USING THE ANALYTIC HIERARCHY PROCESS AND GIS FOR DECISION MAKING IN RURAL HIGHWAY ROUTE LOCATION

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International Journal of Civil Engineering and Technology (IJCIET)
Volume 7, Issue 2, March-April 2016, pp. 359–375, Article ID: IJCIET_07_02_032
Available online at
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USING THE ANALYTIC HIERARCHY
PROCESS AND GIS FOR DECISION
MAKING IN RURAL HIGHWAY ROUTE
LOCATION
Ayman A. Abdul-Mawjoud
Assistant Prof., Department of Civil Engineering,
College of Engineering/University of Mosul, Mosul/Iraq
Mohammed G. Jamel
Assistant Lec., Department of Civil Engineering,
College of Engineering/ University of Mosul, Mosul/Iraq
ABSTRACT
Rural highway route location is a very complex case, requiring significant
time and effort from the planners. This study presented the route location
method by applying Analytic Hierarchy Process (AHP) and Geographical
Information System (GIS). The location of the study is confined to south Mosul
city in Iraq of the area (198km2
). The researcher is behind defining the route
which connects Baghdad-Mosul and Mosul-Kirkuk roadways. This route is
considered the suggested turn to Mosul city. A variety of data set from
different sources and at different scales are managed. A questionnaire has
been made with a group of decision makers and specialists in designing and
constructing roadways to point out the relative importance of location criteria
that was done by following pairwise comparison after building a hierarchical
framework to evaluate the criteria. The relative importance is found as
follows: land use (23%), water resources (26%), slope (10%), soil bearing
(10%), environmental impact (5%), hydrology (8%), settlement area (11%)
and linear engineering structure (7%). A basic for sub-criteria weighted
within designed criteria was conducted according to cost and engineering properties.
The study is based on an accurate digital space data of 0.6m to define and
insert the data and locations of these criteria and change it into digital data by
using GIS Program-ArcMap10. It is used as a tool in the hands of decision
makers to determine the Spatial Multi - Criteria Decision Analysis. This
influences the defined route as part of the stages of route design by
formulating the equivalent cost surface to the mentioned criteria. Many maps
and special framework of insertion of data analysis of the adjusted surface
have been used to define the optimal route. It was also conducted to evaluate
this route compared with the shortest possible route and tracks proposed by

Ayman A. Abdul-Mawjoud and Mohammed G. Jamel
the relevant agencies in Mosul city, it was found that the optimal route
reduces valuable cost surface by up to between (21.8% to 63.7%) for the other
tracks. The cost surface is changed to form many alternatives with different
lengths to define Least Cost Route. That is done by economic assessment of the
influential criteria on the suggested routes. A shorter route than the optimal
one is gained with less cost of (2.25%) to reduce the environmental impacts
and travel time and use of GIS to get the rate of criteria in every suggested
route to facilitate the process of decision making.
Key words: Analytical Hierarchy Process (AHP), GIS, Highway route
location, Least cost path, Multi-criteria analysis (MCA), Optimum route,
Pairwise comparisons, Weighted Linear Combination (WLC).
Cite this Article: Ayman A. Abdul-Mawjoud and Mohammed G. Jamel.
Using The Analytic Hierarchy Process and GIS For Decision Making In Rural
Highway Route Location, International Journal of Civil Engineering and
Technology, 7(2), 2016, pp. 359–375.
http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=7&IType=2
1. INTRODUCTION
The process of designing and constructing roads is considered one of the most
complicating problems in creating the balance among the technical, economic and
environmental factors. Moreover, the process of defining the optimum route is part of
the stages which subject to certain location criteria that require a balance among them,
that aims at reducing losses resulting from the loss of natural resources and lessening
the initial survey to define the route.
The Analytic Hierarchical Process (AHP) can be employed as one approaches that
may be applied to find complex decision - making problems containing multiple
scenarios and criteria [1, 2]. Saaty [3] proposed AHP method that has the flexibility
to combine quantitative and qualitative factors to manage different groups of
performers. It uses a multi-level hierarchical configuration of objectives, criteria and
sub-criteria. The relevant data are derived by using a set of pairwise comparisons. The
weights of the importance of the decision criteria are obtained through these
comparisons, a checking for consistency are performed to ensure that the comparisons
are perfectly consistent [4].
Using GIS with Multi - Criteria Analysis (MCA) has helped to improve multi-
criteria decision making combined with planning process [5, 6, 7, 8], and involves the
phases of intelligence, design, and choice [9]. However; GIS has the capability to
conduct data spatially in layers and then overlay these layers to accomplish spatial
land-use suitability analyses.[10]
AIM OF THE STUDY
The main goals of this study are:
1. Finding and planning a highway routes using AHP and GIS technology, considering
the influence of several economic, technical, and ecological factors.
2. Comparing the optimum route with the shortest possible route and tracks proposed by
the relevant agencies in Mosul city.
3. Determination of the least cost route by changing the cost surface to form many
alternatives with different lengths.

Using The Analytic Hierarchy Process
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2. METHODOLOGY
2.1 The Analytic Hierarchy Process
The Analytic Hierarchy Process (AHP) is a compre
expressing and analyzing policy decisions, it was developed by Saaty, Tomas L. in
1960s [11]. It is a mathematical procedure, widely used in decision making in a wide
range of applications. It is a theory of measurement thr
depend on the judgments of
measure impalpable in relative terms. The comparisons are execute using a scale of
absolute assessments that represents, how much more, one elem
with respect to a given attribute and then measure the consistency of the
judgments[12].
The selection of the location of a proposed highway is considered the important
initial step in highway design. The decision to choose an accurate
based on topography, soil characteristics,
the relation between these criteria and the Analytic Hierarchy Process in this study is
shown in Fig. 1.
Figure 1 Analytic Hierarchy Process for
2.2. Weighing of criteria
The pairwise comparison method was presented by Saaty in 1980, it involves pairwise
comparisons to produce a ratio matrix of criteria and to produce relative importance
of each criteria by using Saaty’s weighing scale. Factors are compared against each
other in a pairwise comparison that is a measure of relative importance among the
factors. Thus, numerical values showing the
another. Saaty suggested a scale for comparison including of values ranging from 1 to
9 which represent the intensity of importance, by means of a value of 1 describes
Using The Analytic Hierarchy Process and GIS For Decision Making In Rural Highway
Route Location
CIET/index.asp 361
. METHODOLOGY
2.1 The Analytic Hierarchy Process
The Analytic Hierarchy Process (AHP) is a comprehensive intuitive method for
expressing and analyzing policy decisions, it was developed by Saaty, Tomas L. in
range of applications. It is a theory of measurement through pairwise comparisons and
depend on the judgments of the proficient to derive priority scales, these scales
absolute assessments that represents, how much more, one element command another
initial step in highway design. The decision to choose an accurate location is usually
based on topography, soil characteristics, environmental and economic factors
Analytic Hierarchy Process for evaluation of the criteria in the study
riteria
using Saaty’s weighing scale. Factors are compared against each
numerical values showing the relative importance of a factor against
a scale for comparison including of values ranging from 1 to
9 which represent the intensity of importance, by means of a value of 1 describes
nd GIS For Decision Making In Rural Highway
editor@iaeme.com
hensive intuitive method for
expressing and analyzing policy decisions, it was developed by Saaty, Tomas L. in the
ough pairwise comparisons and
proficient to derive priority scales, these scales
ent command another
location is usually
environmental and economic factors [13],
evaluation of the criteria in the study
using Saaty’s weighing scale. Factors are compared against each
relative importance of a factor against
a scale for comparison including of values ranging from 1 to
9 which represent the intensity of importance, by means of a value of 1 describes the

equal importance and a value of 9 expresses to those factors having an excessive
importance over another [1, 14]. Table (1) shows Saaty’s weighing scale.
Table (1) Scale for pairwise comparison [12]
ExplanationDefinition
Intensity of
Importance
Two activities contribute
equally to the objective
Equal importance1
Experience and judgment
slightly favor one activity over
another
Weak importance of one
over another
3
Experience and judgment
strongly favor one activity
over another
Essential or strong
importance
5
An activity is strongly
favored and its dominance
demonstrated in practice
Demonstrated
importance
7
The evidence favoring one
activity over another is of the
highest possible
order of affirmation
Absolute importance9
When compromise is needed
Intermediate values
between the two
adjacent judgments
2,4,6,8
2.3. The relative importance of the criteria
Assigning importance of the criteria is changed in the range of variation for
evaluation criterion. In the case of n criteria, the weights are usually normalized to
sum to 1. The definition of a set of weights is as follows:
= 1, 2, … , …
= 1 … … … … … … … … … … … … … … 1
A ratio matrix was developed from an individual or group compares every
possible pairing and enters the ratings into a pairwise comparison matrix.Since the
matrix is symmetrical, only the upper or lower triangle really needs to be filled in.
The remaining cells are then simply the reciprocals of the other triangle. The relative
weights of the criteria can be achieved by following the operations:[12, 15, 9]
- Sum the values in each column of the pairwise comparisonmatrix;
= … … … … … … … … … … 2
C11 C12 C13
C21 C22 C23
C31 C32 C33

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Divide each element in the matrix by itscolumn total;
Xij =
∑
… … … … … … … … … … 3
- For each row, divide the sum of normalized scores by the number of criteria to
compute the average of the elements in each row of the matrix; that is,
=
∑
… … … … … … … … … 4
These averages provide an evaluate of the relative weights of the applicable
criteria. At present, the weights are demonstrated as the average of all possible
manners of comparing the criteria. The larger the weight, the more valuable is the
criterion [9]. The degree of consistency should be determined that is used in
developing the ratings.
The Consistency Ratio (CR) describes the probability that criteria weighting were
randomly generated and Saaty[3, 16] suggests that CR should be less than 0.10, which
demonstrates a realistic level of consistency otherwise the ratio is inconsistent.
Saaty[3] describes a procedure by which a Consistency Index (CI) and a consistency
ratio, can be produced as the following:
* =
… … … … … … … … … 5
X11 X12 X13
X21 X22 X23
X31 X32 X33
C11 C12 C13
C21 C22 C23
C31 C32 C33
W11
W21
W31
Cv11
Cv21
Cv31
=
1
+ + ! ! "
=
1
+ + ! ! "
! =
1
!
! + ! + !! ! "

The consistency index provides a measure of deviation from consistency. The
calculation of CI is based on lambda (λ) which is always greater than or equal to the
number of criteria used [15].
ƛ=
∑ #$%
&'(
… … … … … … … … … … … … … … … 6
* =
ƛ −
− 1
… … … … … … … … … … … … … … 7
From Table (2) select the Random Index (RI) depending on the number of criteria.
Table 2 Random Index Values (RI), [3, 4]
987654321No. of Criteria
1.451.411.321.241.120.900.580.000.00Random Index
. =
*
.*
… … … … … … … … … … … … … … … 8
2.4. Sub-criteria identification
For each criteria, a number of sub-criteria was determined according to the study area
and estimated cost for the road construction, the primary comparison for sub-criteria
is for each main criteria.
2.5. Creating a suitability cost surface
After weighting the criteria and creating cost surface concerning the relative
importance of each criterion and also suitability index, all the criterion maps were
overlaid to calculate how suitable each area is to travel through. Finally, suitability
map was managed and the optimum route was determined [1, 17].
This method can be mannered using GIS system having overlay capabilities that
admit the evaluation criterion map layers to be accumulated to determine the
composite map layer.
2.6. Generating the least cost alternatives
After finding the optimum route we can minimize optimal length and path turn to
perform a route straightening by executing changing in cost surface using the
following formula:
01 23451 634 7289:;5 = + <
11 −
11
= × 634 7289:;5 … … … … 9
where, I, is the value of the surface change ranging from 0 for no straightening to
11 for total straightening.
This formula was conducted on the surface cost, by realizing disproportional
raising between the higher and lower values of the cost surface. This accomplished in
reducing the length and secondary angles of the optimal route in the suitable areas
while continuing to avoid unfavorable areas [18]. A re-analyzed using ArcMap10-
program was conducted for finding a recent route location. This shortening and
straightening of the route are valuable because the cost to construct a shorter route is
taken into consideration requirements of engineering perspective. However; a least

Route Location
cost route can be determined with their corresponding (i) value and project the
position in the digital space. Fig. (2) clarify adjusted value against the surface value.
Figure 2 Surface cost alternative curve
3. STUDY AREA
The study area for this research is the area around 198km2
south of Mosul city in Iraq
which includes the extent of latitude between (N4008731-N4021577) and longitude
between (E329630-E345068)according to UTM metric unit. The suggested route
connects Baghdad-Mosul and Mosul-Kirkuk roadways across Tigris river. This route
is considered the suggested turn to Mosul city.
The study area had different land use and different slope grades from flat to
rugged terrain, Fig. (3) shows the area percentages of land use within the study area.
Figure 3 Land use of study area
The origin of the route is on Mosul-Baghdad roadway near Hamam-Alallel
crossing while the destination is demonstrated by a line of 3392m length on Mosul-
Kirkuk roadway which presents the destinations of the three proposed routes
suggested by the relevant agencies in Mosul city. Fig. (4) shows the study area and
the three proposed routes.

Ayman A. Abdul
http://www.iaeme.com/IJCI
Figure 4 Study area with
4. CRITERIA EVALUATI
The relative importance of location criteria was conducted after analyzing a
questionnaire form from a group of decision makers and specialists in designing and
constructing roadways. After forming a comparison matrix
(ƛ) was calculated and if a consistency ratio for this calculation is less than 0.1 lamdia
(ƛ) enter in the evaluation, otherwise canceled. A total of 38 comparison matrices was
conducted from the approved questionnaire form wi
decision 89.5%. The relative
shown from the figure that the highest relative importance is for water
followed by land use while the lowest relative importance is
impact.
Figure
Environ
5%
Hydrolog
y
8%
Settleme
nt Area
11%
CIET/index.asp 366
with the origin and destination points of the three proposed routes
4. CRITERIA EVALUATION
constructing roadways. After forming a comparison matrix for each specialist, lamdia
) was calculated and if a consistency ratio for this calculation is less than 0.1 lamdia
) enter in the evaluation, otherwise canceled. A total of 38 comparison matrices was
conducted from the approved questionnaire form with the percentage of right
decision 89.5%. The relative importance of the criteria was shown in Fig
shown from the figure that the highest relative importance is for water
while the lowest relative importance is for environmental
Figure 5 Relative importance for the criteria
Landuse
23%
Water
Source
26%
Slope
10%
Soil
Bearing
10%
Environ
5%
Hydrolog
y
8%
Settleme
L.E.S
7%
editor@iaeme.com
oposed routes
for each specialist, lamdia
) was calculated and if a consistency ratio for this calculation is less than 0.1 lamdia
) enter in the evaluation, otherwise canceled. A total of 38 comparison matrices was
percentage of right
shown in Fig. (5). It is
shown from the figure that the highest relative importance is for water resources
for environmental

Route Location
4.1. Set of criteria map
A digital map for each criteria was managed from the data of the study area. A unique
criteria measurement was performed to realize a weighted linear combination (WLC)
to use it in the analysis procedure by ArcMap10. A scale value was arranged to a
suitability value for each sub-criteria, the higher a suitability value provides a lower
scale value. However, the ones with the highest suitability values were regarded the
most favorable fields for the roadway route. While the fields with a suitability value
of 0 were regarded unsuitable areas for roadway construction.
• Land use: A suitability value was executed according to land use partitions due to
categories and prices of land for integration of criterion scale. Airport, hospital,
military zone and industrial zone were given the value of 0, therefore, these category
fields were excluded from the possibility over which roadway could pass.
• Water resources: A sequential distance was recognized from Tigris river bank to
reduce the distance of river crossing.
• Slope: A Digital Elevation Model (DEM) with 10 m resolution was converted to a
relative slope. A slope of (0-3%) was considered as flat terrain, (3-5%) as Rolling
terrain while (5-7%) slope was considered as mountain terrain [19]. An increasing
percentage of slope resulting in increasing earthwork construction, therefore, the
fields with low slope are assigned the high suitability value, while the fields with high
inclination are assigned the lowest suitability value.
• Soil bearing: California Bearing Ratio- CBR was considered to determine a
suitability value. The layers with a high value of CBR were assigned higher
suitability values because hard grounds provide more suitable conditions for
roadways. CBR for the study area ranging between (<4% - 8.33%), using Inverse
Distance Weighting (IDW) processes by Arc-Map10 for creating predicted surface
for soil bearing map regarding CBR.
• Environmental impact: Gases from the exhaust of moving vehicles was considered
for estimation of harmful, therefore, the study area was divided according to land use
considering the primary circumstance is for reducing harmful to occupying the land.
• Hydrology: Location of valleys was determined from the DEM map. Valleys were
classified according to their cross section, Type 1 is the smaller cross section and best
suitable while Type 3 recognized larger cross section and less suitable.
• Settlement area: A sequential distance was considered from the settlement area to
the proposed route with minimum a distance of 500m and the area was divided in
constant range distance from settlement area.
• Linear engineering structure: Right of way was established by the linear
engineering structure which is the roadway, pipe line, power line, rail road, and rail
tunnel to reduce crossing with the proposed route. Suitability value was considered
through the severity and most probability for accidents of these linear structures with
the proposed route. Fig. (6) shows criterion maps in the study area.

a. Criterion map for land use
b. Sequential distance of criterion map for water resources
c. Digital Elevation Model-10m of criterion map for slope

Route Location
d. California Bearing Ratio- CBR of criterion map for soil bearing
e. Criterion map for environmental impact
f. Type of valley of criterion map for hydrology

g. Sequential distance from urbanized area
h. Criterion map for linear engineering structure
Figure 6 Criterion maps in the study area
4.2. Surface composition cost and optimum route selection
The criterion maps were overlaid and the final land suitability map was prepared
using a weighted linear combination (WLC) to realize equivalent surface cost for all
criteria.
The (WLC) method is the most often used proficiency for undertaking spatial
multi-attribute decision making, in other words; based on the concept of a weighted
average [20]. In this process, the decision maker directly allocates weights of relative
importance for each attribute. For each alternative a total score is acquired by
multiplying the importance weight allocated for each attribute by its scale value, and
summing the products [21].
The most desired alternative is selected by identifying the minimum value of the
summing products [9].This method can be adapted using GIS program having

Route Location
capabilities of overlay that allow the evaluation criterion map layers to be
accumulated to determine the composite map layer. Fig. (7) shows the finding of the
Optimum Route (OR) within the study area.
Figure 7 Optimum route in the study area
4.3. Evaluation of optimum route
Optimum route and any other route can be evaluated by elicitation the value of cells
from cost surface through the path of the route and summing the values of that route.
A comparison was an assessment of the optimum route with the shortest route (line
joining the origin and destination points) and the three tracks proposed by the relevant
agencies, by finding the sum of the cell values through each route. Table (5) shows
the number of cell and cost surface for each route, after re-value the cell weight. It is
shown from the table that optimum route had the shortest path after a straight line
path and reduce valuable cost surface through proposed routes by up to between
(21.8% to 63.7%).
Table 5 Number of cells and cost surface for optimum, shorest, and the three proposed routes

4.4. Generating alternatives
The cost surface is changed to form many alternatives with different lengths to define
Least Cost Route. That is done by economic assessment of the influential criteria on
the suggested routes.A change in surface cost was proceed using the formula (9)
mentioned in the methodology to find another suggested routes with the same origin
and destination points. Table (6) show suggested routes with their lengths, while Fig.
(8) shows the utility scenario for suggested route locations.
Table 6 Length of suggested routes compared with optimum one
Reduction in
Length %
Length- mAdjusted ValueNameId
----13489.500Route _Line (OR)1
0.3513441.901Route _Line 12
2.2513186.333Route _Line 33
3.7712979.635Route _Line 54
5.5212744.117Route _Line 75
5.6012735.219Route _Line 96
5.2312784.0711Route _Line 117
Figure 8 Utility scenario for suggestedroute locations
4.5 Evaluation of alternatives
The total cost for roadway routes were gained by calculate the operation cost
depending on the traffic survey data and the construction cost that effected by a group
of criteria to evaluate alternative routes.
Table (7) summarized the operation, and construction costs for suggested routes.
It is shown that the Route_Line3 has the lowest cost with a reduction in length of
2.25% contrasting optimum one.

Route Location
Table 7 Operation, and construction costs for suggested routes
(a) Operation cost*
Operation Cost
($)
Tire Cost($)Oil Cost ($)Fuel Cost ($)
Length (m)Route Name 15756.77*L
/1000
6113.469*L
/1000
39266.17*L
/1000
824699.5212550.9382467.6452968113489.5Route _Line (OR)
821789.4211800.9182176.6452781213441.9Route_Line1
806164.8207773.9580614.2251777713186.33Route_Line3
793527.9204517.0379350.5650966012979.63Route_Line5
779129.020080677910.7250041212744.11Route_Line7
778584.9200665.7677856.3150006312735.21Route_Line9
781572.0201435.6478155.0150198112784.07Route_Line11
* Operation cost are calculated according to reference ITMP [19]
(b) Construction cost
(c) Construction cost with and without bridge
5. CONCLUSIONS
This study is mainly focused on finding a route location by applying AHP method to
land use suitability analysis with eight criteria layers using GIS techniques, from this
study we concluded that:
1. The Analytic Hierarchy Process (AHP) model is possible to accomplish a complex
process in a much shorter time and accuracy and gives an ideal method of creating
scenarios that differ significantly from proficient or decision maker.
Environment
Impact Cost_$
Settlement area
Cost_$
Construction
Cost_$
Geology
Cost_$
Bridge Cost_$
Acquisition
Cost_$
Cut & Fill Cost $Route Name
1,370,385.42,160,947.27,078,600.7790,827.8389,8845.51,265,090.7579,923.7Route _Line
1,365,549.82,160,576.77,053,322.3788,849.33,898,845.51,254,033.3594,688.5Route_Line1
1,339,586.62,143,412.06,917,599.9811,922.73,898,845.51,165,716.9763,905.4Route_Line3
1,318,588.22,160,957.86,805,010.4804,383.44,028,036.51,142,215.61,210,233.9Route_Line5
1,294,661.93,056,208.36,445,553.4811,578.214,765,980.2983,899.91,478,759.8Route_Line7
1,293,757.83,057,537.06,440,827.0840,882.714,765,980.2983,326.21,648,779.0Route_Line9
1,298,721.42,876,051.96,556,273.6783,546.310,665,684.21,024,401.72,178,618.5Route_Line11

2. The present study shows that a pair-wise comparison proved to be the efficient and
effective method for determining criteria weights.
3. The relative importance of the designed criteria defined in this study is as follows:
land use (23%), water resources (26%), slope (10%), soil bearing (10%),
environmental impact (5%), hydrology (8%), settlement area (11%) and linear
engineering structure (7%).
4. It was found that the optimal route reduces valuable cost surface by up to between
(21.8% to 63.7%) for the proposed tracks by the relevant agencies. While a shorter
route than the optimum one is gained with less cost of (2.25%) to reduce the
environmental impacts and travel time.
REFERENCES
[1] V. D.Patil,R. N.Sankhua, and R. K. Jain, Analytic hierarchy process for
evaluation of environmental factors for residential land use suitability,
International Journal of Computational Engineering Research, Vol. 2 Issue 7,
2012.
[2] R.Greene, R.Devillers, J. E.Luther, and B. G.Eddy, GIS-based multiple-criteria
decision analysis, Geography Compass 5/6, 2011, pp.412–432.
[3] T. L.Saaty, The analytic hierarchy process (McGraw-Hill, New York, NY,
1980).
[4] H. S.Mann, Using the analytic hierarchy process for decision making in
engineering application: some challenges, International Journal of Industrial
Engineering: Applications and Practice, 2(1), 1995, pp. 35-44.
[5] M. O.Al-Mumaiz, Spatial multi-criteria assessment to select an optimum route
to improve transportation network in Al-Omarah city, Engineering &
Technology Journal, 30(8), Technical University, Baghdad, 2012.
[6] S. J. Carver, Integrating multi-criteria evaluation with geographical information
systems, International Journal of Geographical Information Systems, 5(3), 1991,
pp. 321–339.
[7] B. Roy, Multicriteria methodology for decision aiding (Dordrecht: Kluwer
Academic Publishers, 1996).
[8] J.Malczewski, GIS-based multicriteria decision analysis: A survey of the
literature, International Journal of Geographical Information Science 20(7),
2006, pp. 703–726.
[9] J.Malczewski, GIS and multi-criteria decision analysis (John Wiley & Sons,
1999).
[10] D. B.Geneletti, A GIS-based decision support system to identify nature
conservation priorities in an alpine valley, Land-Use Policy 21, 2004, pp. 149-
160.
[11] T.Roh,J. Lee, H.Kim, J.Kim, and Y.Jung, Construction on decision support
system for route location based on GIS, The International Archives of the
Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol.
XXXVII, Part B2, Beijing, 2008.
[12] T. L.Saaty, Decision making with the analytic hierarchy process, International
Journal Services Sciences, 1(1), Inderscience Enterprises Ltd, 2008, pp.83–98.
[13] N. J.Garber,andL. A. Hoel, Traffic and highway engineering, fourth edition
(Cengage Learning, 2009).
[14] M.Piantanakulchai, andN.Saengkhao, Evaluation of alternatives in transportation
planning using multi-stakeholders multi-objectives AHP modeling, Proceedings
of the Eastern Asia Society for Transportation Studies, 4, 2003.

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[15] R.Sadasivuni, C. G. O’Hara, R.Nobreg, and J. Dumas, A transportation corridor
case study for multi-criteria decision analysis, ASPRS 2009 Annual Conference
Baltimore, Maryland, 2009.
[16] T. T.Duc, Using GIS and AHP technique for land-use suitability analysis,
International Symposium on Geoinformatics for Spatial Infrastructure
Development in Earth and Allied Sciences, 2006.
[17] F.Kara, andN.Usul, Highway route design through the use of GIS and multi-
criteria analysis: A case study of Istanbul, Ozean Journal of Applied Sciences
5(1), Ozean Publication, 2012.
[18] A. J.Schmidt, Implementing a GIS methodology for sitting high voltage electric
transmission lines, Volume 11, Papers in Resource Analysis, 17 pp. Saint
Mary’s University of Minnesota University Central Services Press, Winona,
MN, 2009.
[19] ITMP, Iraqi Transport Master Plan, A joint project between the Iraqi
government and the Italian government, Italian consortium for Iraqi transport
infrastructure, the final issue, 2005.
[20] J.Malczewski, On the use of weight linear combination method in GIS :
Common and best practice approaches, Department of Geography, University of
Western Ontario, Transaction in GIS, 4(1), 2000, pp. 5-22.
[21] Islam M. Abo Elnaga. Waste Materials Recycling In Highways Construction,
International Journal of Civil Engineering and Technology, 5(7), 2014, pp. 17–
25.
[22] Abdul Kareem Naji Abbood. Rehabilitation Study of Altaji – Baghdad Highway
Through The 8.00 Km Section Length, International Journal of Civil
Engineering and Technology, 5(3), 2014, pp. 50–59.
[23] Islam M. Abo Elnaga. Development of Traffic Accidents Prediction Models At
Rural Highways In Egypt, International Journal of Civil Engineering and
Technology, 5(6), 2014, pp. 16–24
[24] A.Djenaliev, Multicriteria decision making and GIS for railroad planning in
Kyrgyzstan, M.Sc Thesis in Geoinformatics, School of Architecture and the
Built Environment Royal Institute of Technology (KTH)100 44 Stockholm,
Sweden, 2007.

USING THE ANALYTIC HIERARCHY PROCESS AND GIS FOR DECISION MAKING IN RURAL HIGHWAY ROUTE LOCATION

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