly those
on pavements condition, as well as good management of
databases that are used for storing such information. Spatial
databases are the foundation of the entire public road database.
They are based on GIS technology in which alphanumeric data
are linked to the georeferenced vector spatial data.
The Geographic Information System (GIS) is an informationtechnology database management tool that enables creation,
visualization, query, analysis and interpretation of georeferenced
data. It is unique in its ability to integrate spatial data in the form
of vectors (points, lines, polygons) and grids with alphanumeric
data (attributes). The data visualization capabilities, integrated
logical, mathematical and statistical functions for spatial
analysis, and the use of topography for decision making,
constitute an important advantage of GIS compared to other
database management or map creation tools.
GIS is recognized as a useful technology in many fields of
engineering, and especially in the planning and maintenance
of infrastructure. Given the spatial component of the road
infrastructure data, GIS offers an ideal solution for maintaining
a road database, which is a basis for decision making and
pavement management.
This paper provides an overview of
pavement management systems and
their integration with GIS, while also
presenting the possibility of establishing
a simple system for managing and
keeping a road database to meet the
needs of small-size city administrations.
Processes for assessing and comparing
pavement condition are also presented.
largely subjected to financial and time constraints, and so the
purpose of the system is to help infrastructure managers make
decisions, establish priorities, and optimize the overall process.
An efficient Pavement Management System is the one that
maintains all pavements at a sufficient level of serviceability,
that results in low user costs, requires small funds, and does not
create adverse effects for the road safety and environment [2].
The development of these systems began in the late 1960s
when the emphasis shifted from the design and construction of
new road infrastructure to the maintenance and rehabilitation
of existing infrastructure. Initially, those were the systems with
simple capabilities for data processing, evaluation and ranking
of roads based on factors such as pavement or traffic condition.
Today, they enable prediction of future pavement condition,
economic analysis of preventive or subsequent maintenance
activities, creation of long term maintenance plans, optimization
and creation of priorities based on multiple components [3].
The Pavement Management System structure is shown in Figure
1. The system consists of the following components: pavement
condition survey, road network database, quality evaluation tools,
analytical tools and models for predicting pavement properties
and user and agency costs, tools providing assistance in decision
making and implementation processes [4, 5].
Pavement Management Systems (PMS systems) are also
referred to in literature as PMMSs (Pavement Management
Maintenance Systems), i.e. the systems that specialise
exclusively in the management of pavement maintenance [6, 7].
A variant of these systems that can be found in literature are the
so-called Road Information Systems (RIS) [8]. These are unique
road databases that usually contain information on roads in the
jurisdiction of a particular administration, time of construction,
geometry, facilities, drainage, and signs & markings.
2. Road infrastructure
management
The Pavement Management System
(PMS) is described as a set of tools and
methods that help decision-makers find a
cost-effective strategy for assessing and
maintaining pavements in a serviceable
condition [1]. It is a systematic process
of planning, programming, analysis,
construction and research within road
infrastructure. Maintenance planning is
298
Figure 1. Structure of Pavement Management System [4]
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Application of GIS technology in Pavement Management Systems
An essential element in the development of a pavement
management system is the process of data collection and
database creation, since all other system activities are generated
on the basis of these initial activities. Before beginning with
data collection, it is necessary to carefully select the quantity
and the type of data to be collected, the required quality of data
and their level of detail, so as to make sure that the data are
sufficient for decision making, and that they are compliant with
the available equipment and financial resources [9].
The data on pavement condition can be collected manually,
by visual inspection, and/or by measuring equipment, or
automatically by specially equipped vehicles. In manual data
collection, the so-called catalogues of pavement damage
are usually used to allow for proper classification of damage,
and to make the procedure consistent in all circumstances.
The automated data collection is carried out by vehicles
equipped with appropriate devices, such as digital cameras,
global navigation satellite systems (GNSS), gyroscopes, laser
profilographs, and other laser sensors. New technologies, such
as drones or LiDAR, are increasingly being explored and applied
for recording pavement condition [10]. The data collected in an
automated way are fully interpreted and analysed with the help
of computer programs in order to obtain appropriate pavement
condition results, or are processed in a semi-automated
manner in which case trained professionals review the records
in order to detect damage. This type of data collection requires
expensive equipment, but is faster and more efficient.
When creating a road network model, the position of all
collected data should be determined by positioning reference
systems. For many years, the linear reference system (LRS) was
used in transport infrastructure. In this system, the position
of measured data is linked according to its distance from the
known starting point of the linear element (e.g. road axis). The
automation in data collection also implies the shift to a reference
system that is based on geographical coordinates. By using
GNSS, the position of each collected data can be determined
very accurately based on the longitude and latitude data [11].
The data collected to create databases for pavements and other
transport infrastructure facilities include: hierarchy of each road
network segment, position of each road network segment, road
geometry, number and width of traffic lanes, marginal strips and
shoulders, pavement structure data, pavement maintenance
history, average cost of road maintenance and rehabilitation,
and other data (e.g. traffic signalization, drainage).
Decision aid tools are a component of the PMS system. These
decision aid tools can be based on the priority ranking model
or on the system optimization model. When ranking priorities,
the pavement condition data should be combined into a single
index representing pavement quality. After that, pavements are
sorted according to a chosen criterion. After assigning ranking
to a roadway, it is possible to allocate funds intended for its
maintenance and rehabilitation. The ranking and categorization
criteria are usually parameters such as road category and class,
road significance within the road network, traffic intensity,
pavement quality index, etc. Although such models facilitate
GRAĐEVINAR 71 (2019) 4, 297-304
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decision-making, they do not include tools for selecting best
strategies for long-term road maintenance and rehabilitation,
as such tools require the use of more complicated optimization
models. Optimization models are used in an attempt to meet
one or more established objectives in order to create the road
maintenance and rehabilitation strategy of highest possible
efficiency. The objectives are designed to minimize costs
(maintenance and rehabilitation costs, vehicle operating costs),
achieve the best quality pavements within the available annual
funding, and maintain pavement quality as long as possible
after the end of the planned road life cycle. In these models,
pavement data are initial input parameters and the pavement
behaviour model is used to predict future pavement condition.
Various maintenance and rehabilitation actions are used as
variables for optimization, while boundary conditions to be met
during optimisation are available annual funding and minimum
pavement quality requirements [12].
3. Application of GIS for pavement management
and maintenance system
Due to their spatial analysis capabilities, Geographic Information
Systems (GIS) are an ideal tool for improving pavement
maintenance systems because the data they contain are of
geographic nature [7, 11]. In literature, the integration of these
two systems is called either G-PMS or GIS-T (T-transportation)
when traffic data are also included.
Using GIS in such systems enables a prompt response regarding
interconnection of spatial data, geospatial analysis, analysis of
the entire network or its segments, and updating and modifying
the road network and relevant data. The data can be grouped in
a very simple way using colours according to the type of data,
and their attributes or values. In addition, they can be marked by
selecting attributes. Zooming in to the required level of detail is
also available, and maps and presentations can be created. Also,
as to large quantities of data collected by different agencies
or participants in infrastructure maintenance activities, GIS
provides a very significant help in collecting, integrating and
managing these databases [7, 11, 13-15], and the output data
are formed in such a way that they can easily be understood by
management and public stakeholders [16].
3.1. Worldwide application of G-PMS
The idea of improving pavement maintenance systems by
applying the geographic information system has been in use
for a number of years in various forms. Literature provides
examples of how universities apply it for the purpose of
conducting research on a small number of roads, sometimes
at the campuses of these universities [7, 17], or in cooperation
with local road administrations to create a pavement
maintenance system for urban areas [15, 18-20]. In Arizona
and North Carolina, such systems have been created by federal
government in cooperation with universities, and applied in
several districts [13, 21].
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Examples in literature mention numerous GIS software
products for the creation of such systems: ArcView [7, 20, 2224], ArcInfo [19], MapInfo [13, 15], ArcGIS [4, 25], Geomedia
Pro [6], and ESRI MapObjects [14, 26]. Analyses performed
in GIS differ in terms of complexity and range from queries,
pavement condition assessments, total annual maintenance
cost calculations, and long-term maintenance planning. For
example, in paper [22], the criteria used for selecting road
pavement maintenance activities are based on an average
annual daily traffic of 5 000 to 10 000 vehicles, roughness of
up to 4m/km, and the total area under cracks greater than or
equal to 10%. In a GIS-based system, these criteria are easily
applied by creating queries if the attributes containing traffic,
roughness, and cracking data are defined for a given road.
In [2z], the map of pavement maintenance priorities is the
result of attributes of measured pavement roughness IRI as
assigned in GIS. Other papers introduce the pavement condition
assessment index: PSR (Pavement Serviceability Rating) [23,
28], PASER (Pavement Surface Evaluation and Rating) [18], CRS
(Condition Rating Survey) [20], PCI (Pavement Condition Index)
[6, 21, 29], PACES (Pavement Condition Evaluation System) [14],
and PSI (Pavement Serviceability Index) [19, 30]. In addition to
GIS tools, these papers also mention their use in combination
with specialized software products for database creation,
pavement management modelling, or decision-making, such
as MicroPaver [17, 31], HDM-4 [22], GENENTIPAV-D [19],
Visual Basic [26] and some other open source tools, developed
either by individuals or at university level [12, 13, 32]. The most
comprehensive G-PMS system of this kind, presented in paper
[19] for the city of Lisbon, consists of a pavement database,
pavement quality assessment tool, and a decision aid tool
that takes into account the cost of maintenance and available
resources, as well as road user costs.
3.2. Application of GIS in Croatia
In Croatia, GIS technologies are used in the development of
spatial plans, property registers, e-cadastres, and geoportals. A
review of relevant literature also reveals various applications in
timber industry [33, 34] and studies exploring the possibilities
and advantages of its application in construction industry – water
engineering [35, 36] and road and rail infrastructure [37-39].
An overview of a GIS-based pavement maintenance system
operated by Hrvatske ceste (Croatian Roads) is offered in [37].
The system is based on the assessment of pavement condition
by means of recorded properties and traffic and, in the future, it
should serve as a basis for selecting an optimum maintenance
strategy. Due to unsystematic and incomplete transport
infrastructure data in the city of Osijek, a pilot project [38] was
conducted to create a transport infrastructure database in
ArcView software, limited to the strict downtown area of the
city. In [39], the authors used GIS to create a cadastre of walls
and culverts on two county roads.
The requirement of keeping uniform road databases in Croatia
is prescribed by the Roads Act [40]. Road administrations are
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Martina Zagvozda, Sanja Dimter, Vladimir Moser, Ivana Barišić
required to keep such databases, and the manner of doing so is
regulated by the Byelaw on the form, content and manner of keeping
databases on public roads and their facilities [41]. Road database
is defined as a “set of interconnected data providing through
interaction an information on the condition of public roads and
their facilities, integral elements and traffic on those roads, which
are used appropriately and under specified conditions for the
management, construction, maintenance and ensuring safety of
public roads and traffic operated on such roads” [41].
These uniform databases consist of two parts: spatial database
and alphanumeric database. The spatial database contains
georeferenced vector spatial data on the road axis to which
alphanumeric data are linked (road markings, road geometry,
information on pavement type and condition, road facilities,
traffic, etc.). Defined in this way, these uniform databases are
fully consistent with the data defined in GIS; spatial data are
equivalent to georeferenced vectors, and alpha-numeric data
are equivalent to attributes linked to vectors.
While there are some initiatives and research in this area, it can
be noted that the application of GIS for pavement management
in Croatian cities is still insufficient. The survey [42] carried out at
the level of local government units in eastern Croatia shows that
only one out of fourteen surveyed administrations applies GIS for
keeping a pavement database. The main reason for this situation
are limited and insufficient resources that sometimes fail to
cover even the existing pavement damage, which means that the
funding is also lacking for the improvement and modernisation of
the management system for unclassified roads.
4. An example of GIS use for pavement
management in urban areas
Establishing a GIS-based system for keeping a pavement database
does not necessarily require purchase of expensive commercial
software programs. In other words, this lack of resources is no
longer a limiting factor, as an appropriate free software can be used.
In this context, creation of a uniform database in a free GIS software
for several selected streets in the Osijek district of Donji grad is
described below. Although these free software products do not
have the commands specially adapted to pavement management,
their embedded commands and functions still enable easy creation
of a uniform database as defined in the Byelaw [41]. Apart from
the database, the pavement condition assessment based on the
recorded damage, which can be used when making decisions
about maintenance priorities, is also modelled in this example. A
free open source software QGIS was used to show that a digital
GIS pavement database can be established quite rapidly, and that
the database creation and operation requires only the knowledge
of basic software, without connecting it to external tools (SQL, etc.).
4.1. About the QGIS software used
Quantum GIS (QGIS) [43] is an open source software created
in 2002 with the aim of bypassing commercial software and
extending availability of GIS to all personal computers. QGIS
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Application of GIS technology in Pavement Management Systems
provides easy-to-use user interface, supports many raster
and vector data formats, can be upgraded to various additional
connections, and its source code can be customized depending
on particular needs. Although it is not specifically intended for
the use of GIS in traffic infrastructure management, as a free
and widely available software it is one of possible solutions
for managing databases and unclassified roads pavements by
small city administrations. The establishment of such a system
could fully meet the needs of small city administrations given
the limited resources available to them, traffic structure on
their roads, and the requirements set for the infrastructure they
manage.
lot data. The length of the segment was obtained by inquiring
about the length of the mapped road axis vector.
Table 1. Damage attributes
Damage
group
Line damage
Surface damage
- id – number of demage
- id – number of demage
- type of damage
- type of damage
- class of damage
- class of damage
Attributes - length of damage
- surface of damage
- id of street where it is located - id of street where it is located
4.2. System creation technology
Five unclassified roads in the Donji grad district of the city of
Osijek were selected for designing the system in QGIS. These
are smaller access roads with various types of pavement
damage. They are managed by the city of Osijek. The existing
pavement condition was recorded using GNSS, which recorded
the locations of the edge points of each damage. Appropriate
measuring equipment was also used to determine the degree
of damage. Additional activities included photographing and
sketching the damage and filling in a Visual Inspection Form
using the Catalogue of asphalt pavement damage [44].
- converted affected -
- vertical deformation
surface
After that, by inputting the AutoCAD drawing (dwg document)
containing geographic coordinates of the damage based on
GNSS, the damage collected in vector form was digitalized and
divided into two basic groups: line damage and surface damage.
Linear damage includes longitudinal and transverse cracks,
while surface damage includes alligator cracks, potholes,
surface layer removal, depressions, patches, and repairs.
Attributes defined for each group of damage are shown in Table
1. QGIS enables creation of customized drop-down menus (e.g.
a drop-down menu with damage types or damage levels) for
faster and easier digitization of data.
Figure 3. Categorized display of line damage according to type
Figure 2. Form for entering information on road axis attributes
The data digitization was performed by inputting the axes of
individual roads (line elements) based on the GNSS data on
the starting and ending point of the segment. Alphanumerical
data (attributes), which constitute the pavement database,
were linked to the road axes (Figure 2): identification number
(id), street name, segment name, road width, type of surfacing,
road category, number of traffic lanes, traffic data and parking
GRAĐEVINAR 71 (2019) 4, 297-304
A system defined in this way, with the associated attributes, is a
foundation for creating various queries, analyses and statistics.
It enables easy categorization of roads or damage according
to their properties (Figure 3), easy isolation of individual types
and levels of damage, while also facilitating calculation of the
quantity and level of damage of a particular type for each street.
For example, Figure 4 shows creation of a query that isolates
only grade 3 transverse cracks that are located in segment
3, while other damage on this segment, or damage in other
segments, are not displayed. Similarly, a query can be created
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Građevinar 4/2019
about the total number or quantity (length, surface) of damage
for a particular segment or for the entire network of roads under
study.
Martina Zagvozda, Sanja Dimter, Vladimir Moser, Ivana Barišić
(1)
Where: IRI is the longitudinal roughness in mm/km, R is the
medium rutting depth in mm, C is the total surface affected by
longitudinal cracking in m2/100 m2, S is the total surface affected
by surface damage in m2/100 m2, and P is the surface of patches
in m2/100 m2. The expression for the PSI index calculation
was taken from the aforementioned paper [19] in which the
weighting coefficients for individual damage were adjusted to
the needs of the urban road network. It was established that
the impact of longitudinal roughness and rutting on the ultimate
value needs to be reduced in urban areas as, due to lower
speeds and shorter travel distances in urban areas, drivers are
more willing to accept a less comfortable drive.
Table 2. Longitudinal roughness [19]
Level of
damage
Figure 4. Creation of query for selecting grade 3 transverse crucks
situated at segment 3
This database was then upgraded by modelling a process for
calculating the present serviceability index (PSI). QGIS enables
creation of an algorithm that performs the modelled process. In
this case, it is a series of commands that are used for calculating
the total quantity of individual types of damage categorized by
street the damage is related to. Then the pavement condition
index PSI is calculated for each street (Figure 5).
The PSI pavement index was selected for this example because
it is expressed as a mathematical function of the digitized
pavement damage:
Figure 5. Creating process for calculating the PSI pavement index
302
Description of damage
Quantity of
longitudinal
roughness
[mm/km]
S1
User in passenger car does not feel
vibrations
2000
S2
User in passenger car occasionally
feels low level vibrations
3500
S3
User in passenger car feels smaller
vibration on almost the entire segment
or occasionally feels strong vibrations
5500
Longitudinal roughness was not measured due to lack of
equipment, but values were defined according to Table 2
originating from [19]. Considering the street type and traffic
structure, the level of rutting is not pronounced. That is why
this phenomenon was neither registered
nor digitized. However, rutting is still an
integral part of the database and can
subsequently be measured and added
to already measured damage, if it has
to be done in the scope of assessment
of condition on the remainder of the road
network.
After starting the modelled process,
the output information is the new layer
containing PSI indexes of recorded
pavements. Road axes are categorized
based on PSI values and are displayed
in various colours (Figure 6). It can be
seen that three roads are in a very poor
condition with an index between 2 and
2.5, while only one road has an index
greater than 3. These results are in
accordance with the actual pavement
condition. Pavements in Cvjetkova,
Banova and Ciglarska streets contain a
significant quantity of all types of cracks,
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Application of GIS technology in Pavement Management Systems
are exclusively intended for road
infrastructure
management,
their
limiting factor is often the price or
the scope and functions that do not
necessarily correspond to the needs
of a particular road administration.
Various GIS technologies can be applied
for establishing or keeping a road
infrastructure management database.
By using GIS, the system can be fully
adapted to the operation of any road
administration.
In the management of unclassified
roads in Croatia, the application of new
technologies is hampered by inadequate
budget available to local governments.
Figure 6. Display of streets categorized according to calculated PSI index
The solution can be found in the
application of free software products
like QGIS that have proven to be very
successful in this example, even though
the research was based on a small
sample of roads. Existing or newly
collected data can be easily digitized
resulting in a uniform database, and
additional benefits can be obtained by
modelling the process, as demonstrated
in the process for pavement condition
assessment.
Pavement data collection activities
should certainly be encouraged and
expanded to a greater number of
pavements in order to confirm suitability
Figure 7. Photographs of actual pavement condition: a) Cvjetkova Street, b) Lađarska Street
of this database-keeping methodology,
by comparing the actual pavement condition and condition
potholes and other damage, and they would require pavement
assessment as expressed by PSI index on a large number
rehabilitation or more extensive maintenance operations. The
of samples. The slowness of local self-governments in the
northern part of Lađarska Street contains only lower-grade
introduction of new technologies is the result of insufficient
cracks (PSI index 3 – 3.5), while the southern part contains
funding, but is sometimes also due to improper use of resources
potholes resulting from war damage (PSI index 2.5 – 3.0).
[42]. The solution should, therefore, be sought in free tools that
would greatly contribute to the creation of a comprehensive
5. Conclusion
picture of pavement condition, as well as to an easier definition
of maintenance priorities, better allocation of available
GIS tools have great potential in the management of transport
resources, and systematic use of such resources.
infrastructure. Although there are software programs that
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