Environmental Urbanization Assessment Using GIS and Multicriteria Decision Analysis: A Case Study for Denizli (Turkey) Municipal Area

In recent years, life quality of the urban areas is a growing interest of civil engineering. Environmental quality is essential to display the position of sustainable development and asserts the corresponding countermeasures to the protection of environment. Urban environmental quality involves multidisciplinary parameters and difficulties to be analyzed. *e problem is not only complex but also involves many uncertainties, and decision-making on these issues is a challenging problem which contains many parameters and alternatives inherently. Multicriteria decision analysis (MCDA) is a very prepotent technique to solve that sort of problems, and it guides the users confidence by synthesizing that information. Environmental concerns frequently contain spatial information. Spatial multicriteria decision analysis (SMCDA) that includes Geographic Information System (GIS) is efficient to tackle that type of problems. *is study has employed some geographic and urbanization parameters to assess the environmental urbanization quality used by those methods. *e study area has been described in five categories: very favorable, favorable, moderate, unfavorable, and very unfavorable. *e results are momentous to see the current situation, and they could help to mitigate the related concerns. *e study proves that the SMCDA descriptions match the environmental quality perception in the city.


Introduction
ere has been a growing interest on life quality of the urban areas due to many reasons in recent years.e matter holds many components like buildings, physical environment, health, security, and community.e environmental issues of urbanization are the major portion of the physical environment difficulties.
e quality of urban environment involves multidisciplinary parameters, and they are interconnected parameters containing the distribution of green zones, the urban heat island, air quality, and building density and geometry [1].ese parameters, vital for densely populated cities, can be monitored easily [2].A large number of studies enlighten the problems, their sources, and mitigation measures [3][4][5][6].is complex problem also contains many uncertainties and subjective judgements.
erefore, decision-making on these problems is tough and encloses many parameters and alternatives inherently.Multicriteria decision analysis (MCDA) comes forward to handle that type of problem-solving; it is because the objective and subjective parameters can be defined and evaluated.Multicriteria decision-making takes accounts of several choices or behavior patterns when there exist a number of alternatives which disaccord to a major extent [7].A set of systematic procedures to analyze multifaceted problems is employed in decision analysis.e problem is allocated into small logical parts each of which is analyzed, and the parts are integrated in a rational manner to form a meaningful solution [8].MCDA is a very effective method to handle such problems, and it leads the decision makers confidence by combining that information.is practice may be intuitive or analytical [9].Hence, experience as well as data is vital because the parameters have comparative significance.e criteria may be both qualitative and quantitative [10].
MCDA supports users in analyzing potential engagements or options based on multiple unmeasurable factors/ criteria, using decision rules [8].ere are two approaches to classify the MCDA methods, namely, multiobjective decision-making (MODM) and multiattribute decisionmaking (MADM).
e main difference between them is the number of evaluated options.
e first one is more suitable to tackle the multiobjective planning, while the latter is designed for selecting discrete alternatives [11].In this sense, the MCDA methods are classified into three groups: value measurement models, goal, aspiration, or reference level models, and outranking models [7].e values of alternatives reflect a preference order in the first group.e second group leads methods for "situations in which users may consider it very difficult to express trade-offs or importance weights but may be able to describe outcome scenarios, expressed in terms of satisfying aspirations or goals for each criterion."e outranking models focus on "pairwise evaluation of alternatives, identifying incomparabilities as well as assessing preferences and indifferences" [11].
e analytic hierarchy process (AHP) as a type of MCDA was developed by Saaty [12]. is method consists of three distinct phases: the principle of "building hierarchies," the principle of "setting up priorities," and the principle of "logical consistency" [13].
e first principle is based on findings and detects relations between them.People cannot recognize and analyze the effective factors of a whole structure without dividing it into small parts.It is being performed by a logical process, which aims at building proper hierarchies."A hierarchy is a specific system type, which is grounded on the assumption that the user assigned entities, can be grouped into separate sets, with the assets of one group impressing the assets of only one other group, and being impressed by the assets of only one group" [14].e simplest model of hierarchy contains three levels: the first one is the aim of the decision-making problem and the other two comprise criteria and options.Pairwise comparisons in the AHP are engaged for setting up weights among components of the same hierarchical level.All the components of the level are paralleled in pairs with respect to the logical components in the next higher level, obtaining a pairwise comparisons' matrix.In order to represent the relative importance of one component over another, a pairwise comparison scale is announced.Its values range from 1 to 9, and they are assigned to judgement in comparing component pairs in each level [15].It compares criteria pairwise on a fuzzy-linguistic ratio scale and calculates the overall relative weights based on cumulative computations of all pairwise ratios [9].AHP also offers a contributive, hierarchical accumulation of criteria [16].e method was engaged in numerous studies like engineering, nature, and social sciences [17][18][19].It is also frequently used in environmental studies [20,21].
e function of Geographical Information System (GIS) in early times was only storage, displaying geographic data.Presently, GIS has become a significant technology by the inclusion of end users in navigation devices, GPS-(global positioning system-) enabled smartphones, and so on.Moreover, its engagement in spatial analysis by collecting and evaluating geographical and nongeographical data widens the employment of the method.GIS can promote making decisions by integrating some geographical skills like GPS and remote sensing [22]. is capability of GIS made it a powerful tool in many branches of science and technology, namely, natural sciences, archeology, engineering, medical, and social sciences [23][24][25].
e combination of MCDA with GIS is an effective tool, and they take advantage of each other [26].e automation, management, and evaluation of spatial data for end users have made GIS an essential player for examining MCDA issues.Nevertheless, increasing GIS applications are called as structures for assisting MCDA problems, and many of them lack the spatial analysis needed by decision makers.MCDA applications offer many skills and measures to help decision makers' preferences.Combination of these methods through a program enabling a user to communicate with a computer delivers the outline of the SMCDA support system.It helps to develop the efficiency of the decision-making by including end users' decisions.Normally, MCDA uses mean or overall data that are uniform in the whole area, which is unlikely in many studies [27].Nevertheless, the geographical locations of alternatives and criterion values are needed in SMCDA [16,28].e GIS and MCDA synthetization began at early 90s.Carver [29] has described the basics and restrictions of merging them.For the comprehensive literature, some literature is available for interested readers [8,15,30].Environmental quality is beneficial to determine the present position of sustainable development and asserts the corresponding countermeasures to the protection of environment.
is study deals with physical environmental quality of the Denizli (Turkey) municipal area as a part of urban environmental quality.
e topography that designates particular natural hazard risks and some urbanization parameters is employed by using SMCDA and GIS. e results are momentous to assess the current status and to mitigate the related issues.

Site Characteristics
Denizli municipal area is one of the highly developed provinces and located at SW Turkey (inset of Figure 1).e area is in a graben area which is bounded by high mountains both in the north and in the south.e downtown is close to the northern part of the graben, and dominant slope direction is from north to south as illustrated in Figure 1.
Environmental assessment zoning maps of the municipal areas are based on the particular natural hazard risks and some urbanization parameters, namely, altitude, road density, green field density, and traffic noise.e altitude in the area controls both sediment size and flooding risk, and it is engaged as a natural hazard parameter.e sediment size distribution is controlled by slopes [31].
e larger sediments have higher strength than the smaller ones as seen in Figure 2 [32].ey cause less damage during an earthquake.Lower altitudes are also under the flooding risks inherently.
e altitude values are obtained from the digital elevation 2 Advances in Civil Engineering model (DEM) of Denizli.e elevation and grain size of the sediments are getting smaller from south to north.Green eld density and road density are employed to re ect the urbanization parameters.Because of the data location density, a square grid plan with 500 meters in size is established and every grid is considered for the calculation.e green elds are marked as blocks in the development plans.To nd out the green eld density, the area of green eld blocks is proportioned to the area of building blocks in each grid.Similarly, the total road area in a grid cell is proportioned to the block area.e tra c noise is one of the major parameters for life quality [33], and it is the fourth parameter in this study.
e tra c noise data are mainly based on the Cetin study [34].
It has not covered the whole study area, and the incomplete data were supplemented later.is study has engaged the weighted grading as a MCDA.e criteria were compared with respect to their weights after identifying them.In order to implement it, a pairwise comparison matrix composed the relative weights.en, the generated data were normalized, and the eigenvector associated with the maximum eigenvalue of the ratio matrix.MapInfo ® was engaged to analyze and imagine the spatial data.

Analyses by MCDA
e employed parameters are, namely, altitude, road density, green eld density, and tra c noise.ese data are divided into ten groups and graded by using these groupings.e altitude, road density, green eld density, and tra c noise values and grades are given in Table 1.e altitude varies from 250 meters to more than 475 meters (Figure 3).Higher    Advances in Civil Engineering altitudes have some advantages in terms of natural risks like ooding.Moreover, soil types at higher locations are coarser than that at the lower ones.It means coarser soils present better seismic characteristics than the ne soils.After all, higher altitudes are more preferable, re ect less natural hazard risk, and have higher grades.e road density is intensive at southern and northern parts of the area (Figure 4).Higher road density represents easy access and more parking spaces in the Turkish case, and it is desirable.erefore, higher values have high grade points.Similarly, high green eld density expresses better environmental conditions.e green eld density of the area is illustrated in Figure 5. e vast majority of the municipal area has very low green elds, less than 10%.Limited areas at western and southern parts of the area have more than 20% green area density.Noise displays poor environmental settings.
e lowest noise level measured in the area is 60 dB, while the highest one goes up to 90 dB (Figure 6).e central, southern, and northern fragments of the municipal area are noisier than the other parts.Especially, western and eastern districts are quieter, and they have noise level less than 70 dB.
e intensity scale submitted by Saaty [14] was employed in the study, and the measures were de ned based on the professional knowledge of the authors.Table 2 lists the formed ratio matrix and the intensity importance values.Normalizing the weights was done by dividing the weights by the sum of the column (Table 3).Average of the cell in the rows gave the priority vector.e ratio matrix and priority vector were multiplied to nd out D vector that was divided by the priority vector to get the eigenvector.
e validation of the consistency of the results is done by the "consistency ratio (CR)." e maximum value of the CR is 0.10.When it is higher than that value, the results are assumed to be consistent and should be revised.Randomness Index (RI) and the maximum eigenvalue (Λ max ) were calculated to obtain the CR.
Randomness Index (RI) is the number of criteriondependent values (n), and Saaty [12] has proposed it as 0.9.
e ratio of Consistency Index (CI) to Randomness Index (RI) is called "consistency ratio (CR)," and it is equal to 0.04.Multiplying the eigenvector of each criterion to the designated points of this criterion in the alternatives gives the weighted value.e ultimate value at the localities was calculated by adding these values at each point, and the nal thematic map of environmental assessment is accomplished by these data.

Discussion and Conclusions
Several disciplines that have di erent approaches and methods deal with the environmental quality phenomenon.
ese branches vary from engineering to health, sociology, economy, and so on, and they have their own approaches and valuations.Furthermore, assessment of some criteria might be subjective when the perception of the people is concerned.Ironically, the models and/or evaluations should re ect the general perception.Some problems became visible throughout the study.e rst problem to tackle was the choice of the MCDA method.It is well known that MCDA procedures cause dissimilar results. is study has engaged AHP as it o ers a structured, yet exible method to decision-making.Additionally, AHP permits to control the inconsistency of the value judgements.Moreover, the observed data are being employed in a spatial manner.e second and the more critical one was minimizing the risks and cost of   4 Advances in Civil Engineering environmental urbanization while maximizing the public acceptance or not.e results should be compatible with the general perception in the city.e preferences for urbanization quality may be altered by virtue of social, economic, and technological level of the communities.However, globalization eliminates the physical dissimilarities between nations, and multinational companies dominate not only the economic systems but also the lifestyle and cities. is process leads to global hierarchy of cities, which results in increased living standards.Consequently, there are a large number of di erent criteria to evaluate the quality of the urban areas, and the attributes change in time.e studies show that the considered parameters are not the same.ey are infrequently measured by the same units even if they are identical.In many cases, the names of social and political attributes may be misrepresentative [35].
e study has considered some certain natural hazard risks and life quality parameters.e altitude in the study controls the sediment size which is related to strength of the soil as foundation.Moreover, higher soil strength mitigates the earthquake damages.Altitude, naturally, governs the ooding risk of the municipal area.In this case, this criterion covers basic construction requirements.Tra c noise, road density, and green eld density are the most common and problematic parameters in many urban areas like Denizli.Air quality has been added in many cases, but it is not a major problem in this example.
e classi cation techniques frequently use ve clusters from "very pro." to "very con."Obviously, this description gives more detail than the three clusters (good, moderate, and bad).In this study, the weighted values have been divided into ve equal parts, and the following ve zone descriptions have been employed from higher to lower values: (i) Very favorable (ii) Favorable (iii) Moderate (iv) Unfavorable (v) Very unfavorable e distribution of the zones is illustrated in Figure 7. Generally speaking, most of the zones directed in NW-SE direction."Very favorable" and "favorable" zones which have   Advances in Civil Engineering the highest calculated points are located at the south, southwest, and northern parts of the municipal area.ese regions have higher altitude and partly lower road density.e green field density and noise level are at the average values.On the contrary, "very unfavorable" and "unfavorable" zones are mainly located around the central part of the study area.ese two parts, except the northwestern parts, have low altitude, average road density and noise, and too low green field density values.
ese zones involve high flooding and soil amplification risks (high seismic risk), which are unacceptable for an environmental urbanization.
e "very unfavorable" and "unfavorable" zones are mainly used for trading and light industrialized activities.e "moderate" areas lie between these two groups and cover widely in northwestern parts of the study area.
A comparison with multicriteria model results and the perception in the city might be valuable.Ozer et al. [36] has designated the same area on the basis of socioeconomic parameters.e definitions of the AHP model have meaningfully matched with those descriptions.e described zones reflect the general perception in the city, which is the main goal of the study.e central part of the municipal area is depicted as "miserable," while southern and southwestern parts of the study are known as the best part of the living area parallel to the study.
e study proves that the SMCDA can be employed to assess the urban environmental quality perception in a city when the criteria are set well. e method is beneficial to see the present situation, and such a study may trigger the countermeasures to mitigate the related concerns in an administrative manner.

Figure 2 :Figure 1 :
Figure 2: Correlation between the median particle diameter and the angle of shearing resistance [32].

Table 1 :
Considered parameters and grading.

Table 2 :
Relative importance of weightings.

Table 3 :
Normalization and priority vector values of the criteria.