GIS-AHP MULTI CRITERIA NATURE PROTECTION VULNERABILITY EVALUATION METHOD: A CASE STUDY OF TARA NATIONAL PARK, SERBIA

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-© by PSP Volume 32– No. 09/2023 pages 2954-2964 Fresenius Environmental Bulletin
2954
GIS-AHP MULTI CRITERIA NATURE PROTECTION
VULNERABILITY EVALUATION METHOD: A CASE
STUDY OF TARA NATIONAL PARK, SERBIA
Darko Lukic1,*, Marija Peric2, Slobodanka Stankov3
1Military Academy, University of Defence, Pavla Jurisića Šturma 33, 11000 Belgrade, Serbia
2Academy of Applied Technical Studies Belgrade, Katarina Ambrozić 3, 11000 Belgrade, Serbia
3Western Serbia Academy of Applied Studies, Užice Department, College of Applied Sciences Užice, Trg Svetog Save 34, 31000 Užice,
Serbia
ABSTRACT
The main problem of this research is to
determine the “vulnerability” of protected areas on
the example of National Park (NP) “Tara”. For the
purposes of the research, the GIS˗AHP Multi
Criteria Nature Protection Vulnerability Evaluation
Method (GIS˗AHP MPVEM) was developed. By
applying this method, the obtained results indicate
factors that mostly influence on “vulnerability” of
the protection regime degree (first, second and third)
in the studied area, based on comparisons with the
current protection of the area. The spatial protection
function of the Zone I is very small (34.7%) and
spatial “vulnerability” of the total protection is
41.5%. The result was influenced by the poor relief
and communication accessibility of the protected
zone. Moderate “vulnerability” (20.8%) is
associated with most illegal landfills. Very high
(2.5%) and high (0.6%) spatial “vulnerability” refers
to the area that is outside of the protection of Zone I
or in contact with protection of Zone II. In the future,
the obtained parameters should imply new protected
zones of NP “Tara”, mainly presented in the
expansion, i.e. variability of existing boundaries. In
accordance with European Union (EU) regulations,
recommendations and directives, the Republic of
Serbia is obliged to expand the protected areas up to
20% of the total area of its territory.
KEYWORDS:
GIS˗AHP, spatial “vulnerability”, protected zones,
National Park “Tara”
INTRODUCTION
In order to spatial protection, the formation of
protected areas of nature is increasingly growing into
an activity of global proportions. Introducing the
term of nature conservation in the 1980s, scientists
have warned to mass extinction of species, especially
in biodiversity rich countries [1]. As nature
protection is increasingly degraded, humanity is
looking for modules on how to highlight and
stimulate the protection of natural resources and
values [2-3].
The spatial protection in the Republic of Serbia
has a long tradition. It is mostly sporadic and
unplanned. Natural protected assets cover an area of
6.770 km2 or 7.65% of the total territory of the
Republic of Serbia (88.361 km2). It is evident that
the surface under protected areas of nature is below
the levels of Europe and the world. According to EU
directives, the Republic of Serbia is obliged to
expand the protected areas up to 20% of the total area
of its territory. Consequently, the Spatial Plan of the
Republic of Serbia (PPRS) 2021-2035 envisages that
the regimes of the first level of protection include
5%, the second level of protection 25% and the third
level of protection 67% of the total protected area
[4]. The Decree on protection regimes defines
general regimes of I (strict protection), II (active
protection) and III (proactive protection) degree of
spatial protection [5]. According to Maksin,
protected areas are generally categorized into three
groups of spatial protection (strict protection,
selective protection and rehabilitation and
renovation) [6].
National parks are the representatives of the
most complex spatial protection where strict and
selective protection is applied. Of special importance
is NP “Tara”, whose natural and created values are
protected within the most important conservation
tool in the EU–NATURA 2000 ecological network
[7]. NP “Tara” with “Zaovine” Landscape of
outstanding features and Šargan-Mokra Gora Park of
Nature will become part of the future cross-border
protected area – “Drina” Biosphere Reserve under
the UNESCO Man and the Biosphere (MaB)
programme. The cross-border position as well as
belonging to “Drina-Tara” Euroregion will include
the evaluation of protected areas and the
establishment of new protection regimes or as Xu
proposed in China – the creation of mixed zoning
schemes based on the UNESCO MaB programme
[8-9].
The main subject, task and goal of this research
is to determine the “vulnerability” of the existing

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protected area of NP “Tara”. Based on the defined
criteria that mostly endanger protected zones and
lead to spatial “vulnerability” GIS˗AHP MPVEM
method was created. By applying this method, the
obtained research results indicate spatial parts
endangered by the action of various factors, based on
the comparison with the current state of spatial
protection. In the future, the research results should
imply a new definition of protection zones and a
possible expansion of NP “Tara” in accordance with
initiatives, regulations, proposals and laws.
MATERIALS AND METHODS
In modern environmental research, GIS has
been applied alone or in combination with other
methods in various aspects of evaluation and zoning
of protected areas (Table 1). For the purposes of this
research GIS˗AHP MPVEM model was developed.
TABLE 1
The applied multi-criteria analysis methods for nature protection zoning.
Objective of the evaluation
Method
Reference
Synthetic evaluation of eco-environment quality
GIS, AHP
[10]
Evaluation and protection tool for resources of nature
GIS
[11]
Protected area for wildlife sanctuary zoning
GIS, AHP, Fuzzy, MOLA
[12]
Environmental impacts in protected areas
GIS
[13]
Prevention of unsuitable land use changes and vegetation
cover development
AHP, Delphi, MADM,
TOPSIS
[14]
Conservation of biodiversity
GIS, AHP
[15]
Zoning protection of plants for nature conservation
GIS, Fuzzy
[16]
Delimitation of landscape
GIS, Fuzzy
[17]
Evaluation potential sites for soil and water conservation
techniques
GIS, AHP
[18]
The suitability of land use
GIS, AHP, Fuzzy logic
[19]
Territorial planning of suitable rural areas
GIS, OWA, WLC, AHP
[20]
Development of eco-zones in protected areas
GIS, RS, SPCA
[21]
Evaluation of sustainable land-use planning
GIS, MCA
[22]
Evaluation of the environmental vulnerability
GIS, PPM
[23]
Evaluation of ecological habitats vulnerability
GIS, PCA, Fuzzy
[24]
Zoning for a multiple-use marine protected area
GIS, AHP, SAW
[25]
Assessment of the soil erosion criterion
GIS, AHP, Fuzzy
[26]
Environmentally sensitive areas for land use planning
GIS, AHP
[27]
Analysis of breeding habitats for recolonizing species
GIS, AHP
[28]
Zoning eco-environmental vulnerability for environmental
management and protection
GIS, AHP
[29]
Assessment of ecosystems vulnerability to fire in managing
natural protected areas
GIS, Fuzzy
[30]
Zoning ecological red line
GIS, AHP
[31]
Nature conservation
GIS, MCDA
[32]
Flood hazard zonation
GIS, AHP
[33]
Analysis of natural reserves of biodiversity
GIS, AHP, TOPSIS
[34]
Ecosystem degradation
GIS, MCA
[35]
Population and settlement pressure on protected areas
GIS
[36]
TABLE 2
Saaty's pair-wise comparison scale for AHP
Intensity of relative importance
Definitions
1
Equal importance
2
Equal to moderate importance
3
Moderate importance
4
Moderate plus
5
Strong importance
6
Strong plus
7
Very strong demonstrated importance
8
Very, very strong
9
Extreme importance

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FIGURE 1
Steps of GIS-AHP MPVEM model
 

                (2)
The proposed model consists of several
logically related steps presented in (Figure 1). The
multicriteria analysis model is based on integration
of widely applicable AHP and Weighted Overlay
tool. Based on a large number of factors that may
have an impact on the endangermentanalysis of
existing protected zones in NP “Tara”, AHP
integrated in GIS can provide appropriate
manipulation and presentation of data with
consistent evaluation.
AHP is procedure for modeling, based on raster
data in a multi criteria hierarchical configuration
[37]. The original Saaty´stechnique [38] involves a
nine-level of assessment (Table 2).
Based on the opinion of one or more experts,
the procedure involves assessing the importance of
each individual factor. Then, the nine-level
assessment system is applied to a two-dimensional
n×n reciprocal AHP matrix, where each criterion is
compared with each of their in order to get relative
weights expressed in numerical scale values as it
follows   󰇛    󰇜. Normalization of the
sum of rows is perform by dividing the sum of each
row by the number of rows. The result of the
calculation is a priority vector, i.e. a vector of the
eigenvalues of the matrix. In the standard AHP, the
eigenvector method (EV) is used to determine the
weights of the criteria, that is, the main right vector
of the eigenvalues of the matrix A [31]. This vector
is obtained by solving a linear system (1):
   (1)
where λ is the largest eigenvalue of the matrix
A, and w is required vector of weight criterion.
Based on the results of the previous step (1),
each criterion received an appropriate weight
coefficient, defining its relative value in relation to
the desired outcome [32]. The final convenience map
is obtained by calculating the total benefit of each
raster cell using equation 2:
where is the cell value, on the final
convenience map andis the weight coefficient.
The consistency of the matrix is controlled by
consistency parameters  (Consistency Index),
(Random Index), (Consistency Ratio), 
(Eigenvalue – sum of the products between each
element of the Eigen vector and column totals) and
n (Number of factor), using equation 3:
 
  
 (3)
If  is assumed to be the number of conditional
factors, then the total number of comparisons that
one expert should make is 󰇛󰇜
 [35].
Consequently, this procedure is adequate only in
cases where no more than ten factors are involved
(Table 3), but in some cases, such as our work, a
minor degree of inconsistency is fully acceptable
[39].

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TABLE 3
Average Random Consistency Index with consistency scale rate
Scale rate
High Consistency
Average Consistency
Low Consistency
Matrix size
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
(RI)
0
0
0.58
0.9
1.12
1.24
1.32
1.41
1.45
1.49
1.51
1.54
1.56
1.57
1.59
The proposed model is consistent if   .
It can be interpreted that the assessment matrix is
inconsistent with less than 10%, or it is consistent
with over 90%. In the following procedure, it is
recommended the sharpness of the model to be
tested.
Study area. The first step was to define the
research area. Than, the problem of the research was
identified too. Based on geographical characteristics,
possible ways of solving the observed problem were
also defined. NP “Tara” is located in the western part
of the Republic of Serbia, in the bend of the Drina
River, on the border with Bosnia and
Herzegovina.With an area of 24.991,82 ha, it covers
the largest part of Tara Mountain, as a significant
resource of the Western SerbiaTourist Region.The
problem of the paper refers to the “vulnerability” of
protected zones in NP “Tara”. In accordance with the
problem, the criteria that mostly endanger protected
zones and lead to their “vulnerability” have been
defined.
Criteria modeling and standardization.
Modeling and standardization of the necessary
criteria for the spatial analysis was performed in the
next step. In the previous practice of solving the
problem of spatial protection evaluation different
spatial criteria have been applied (Table 4).
Topographic criteria have an impact on the
spatial accessibility. Higher altitudes and slopes
prevent access to human activity. Areas with greater
percentage of slope аre less frequented than others
[34]. Altitude has a significant impact on processes
that can affect environmental vulnerability [29].
Lower altitudes and smooth topography are
accessible for human activity. Higher altitudes are
less accessible and endangered [16].
The quality of vegetation diversity is an
important criterion in spatial protection [15]. An area
with large number of endemic species has a higher
value in spatial protection. So far 1013 plant species
have been identified on Tara Mountain. Picea
omorika, the relict and endemic species, indicates
the importance and potential of Tara Mountain as
floristic and vegetation diversity of Serbia and
Balkan Peninsula [71]. In vegetation criterion the
highest value is assigned to coniferous forests, mixed
forests and meadows [43].
Representation of animal species is
interdependent with vegetation, water resources and
topographic criteria [12]. Areas with a large number
of registered wildlife habitats have the greatest value
in spatial protection [44]. Over 53 species of
mammals, 153 species of birds and 37 species of fish
have been registered on Tara Mountain.
.
TABLE 4
The most frequently used criteria for nature protection in previous research
Criteria
Reference
Relevant research
Topography
[40], [41], [16], [21], [20], [42], [27], [43], [29],[34], [44]
yes
Vegetation diversity
[45], [11], [46], [12], [15], [16], [47], [20], [21], [48], [43], [27],
[29], [49], [34]
yes
Wildlife distribution
[45], [12], [50], [16], [48], [27], [44]
no
Water bodies
[12], [15], [16], [47], [23], [27], [42], [29], [51]
no
Hydro meteorology
[52], [42], [43], [29], [44]
no
Road distance
[53], [12], [15], [16], [47], [21], [20], [48], [43], [54], [29], [34]
yes
Settlement and infrastructure
pressure
[53],[45], [55], [56], [57], [13], [58], [15], [47], [21], [20], [59],
[43],[ 54], [34], [60], [61], [62], [36]
yes
Agriculture sites
[45], [12], [63], [47], [19], [20], [23], [48], [54], [42], [29], [34]
yes
Cultural presence and
tourism sites
[12], [64], [65], [20], [27], [66], [67], [68], [60]
yes
Natural risk
[45], [23], [27], [42], [47], [33]
no
Pollution risk
[55], [27], [34]
no
Natural protected area
[69], [70], [15], [47], [67], [34]
yes

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Roads increase human pressure on natural areas
[12]. The most endangered areas are in the
immediate vicinity of the roads. The quality of roads
does not have the same value when it comes to the
accessibility of spatial protected areas [16]. The
distance of more than 3000 m from the roads does
not negatively affect the biodiversity preservation
[15]. For that reason, roads are evaluated differently
depending on their importance, traffic frequency etc
Settlements and different types of
infrastructure have a negative impact on spatial
protection. Primarily it refers to hydropower plants,
tourist infrastructure, rural and weekend settlements.
Protected sites close to these objects are at a higher
risk of disturbance by the local residents [53, 16, 34].
Agricultural areas disrupt biodiversity through
human activity and through the risk of soil and
groundwater pollution [34]. Natural spatial areas at a
greater distance from agricultural areas have a
greater protective value. Therefore, areas near crops
have a greater tendency to be damaged than others
[34]. After defining the criteria, it is necessary to
assign credit values. On the basis of assigned credit
values on a five-point scale, an evaluation of the
spatial endangerment will be performed according to
the appropriate spatial values (Table 5).
In the last step, the appropriate cartographic
material was selected. Then, selected material was
adapted to the appropriate digital form suitable for
the application of GIS-AHP MPVEM (Table 6).
Model evaluation processing. In the further
evaluation step, ArcGIS Desktop 10.6 software was
used. The first step in evaluating alternatives in AHP
method is normalization (Table 7).
Criteria weights were automatically computed
in decision support tool using AHP Excel Template
Update Version 2018-09-15, where criterion maps
were obtained through appropriate standardization
(Figure 2a).
TABLE 5
Criteria for assessing the endangerment to protected areas of Tara National Park
Criteria
Assigned score
Very Low
Low
Moderate
High
Very High
C1
Slope ()
40<
30-40
20-30
10-20
<10
C2
Vegetation type
Transitional
woodland/shru
b
Broad-
leaved
forest
Mixed
forest
Coniferous
forest
Natural
grasslands
C3
Distance to large roads
(m)
1000<
750-1000
500-750
250-500
<250
C4
Distance to trails (m)
200<
150-200
100-150
50-100
<50
C5
Distance to vilages and
settlment (m)
2000<
1500-2000
1000-1500
500-1000
<500
C6
Distance to tourism
infrastructure (m)
3000<
2000-3000
1000-2000
500-1000
<500
C7
Distance to agriculture
sites (m)
2000<
1500-2000
1000-1500
500-1000
500<
TABLE 6
Materials and used methods of criteria map preparation
Criteria
Data material
Scale
Geoprocessing method
Reference
Slope
Digital Terrain Model (DTM)
25 x 25m
Reclassify, slope surface
analyses
[72]
[73]
Roads distance
Digital topographic map 50
(TK50)
1: 50000
Radial distance,
Reclassify
Trails distance
Settlement and
villages distance
Spatial Plan of the special
purpose area of the National Park
“Tara” (Reference map 3 and 4
Natural resources, environmental
protection, natural and cultural
values, tourism, implementation
of the plan)
1: 50000
Radial distance,
Reclassify
[74]
Tourism
infrastructure
distance
Protected zone
distance
1: 50000
Clip, Reclassify
Vegetation
Corine Land Cover 2018
25 x 25m
Radial distance,
Reclassify
[75]
Agriculture
sites

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TABLE 7
Materials Criteria Comparison Matrix
Criteria
C1
C2
C3
C4
C5
C6
C7
Weight
Slope
C1
1
8
3
5
5
5
5
0.4200
Vegetation
C2
1/8
1
1/5
1/3
1/7
1/8
1/5
0.0245
Roads distance
C3
1/3
5
1
3
1
1
3
0.1529
Trails distance
C4
1/5
3
1/3
1
1/2
1/3
1
0.0632
Vilages and settlment
C5
1/5
7
1
2
1
1
1
0.1189
Tourism infrastructure
C6
1/5
8
1
3
1
1
1
0.1308
Agriculture sites
C7
1/5
5
1/3
1
1
1
1
0.0898
FIGURE 2
Map of standardized criteria (a). Final spatial vulnerability map (b). Map of spatial vulnerability of
protected zones (c)

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TABLE 8
Endangerment of Tara National Park
Area
Very Low
Low
Moderate
High
Very High
Zone I (km²)
11.6
13.9
6.9
0.8
0.2
Zone II (km²)
0.1
13.2
48.6
17.0
0.6
Total (km²)
11.7
27.1
55.6
17.9
0.8
As the obtained  is 0.05 it can be claim that
the proposed model has a satisfactory consistence.
As said before the proposed model is consistent if
   . In the further procedure, the criterion
maps were integrated into the final map based on the
obtained weight vectors using the ArcGIS Weighted
Overlay tool (Figure 2b). The last step is the final
evaluation of endangered area protection obtained
model with the existing model of protected areas
defined in the PPRS 2021-2035 [74]. This step was
performed by comparing the potentially endangered
area with the actual protected area of NP “Tara”
(Figure 2c).
RESULTS AND DISCUSSION
In the last step, using the GIS-AHP MPVEM,
the protected zones were compared with the obtained
spatial “vulnerability” map. The obtained results are
shown in Table 8.
Based on an existing document PPRS 2021-
2035 [74], the function of spatial protection of Zone
I is very small and amounts 34.7%, while the spatial
“vulnerability” is 41.5% of the total protection. The
result was influenced by the poor relief and
communication accessibility of the protected zone
confirmed by the results of previous research in this
area [36]. A small part of the vulnerable area within
the protected Zone I is topographically accessible
and is located near the roads in a moderately
vulnerable area of 20.8%. According to Jordá-Borell
et al., [76] smooth topography is associated with
most illegal landfills. Very high (2.5%) and high
(0.6%) spatial “vulnerability” refers to segments that
are outside the protection of Zone I or are in contact
with protection of Zone II (Figure 2c).
When it comes to the protected area of Zone II
the results of the evaluation showed a significantly
higher degree of “vulnerability”. Very high (0.1%),
high (21.4%) and medium (61.4%) “vulnerability”
of the mentioned protected area were observed. The
small (21.4%) and very small percentage (0.7%) of
protected zones “vulnerabilities” were influenced by
similar factors as in Zone I. The most important
factor that influenced the greater “vulnerability” is
the presence of the local population, in our case
defined as population. The presence of the
population has a high impact on the degradation of
the protected area[35]. Economic activity has a
significant role in spatial endangering and the most
important factor that has been noticed is the
unplanned, i.e. illegal construction of private
weekend facilities. According to Caniani et al., [24]
every human activity affects the reduction of the
number of plant and animal habitats. Another
important factor of “vulnerability” that was observed
is the presence of infrastructure intended for mass
tourism within or in the immediate vicinity of
protected areas. Ristić et al., [13] noticed similar
factors of spatial endangering that arose as a
consequence of mass tourism development and good
communication connections in the area of NP
“Kopaonik”.
Negative aspects of endangering the protected
area of NP “Tara” can be eliminated or partially
mitigated by taking appropriate activities, laws and
measures. The first one is to redefine the existing
protected area and adopt regulatory acts in favor of
expanding protected Zone I. In that context, the
current cross-border and European initiatives are
very important. These initiatives indicate and dictate
that in coming period more than 20% territory of the
Republic of Serbia should be protected. This will not
be possible without the implementation, i.e. the
application of the concept of sustainable
development in tourism, where one of the solutions
is the successful development of ecological tourism.
Ecotourism is just one of the solutions where it is
necessary to reconcile the negative aspects of mass
tourism and economic activities with nature
protection [77]. As one of the most influential factors
on the spatial “vulnerability” was the
communication availability, it is necessary to limit
access to vehicles as well as the number of visitors
in certain parts of the protected zones of NP “Tara”.
CONCLUSION
The presented method is conceived by AHP
multi criteria analysis and shows the natural and
social factors that affect the protection of NP “Tara”.
The method is characterized by compactness and is
suitable for adapting and evaluating the
“vulnerability” of other categorized protected areas
(natural monument, protected habitat, landscape of
exceptional features and park of nature). This would
require some modification and selection of criteria
for assessing “vulnerability” in line within the
natural and created features of the new evaluated
area. In addition to the good sides, the proposed
method has certain weaknesses and shortcomings. In
order to maintain a high level of consistency, the
number of criteria has been reduced. Cultural
heritage sites that create pressure on the environment

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2961
based on tourist visits and endangered the protected
area were not included. Also, the sensitivity analysis
was not applied in the paper. Elaboration of different
scenarios through sensitivity analysis would increase
the percentage of subjectivity in the assessment of
protected area valuation as presented by Comino et
al., [47]. In this context, the basic idea of presented
GIS-AHP MPVEM is a solution for quick
comparison of the desired and actual state of the
protected area. Thus, model methodological
possibilities have not been exhausted, but it is
necessary to further develop them.
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Received: 21.06.2023
Accepted: 30.08.2023
CORRESPONDING AUTHOR
Darko Lukic
Military Academy
University of Defence
Belgrade 11000 – Serbia
e-mail: hadzidarko.lukic@gmail.com