Model of Priority Ranking of Cadastral Parcels for Planning the Implementation of Urban Consolidation

Abstract

The paper proposes a Model of priority ranking of cadastral parcels for planning the implementation of urban consolidation, which is a continuation of the published research on the assessment of fragmentation and assessment bonitet values of cadastral parcels. The research deals with one segment of the Spatial Decision Support System and is one process in the planning of urban consolidation. Comparison criteria were identified for the evaluation and priority ranking of cadastral parcels. The subject of the research is private cadastral parcels in the area of large public project construction. The goal of the research is to find the optimal way to compare conflicting and incomparable criteria for the evaluation of private cadastral parcels and, at the same time, a way of fitting the opinions of stakeholders in the implementation planning process of urban consolidation. Due to the complexity of the task and realizing certain spatial criteria, unique models were developed. Special attention was paid to the participatory approach to problem-solving, in which all groups of stakeholders were identified, and the way of expressing their views was defined. The Complex proportional assessment (COPRAS) method and the Analytic Hierarchy Process method (AHP) methods were used to solve the problem. The defined models were tested in the field of construction of a large public project Campus at the University of Split.

1. Introduction

Urban consolidation (UC), as a spatial planning technique, deals with various problems related to an urban and suburban area, which require the inclusion of influential elements related to spatial, technical, economic, ecological, and social aspects. It is a comprehensive implementation of a more detailed urban plan, which enables planners to create a higher quality plan without taking into account the previous ownership and manner of use. The adaptation of the technique to individual urban spatial planning while respecting its key determinants is certainly one of its essential characteristics. The definition often varies from country to country in which it is applied, i.e., from author to author who deals with the topic in a scientific and professional sense. The basic features refer to the urban development of the area in accordance with the urban plan, with the simultaneous protection of the property of the original owners of the land that enters the process of UC. According to Simpson [1], UC is defined as a policy of planning the arrangement of urban space, the goal of which is to increase the efficiency of existing and future urban land resources, predicting influential elements related to the constant growth of the suburban and urban population. Mihajlović [2] defines UC as consolidation in the function of urban development of the settlement, which shapes construction parcels in the construction area and provides land for the construction of public facilities while simultaneously arranging property-legal relations. Urban consolidation can be defined as a land management tool that helps in the development of urban space with the participation of parcel owners. The main goal is to convert irregularly developed land parcels into parcels defined according to the rules of urban planning. All of the above points to the advantages of using UC as a technique of urban spatial planning, but on the other hand, it is important to point out its disadvantages as well related to technical limitations when managing a large amount of diverse data, economic limitations in defining the way of land redistribution and/or monetary compensation after the process of consolidation, and social limitations due to insufficient transparency of the process as well as non-inclusion of stakeholders in all levels of planning during the implementation of the entire procedure [3]. Archer [4] defined UC as a technique of urban development of space specifically to convert agricultural land into construction land. Given that UC, in addition to the arrangement of parcels intended for residential use, also defines the planned layout of public streets, public utility networks, public areas, and public-use facilities, it provides a physical basis for sustainable urban development. Krtalić [5] presented the procedure for implementing UC in Bavaria regarding the Republic of Croatia and defined UC as a legal instrument for harmonizing private and public interest that is used in the process of arranging construction land where there are no large areas of land owned only one owner, which could be arranged in accordance with the urban development plan (UDP). Agrawal [6] provides an overview of the UC procedure in Asian countries and defines UC as a technique used to improve areas that have started to be settled and developed without planning, uncontrolled settlements with irregular parcel boundaries, and areas with inappropriate living conditions. Urban consolidation is used to develop an urban area without involving the process of land acquisition [7] by uniting all parcels of land that are part of the area of implementation of UC into a consolidation mass and with a new redistribution of land (including monetary compensation) to the original owners of land parcels. UC includes the allocation of areas for the construction of urban infrastructure elements and areas for sale that would cover the costs of its implementation. At the same time, depending on the area intended for public use and the area of each parcel in the consolidation process, the percentage of land with which the owners participate in the development of urban space is determined [8]. The coefficient of reduced land parcels is up to 30%, which is more than in the case of consolidation of agricultural land due to land insurance for public areas and facilities. Although with such a redistribution, the owners of the land after the UC process receive parcels of a smaller area, due to the increase in land prices conditioned by the urban development of the space, the preservation of the financial fairness of the process is satisfied [2].

Research Problem

Over the past 30 years, the Croatian urban area has experienced significant changes, which have had the greatest impact on the reduction of public space. The absence of strategies at the state, county, and/or local level, their obsolescence, sluggishness in implementation as well as the absence of a participatory approach to planning have led to the destruction of urban space. In recent years, attempts have been made to prevent “wild” construction, which is especially pronounced in suburban areas, but the big problem remains to find ways to improve the existing urban environment. Croatian Dalmatian cities share the characteristics of Mediterranean cities. Narrow streets and crowded residential buildings often affect the absence of elements of the urban structure. Their subsequent construction is most often impossible to the extent that it is necessary for the normal functioning of the urban environment. Adaptation, revitalization, and reconstruction of older urban areas are particularly important in terms of reducing pressure in suburban areas. It is especially important to single out the process of realizing a large public project, which most often requires a complete reorganization (renewal) of a certain area. The existing spatial arrangement, which may be the result of the absence of local development plans, as well as illegal construction, does not fit into the implementation plans of usually large public or private projects. These projects refer to the complete urban renewal of a particular area, and in both cases, they require a large financial capacity. Public projects have a mitigating circumstance where the consent of private owners is not required for their initiation. Although the starting position of private owners for negotiation is reduced, reaching an agreement on allocation is in the interest of all stakeholders involved in spatial renewal processes. In response to the above requirements, which specifically relate to the processes of reorganization of urban and suburban areas to improve individual areas, but also their complete urban renewal, the method of urban consolidation has been recognized in the world, and the planning of its implementation is part of the subject of this research. Studying the available scientific and professional literature, it was observed that there is no single definition of UC that includes one or always the same urban spatial problems. Depending on the spatial specificities that are primarily regarding the specifics of construction, the legislative principles of UC differ from country to country, which is quite important if one wants to define a process that will be applicable and effective. UC is a procedure whose goal is to satisfy the interests of all parties involved in its implementation, which directly indicates the need to include a wider circle of stakeholders in its planning processes. A participatory approach with a special emphasis on the inclusion of private owners in the planning and decision-making process, as well as informing the general public about a particular procedure, is extremely important in societies that are not familiar with the method of UC and who do not trust the state systems. The advantage of UC in realizing a public project can be seen from the perspective of the investor, who is enabled to self-finance the entire process. After the implementation of the allocation of private owners, the part of the land that has not been used for construction can be sold to cover the costs of the procedure, or it can be used for future urban projects. In Croatia, the legal ordinance that regulates spatial planning has been frequently changed for many years, so the concept of UC appeared periodically in them. However, regardless of the existing legislation, it has not taken root in practice as a method of spatial planning. There are several reasons, from the law that was not fully adapted to the principles that would be applied to the situation in Croatian cities to the specific characteristics of the society that reluctantly accepts this method. For these reasons, although it is very important to study global and European laws and examples of their implementation, it is necessary to get to their adaptation to Croatian conditions and to the problem of educating the wider masses and their inclusion in decision-making processes. Finally, it can be concluded that UC should be seen as the key to sustainable urban development. It creates the conditions for building a strong urban environment that follows dynamic movements in an urban area and controls its development through the synergy of equal construction of all elements of urban infrastructure. Strong local institutions and a good legal framework are the conditions for its effective implementation, and its self-sustainable character defines a fair distribution of financial participation, as well as the profit that results from it.

The research proposed in this paper deals with one component of the Spatial Decision Support System (model within the Model Management Subsystem), and it is one process in the planning of UC. The final goal is to develop an SDSS that will provide effective support in UC planning and define processes within the system that monitor the dynamics of the project with regard to its technical, economic, spatial, and social aspects. This research is primarily focused on the identification of technical and spatial aspects. Spatial limitations affect the definition of the initial set of alternative solutions (private cadastral parcels) that are evaluated and compared to define their priority ranking for inclusion in the processes of implementing UC. It is necessary to find an optimal way of comparing criteria for evaluating alternatives that are incomparable and conflicting and, at the same time, a way of fitting the opinions of stakeholders about their importance for their particular group. Due to the complexity of the task and realizing certain spatial criteria, unique models were developed. Special attention was paid to the participative approach to problem-solving, in which all groups of stakeholders were identified, and the way of expressing their views was defined. Although the involvement of stakeholders often increases the volume of preparatory and implementation actions and complicates and prolongs the entire procedure, their awareness of all steps, as well as respect for their views in actions that directly affect them, creates a favorable atmosphere for the needs of the implementation of current and all future UC procedures. All of the above is included in a unique model developed for the first time as part of this research. The model is flexible in terms of the possibility of its adaptation to different spatial problems. As part of this research, it was validated in the field of realization of a large public project, which primarily affects the definition of the specific procedure of UC—Urban Renewal—and then also the way of including specific determinants and goals of the project itself, for which the urban development plan (UDP) has already been adopted and which needs to be set as the basic basis for planning the implementation of the UC procedure. Urban renewal enables the complete transformation of already-built urban space. The expansion and adaptation of the UC procedure to the current urban problems of Croatian and Dalmatian cities will create quality foundations for its implementation in the future, which will enable the implementation of projects in an optimal way with the aim of improving the quality of life of the city’s population.

2. Literature Review

Although conventional methods are still used in the planning process of UC today, due to the increase in the amount of data that needs to be analyzed, the number of factors, and the involvement of more and more stakeholders in decision-making processes, there is a need for systems that will provide effective support to decision-makers in UC planning. In the following, previous scientific research that applied various decision support tools in the implementation of procedures in urban planning, consolidation, and urban consolidation will be presented.

Muller [9] states that UC solves several problems related to an urban area in the Czech Republic. In addition to the basic arrangement of the urban space, it also includes a series of procedures related to the improvement of the existing and the construction of new transport and water infrastructure with a simultaneous awareness of the environmental protection of the space. He states the importance of using GIS when planning consolidation and creating a layer that will be displayed on the geoportal and that provides data for surveyors, planners, farmers, central and local authorities, as well as other interested entities. In their paper, Branković et al. [10] deal with the consolidation of agricultural land and suggest the use of GIS tools to optimize the land assessment process. Furthermore, Tomić et al. [11] and Matijević et al. [12] state the advantages of GIS technologies in automatic processes of mass valuation of real estate in land consolidation procedures. Arciniegas et al. [13] propose the use of multi-criteria analysis methods and systems based on them (Spatial Decision Support System—SDSS) in agricultural land and water management in the Netherlands. Coutinho-Rodrigues et al. [14] identify multiple and conflicting criteria that have different social, economic, and environmental effects and place them to different groups of stakeholders by designing an appropriate SDSS for water supply infrastructure. Both papers are focused on infrastructure, which is important, but only a part of large public projects in urban areas. Furthermore, various applications of decision support in solving various construction and technical problems can be found in the papers [15,16,17,18,19,20,21,22,23].

Demetriou et al. [24] propose and provide a prototype of DSS when planning the implementation of consolidation of agricultural land. The solution lies in the development of an integrated planning system and DSS that will automate the entire process of consolidation and reallocation of land. Uyan et al. [25] also propose the development of an SDSS that includes a model of agricultural land redistribution. The results were compared with conventional methods based on the testing of agricultural production stakeholders. Muchová and Jusková [26] dealt with a participatory approach in the process of land consolidation in the Czech Republic and Slovakia. Stakeholders’ preferences were collected to evaluate the two consolidation procedures using a simple survey questionnaire. In their paper, Cay and Uyan [27] proposed the use of a multi-criteria AHP method to evaluate stakeholder preferences in the land redistribution process. In his dissertation, Marinković [28] dealt with the formation of an optimization model for the selection of municipalities (45 variant solutions) in AP Vojvodina based on 27 established criteria, that is, the selection of cadastral municipalities (5 variant solutions) in the municipality of Apatin based on 14 criteria to define priority locations for initiation of consolidation projects. The priority ranking was determined using MCA methods, while weights were determined by the author based on Saaty’s scale of relative importance. When defining an adequate model, he decided that the final ranking should be obtained by applying at least two or more methods of multi-criteria analysis to achieve a more regular, correct, and objective choice of municipalities, i.e., cadastral municipalities, for the realization of consolidation projects. Tomić et al. [29] investigated the possibility of using official data registers in the land consolidation process. By using MCA methods and comparing seven criteria, they defined priority areas for the implementation of consolidation. Zou et al. [30] used SDSS with integrated component knowledge based on fuzzy logic expert system to assess land consolidation potential based on four identified criteria. The application of fuzzy logic in land redistribution procedures during consolidation can be found in numerous papers [31,32,33,34,35,36]. Cai et al. [37] dealt with defining the framework of multi-criteria analysis of urban-rural land consolidation in the coastal Nantong city, which is undergoing a process of accelerated urbanization. Given that urbanization affects the transformation of rural to urban land and consequently also affects ecological processes, it is necessary to quantify two elements: a comprehensive assessment of the change of rural to urban land that includes four criteria and specific consolidation models applicable to a specific area. Consolidation in rural–urban areas aims, in addition to consolidating land parcels, to protect natural areas through sustainable land use. Multi-criteria analysis was performed separately for rural and urban land in each region of Nantong city, and a consolidation model was proposed for each region. Ališić et al. [38] define the possibilities of using SDSS in UC procedures in Croatia, where the law on UC still does not exist, and the use of mass real estate evaluation when evaluating real estate before and after the UC procedure.

In her dissertation, Kilić [39] developed an SDSS in UC planning. The processes of planning the implementation of urban consolidation are defined in four phases. The research presented in this paper belongs to the third phase, i.e., the implementation procedure where the priority ranking of cadastral parcels that enter the process of UC is determined. For one of the spatial criteria for the evaluation of cadastral parcels, the Model of index fragmentation assessment was developed [40]. The last, fourth phase in planning the implementation of UC deals with the reallocation processes, as part of which the model to assess the bonitet of cadastral parcels (realized as an ES based on the principle of fuzzy logic—[41]), the model for real estate valuation and the model for collecting preferences of private owners were developed.

Most of the available scientific literature is focused on solving problems related to the consolidation of agricultural land. There are many reasons, but certainly, one of them is the complexity of the UC process, for which it is necessary to find ways to include all relevant influences in a system that will provide an efficient solution. The use of DSS and SDSS is also still based on a consolidation of agricultural land, while their application in urban consolidation was found only on a theoretical level or during the process of consolidation and redistribution of cadastral parcels during conversion from rural to urban land. The main reason for the small number of research dealing with the automation and objectification of UC compared to the consolidation of agricultural land is the complexity of the procedure caused by a large number of different influencing parameters. As already mentioned, the research in this paper is primarily focused on the development of one model within the Model Management Subsystem of SDSS. The model was realized using multi-criteria methods. A multi-criteria approach allows consideration of a large amount of data and information defined through criteria that are often conflicting and incomparable, as well as the application of an interdisciplinary approach by involving multiple groups of stakeholders in the decision-making process with different knowledge and preferences. The aforementioned, in addition to providing a new approach to planning the use of existing and future urban land resources and the settlement of property-legal relations, also improves the objectivity and transparency of the entire process.

The development and validation of the basic model, as well as supporting models for the evaluation of criteria according to individual variant solutions, achieves the main goal of this research, which is the priority ranking of urban private cadastral parcels for planning the implementation of UC. This paper presents research that proposes a unique choice of technical and spatial criteria, their evaluation, and comparison by a defined set of private cadastral parcels, all based on a participatory approach. The implementation procedure is one process within the SDSS in planning the implementation of UC to build a large public project. All of the above represents original scientific research, both in terms of model development and in terms of their application.

3. Materials and Methods

The research presented in this paper is part of a large study that is divided into 4 phases of planning the urban consolidation implementation:

1. 

Preparatory procedures—Part 1,

2. 

Preparatory procedures—Part 2,

3. 

Implementation procedures to rank cadastral parcels and define their subsets conditioned by investor constraints,

4. 

Reallocation procedures parcels for determining the reallocation plan.

This research belongs to the 3rd phase of planning the UC. It is important to emphasize that in this paper, the part related to “Defining cadastral parcel subsets conditioned by investor constraints” has been omitted because it is logically connected to the 4th stage of planning and will be presented in the last paper that will include the entire research.

The implementation procedures shown in the flowchart in Figure 1 begin with the definition of the model of goal hierarchical structure (MGHS), followed by determining the weights of the criteria using the adequate model. The ranking of cadastral parcels was carried out by the model for priority ranking of cadastral parcels. In the following, the previously mentioned models will be described, as well as those that support them in Section 3.1, Section 3.2, Section 3.3 and Section 3.4:

(a)

(Model of goal hierarchical structure for planning the implementation of urban consolidation (Section 3.1), which defines the main goal, sub-objectives, and criteria (Model of index fragmentation assessment and Model of intended utility assessment—Section 3.2) necessary for making quality and effective strategic decisions,

(b)

Model of defining weights (Section 3.3),

(c)

Model of priority ranking of cadastral parcels for planning the implementation of urban consolidation (Section 3.4)

3.1. Model of Goal Hierarchical Structure for Planning the Implementation of Urban Consolidation

The model is formed in the shape of a tree of objectives and includes all objectives and criteria necessary for making a quality and effective strategic decision. The goal tree enables an easier and faster understanding of the interconnections between sub-objectives and criteria at the same and different levels. At the top of the hierarchical structure is the main goal, “Planning the implementation of urban consolidation to realize a large public project”, which is divided into two directly supporting sub-objectives of the second level, maximization of technical and maximization of spatial aspects. Both sub-objectives of the second level are further divided into the sub-objectives/criteria at the third level of the hierarchical structure. It can be said that the branching of the goal tree is carried out to a satisfactory level of relevance and measurability of the sub-objectives, which at the lowest level are called criteria. The criteria represent the evaluation parameters of private parcels of land in the research area. It should be emphasized that the main goal and the second level of sub-objectives always remain the same when planning the implementation of urban consolidation to realize a large public project, while the criteria at the third/last level of the GHS can be modified, new ones added or existing ones taken away in relation to the specific problem. The aforementioned general goal, sub-objectives, and criteria ensure the coverage of selected aspects important for achieving the main goal: by maximizing the technical aspects, cadastral parcels and their belonging to an individual sub-project are observed through the analysis of the state of the project components, to optimize the time required for the preparation of project documentation and construction time of an individual sub-project, and by maximizing spatial aspects, parcels are observed through their spatial characteristics to define the evaluation process in relation to their differences from the “ideal” cadastral parcel. Equally, an important segment of spatial indicators is environmental preservation, which is defined through the criterion “Ecological importance”.

Table 1. Label, hierarchy level and target name.

Label	Hierarchy Level	Target Name
MG	1.	Planning the implementation of Urban Consolidation to realize a large public project
SO1	2.	Maximization of technical indicators
SO2	2.	Maximization of spatial indicators
C1	3.	The degree of complexity of the object—the complexity of the architectural structure
C2	3.	Estimated time for construction of the subproject
C3	3.	The degree of readiness of the design and technical documentation for obtaining a building permit
C4	3.	The area of cadastral parcel
C5	3.	Estimation of the intended utility of a cadastral parcel
C6	3.	Estimation of the fragmentation of a cadastral parcel (Parcel Index Fragmentation)
C7	3.	Integration of subprojects in spatial plans in terms of elaboration
C8	3.	Coefficient of the utilization of the subproject
C9	3.	Ecological importance—Environmental conservation

shows the hierarchy of goals, which is divided into three hierarchical levels and was defined to determine the ranking list of cadastral parcels to define the activities of implementing urban consolidation. The basic elements of the goal tree are shown: main goal (MG), sub-objectives (SO) of the first level, and criteria (C1,…, C9). Technical indicators include criteria C1, C2, and C3, while spatial indicators include criteria from C4 to C9.

The formation of a GHS is a key segment of planning the implementation of urban consolidation; therefore, for its definition, the inclusion of relevant stakeholders is of particular importance. At the same time, in defining the second level, an important role is played by experts who, based on existing specific knowledge, can solve new problem tasks. This primarily refers to the consideration of all relevant influences and the shaping of the goal tree in a comprehensive way for its presentation to other stakeholders involved in the decision-making process. Considering the large number of stakeholders with different knowledge, experiences, and preferences, the formation of the GHS is performed through an iterative process during multiple conversations. The main goal refers to the basic research problem. In informal discussions with experts, the second level of GHS was formed and presented to all other stakeholders. Each group of stakeholders is organized in such a way that it has its representative who represents their attitudes during joint meetings with other representatives. In order for a particular criterion to be included in the set of criteria for evaluating alternatives, it must be accepted by all stakeholders/representatives of stakeholders. Special importance in the proposed process of defining the criteria should be given to possible overlapping of their scopes. It is necessary to consider such criteria, additionally, to define one that best describes the problem and assign it to the sub-goal to which they belong thematically the most. The procedure ends when all members of the groups agree on the defined criteria that are adopted as final for the formation of the GHS. As part of this research, four groups of stakeholders were identified, which include representatives of the city administration, representatives of investors of a large public project, representatives of private owners, and experts in the fields of geodesy, construction, architecture, and project management. When forming the latter, the expert group, it is necessary to identify a group that includes experts who are not necessarily scientists but are of particular importance for the above-mentioned planning processes because they have invaluable experience on this topic, and especially on the characteristics of the research area. Each of the mentioned groups consists of several members. In order to achieve a participative approach to decision-making, the informative and active involvement of stakeholders in all levels of planning is extremely important. This increases transparency and the level of trust in the entire process, specifically in the planning of the implementation of the UC in order to realize a large public project. In order to optimize the entire negotiation process with stakeholders, the representatives of the entire group have the task of conducting discussions with other members and conveying joint decisions at meetings with other representatives. Their opinions are based on their solid knowledge of the problem and mutual communication within the whole group.

The next step is the evaluation of cadastral parcels according to all defined criteria and the formation of a decision matrix. Planning the implementation of urban consolidation is strategic planning that includes solving unstructured tasks, for the effective implementation of which it is necessary to create proper higher-level models. For the evaluation of criteria C5 (estimation of the intended utility of a cadastral parcel) and C6 (estimation of the fragmentation of a cadastral parcel), models are created. The model for criterion C6 is elaborated in detail in the paper “Assessing the land fragmentation to planning sustainable Urban Renewal” by authors Kilić et al. [40]. Parcel Index Fragmentation (IFP) is defined based on 4 criteria, and the methods used for determining it are Fuzzy AHP Method (FAHP) [42,43,44,45,46,47,48] and the Simple Additive Weighting Method (SAW) [49].

3.2. Model of Intended Utility Assessment

In addition to evaluating the current state of cadastral parcels, it is equally important to evaluate their future usefulness in the implementation of the project. In doing so, special consideration is given to their intended utility, i.e., spatial belonging to a specific land use according to the development plan. The flow chart is divided into preparatory and implementation procedures, and the implementation steps of each of them are shown in Figure 2. Like the model of index fragmentation assessment, the model of intended utility assessment is based on a preliminary analysis of the urban development plan (UDP) of the research area. According to the use and purpose of the area, it is necessary to identify the basic intended elements, which are the basis for defining the intended classification for the implementation of the model of intended utility assessment.

Although the starting point of the model of index fragmentation assessment and the model of intended utility assessment are the same, it is important to emphasize the difference in the final information obtained from their implementation. The model of index fragmentation assessment shows the relationship of an individual piece of land against the larger whole to which it belongs (spatial element or logical unit). This relationship is defined by the usefulness of a parcel of land or its part for the realization of a particular unit, and it is expressed numerically by the deviation of its characteristics from the characteristics of the “ideal” parcel (the parcel with the most favorable characteristics). On the other hand, in the model of intended utility assessment, each parcel of land is spatially analyzed separately, and the results are expressed through the percentage shares of the areas of the parcels in the future use of the research area.

In addition to the elements according to the use and purpose of the research area, it is necessary to identify two additional categories, land without a purpose and land outside the scope of the large public project for parcels that are partly located outside the scope of the UDP. The next step is to identify parcels of land in the research area to validate the model of intended utility assessment. The last step in the preparatory procedures is the formation of an expert group. The same experts (5 experts from the Faculty of Geodesy, University of Zagreb, and the Faculty of Civil Engineering, Architecture and Geodesy, University of Split) who were engaged in defining the model of index fragmentation assessment were also presented with the problem of defining the model of intended utility assessment. Their professional advice and suggestions were taken into account during its definition. Implementation procedures begin with an intended classification of the use and purpose of the elements in the research area. In the preparatory part, the basic elements were identified, and based on them, the basic and detailed classifications were defined, which is the basis of the implementation of the model of intended utility assessment. The classification is of a general form and is subject to modifications depending on the spatial development plan and the subjective assessment of the stakeholders involved in its definition.

The next two steps take place simultaneously: the first step refers to the spatial analysis, which provides a statement of the cadastral parcels through the percentage shares of the parcel parts areas according to each use and purpose in the future project, while the second step is defining the importance of use and purpose of the elements in relation to the priorities in the project implementation. Defining the relative importance of elements is certainly the most sensitive and demanding part of this model. When defining them, in addition to taking into account their mutual relationship defined through construction priorities, it is also necessary to take into account other relevant influences (examples are parts of the cadastral parcels that are already on built elements and for which the ownership issue has not been resolved). Relative importance is determined by weights, i.e., coefficients in the range of values from 0 to 10. Weight values are normalized by a complex linear transformation according to the range of values with a preference for the largest value [50]:

$$p_j^{\prime }=\frac{p_j^{}-{\min }_j{p}_j^{}}{{\max }_j{p}_j^{}-{\min }_j{p}_j^{}}$$

(1)

where ${\mathit{p}}_{\mathit{j}}^{\mathbf{\prime }}$ is the normalized weighting value for the j-th intended element, ${\mathit{p}}_{\mathit{j}}^{}$ the weighting value for the j-th intended element, $ma{x}_{\mathit{j}}{\mathit{p}}_{\mathit{j}}^{}$ the maximum weighting value, and $mi{\mathbf{n}}_{\mathit{j}}{\mathit{p}}_{\mathit{j}}^{}$ the minimum weighting value.

The final assessment of the intended utility of cadastral parcels for the future realization of the project is obtained by the sum of the products of the normalized weights and the percentage shares of the areas of the cadastral parcels in relation to the future use of the research area:

$$v\left(A_i\right)={{\displaystyle \sum }}_{j=1}^k{p}_j^{\prime }{x}_{ij}$$

(2)

where $\mathit{v}\left({\mathit{A}}_{\mathit{i}}\right)$ is the estimate of intended utility for a variant solution, i.e., a cadastral parcel ${\mathit{A}}_{\mathit{i}}$, ${\mathit{p}}_{\mathit{j}}^{\mathbf{\prime }}$ is the weight normalized value for the j-th dedicated element, and ${\mathit{x}}_{\mathit{i}\mathit{j}}$ the percentage share of the area part of the cadastral parcel ${\mathit{A}}_{\mathit{i}}$ for a particular intended element. The values of the assessment of intended utility range from 0 to 1, where the score 1 is given to the cadastral parcel whose entire area is within the purpose of the research area which received the highest weight (weight 10), and the score 0 is given to the cadastral parcel whose entire area is within the purpose which was assigned the lowest weight of relative importance (weight 0).

3.3. Model of Defining Weights

The weights of the defined criteria were determined using the AHP method. When defining weights, a mutual comparison of elements at the same level of the hierarchical structure of goals is carried out, whereby preferences are expressed with the help of an appropriate scale, better known as Saaty’s scale of relative importance. Considering the multi-criteria approach and the involvement of several groups of stakeholders in the decision-making process, several strategies, or scenarios, were defined. The scenarios were determined in relation to the definition of weights of each group of stakeholders (four scenarios in total), while the last compromise scenario was used to define the final rank of cadastral parcels. When defining the compromise scenario, or more precisely, the compromise weights, the simple arithmetic mean of the weights was chosen according to the preferences of the stakeholders involved in the decision-making process. The reason for choosing to average with the ordinary arithmetic mean is the compromise result in which all input values are equally represented. The defined weights are normalized, and the sum of all the weights of the goals of the same hierarchical level should be 1 (or 100%). The evaluation of cadastral parcels according to all criteria, together with the definition of their weights, are input data in the model of priority ranking of cadastral parcels for planning the implementation of urban consolidation.

3.4. Model of Priority Ranking of Cadastral Parcels for Planning the Implementation of Urban Consolidation

The method used when comparing cadastral parcels for their priority ranking is the Complex proportional assessment (COPRAS) method [51,52,53,54]. In order to rank cadastral parcels to define the priority of their inclusion in the processes of implementing urban consolidation, it is important to determine the criteria for their evaluation (Model of goal hierarchical structure for planning the implementation of Urban Consolidation), to collect data for their evaluation and to determine their relative importance (Model of defining weights). The COPRAS method was first presented in the paper of the authors Zavadskas, Kaklauskas, and Sarka [51]. The description and applications of the COPRAS method can be found in a large number of papers [55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71].

Ranking alternatives by the COPRAS method assume direct and proportional dependence of significance and priority of investigated alternatives on a system of criteria [71]. The mathematical algorithm is defined through seven phases [65,71]:

• Phase 1. Developing an initial Decision Matrix

The decision matrix is as follows:

$$\mathit{D}=[\dots ]$$

(3)

where m is the number of alternatives and n is a number of criteria.

• Phase 2. The normalization of Decision Matrix

In order to compare the ratings of different alternatives, it is necessary to transform them into comparable dimensionless values using percentage normalization:

$$\mathit{x}{\prime }_{ij}=\frac{{\mathit{x}}_{ij}}{{{\displaystyle \sum }}_{\mathit{i}=\mathit{1}}^{\mathit{m}}{\mathit{x}}_{ij}}$$

(4)

where $x_{ij}$ is the performance of the i-th alternative with respect to the j-th criterion, ${\mathit{x}}^{\prime }{}_{ij}$ is its normalized value, and m is the number of alternatives.

• Phase 3. Determining of Weighted Normalized decision matric

The next stage is to determine the Weighted Normalized decision matrix:

$${\mathit{D}}^{\prime }={\mathit{d}}_{ij}={\mathit{x}}_{ij}\times {\mathit{w}}_j,\mathrm{i}=1,2,\dots ,\mathrm{m},\mathrm{j}=1,2,\dots ,\mathrm{n}$$

(5)

• Phase 4. Calculation of Maximizing and Minimizing Index for each alternative

Alternatives need to be defined as Maximizing and Minimizing Index:

$${\mathit{S}}_{+\mathbf{i}}={{\displaystyle \sum }}_{\mathit{j}=1}^{\mathit{k}}{\mathit{y}}_{+ij}\mathbf{,}\mathrm{j}=1,2,\dots ,\mathrm{k}-\mathrm{Maximizing}\mathrm{Index}$$

(6)

$${\mathit{S}}_{-\mathit{i}}\mathbf{=}{{\displaystyle \sum }}_{\mathit{j}=\mathit{k}+1}^{\mathit{n}}{\mathit{y}}_{-ij},\mathrm{j}=\mathrm{k}+1,\mathrm{k}+2,\dots ,\mathrm{n}-\mathrm{Minimizing}\mathrm{Index}$$

(7)

• Phase 5. Calculation of the relative weight of each alternative

Relative weight is calculated as follows:

$${\mathit{Q}}_{\mathit{i}}={\mathit{S}}_{+\mathit{i}}+\frac{\mathit{S}{\_}_{\mathit{m}\mathit{i}\mathit{n}}{{\displaystyle \sum }}_{\mathit{i}=1}^{\mathit{m}}\mathit{S}{\_}_{\mathit{i}}}{\mathit{S}{\_}_{\mathit{i}}{{\displaystyle \sum }}_{\mathit{i}=1}^{\mathit{m}}(\mathit{S}{\_}_{\mathit{m}\mathit{i}\mathit{n}}/\mathit{S}{\_}_{\mathit{i}})},\mathrm{i}=1,2,\dots ,\mathrm{m}$$

(8)

where $\mathit{S}{\_}_{\mathit{m}\mathit{i}\mathit{n}}=\mathit{S}{\_}_{\mathit{i}}$.

• Phase 6. Determine the priority order of alternatives

The priority ranking of alternative solutions is determined based on their relative weight. The alternative with a higher relative weight is ranked higher (has a higher priority), while the alternative with the highest relative weight is the most acceptable.

$${\mathit{A}}^{*}=\left\{{\mathit{A}}_{\mathit{i}}|\mathit{m}\mathit{a}{\mathit{x}}_{\mathit{i}}{\mathit{Q}}_{\mathit{i}}\right\}$$

(9)

• Phase 7. Calculation of Performance Index (Pi) Value for each alternative

Pi values are calculated as follows:

$$\mathrm{Pi}=\frac{{\mathit{Q}}_{\mathit{i}}}{{\mathit{Q}}_{\mathit{m}\mathit{a}\mathit{x}}}\times 100\%$$

(10)

where a larger Pi indicates a better-ranked alternative.

4. Results

4.1. Preliminary Analysis of the Study Area

The proposed models were tested in the area of construction of a large public project on the Campus, University of Split, Republic of Croatia (Figure 3). The specificity of the application of the proposed model to the selected case study is that its implementation has already begun. The aforementioned required additional modification of the model, i.e., finding a way to fit it into already started processes. The basis of the spatial analysis that defined the input data for the proposed models is the overlay of the official cadastre data and UDP of the Campus, University of Split (Figure 3). The UDP defines the contents within the Campus (subprojects): spatial units related to faculty buildings and other facilities in the function of the University, traffic infrastructure, and green areas, as well as the methods and conditions of their construction. The research covered the mentioned subprojects, the realization of which was not carried out, nor was the way of their realization planned.

At the very start, it is necessary to carry out a spatial analysis based on official cadastral data and a UDP for the Campus construction area. The main limiting factor is the private ownership of cadastral parcels, which is why they were considered alternative solutions. To a number of selected criteria and their importance (weights), it is necessary to define the order of their inclusion in the urban consolidation processes. Figure 4 shows the UDP of the Campus project. The numbers in the figure indicate the spatial placement of current and future sub-projects related to spatial units. The ownership of cadastral parcels is defined by different colors, and of special importance for this research are private cadastral parcels painted in red. They define the alternative solutions of this research.

4.2. Validation of Model of Goal Hierarchical Structure

The validation of the model of goal hierarchical structure for planning the implementation of urban consolidation was carried out according to its theoretical elaboration presented in Section 3.1. The implementation procedures of urban consolidation planning begin with the formation of a goal hierarchical structure. The hierarchical structure is formed in the shape of a tree with three levels, where the last level is represented by the criteria defined for evaluating the initial set of variant solutions, i.e., cadastral parcels. The following

Table 2. Criteria description and technique for evaluation.

Label	Short Description of Criteria and Technique for Evaluation of Investment Solutions	Min/ Max
C1	Given that cadastral parcels spatially often belong to several intended elements, the assessment is defined according to each part of the purpose (the part of an area of an individual cadastral parcel) and the degree of complexity of an individual object (Regulation on Service Prices—[72]) and weight according to the element (buildings—weight 5—roads—weight 3—green areas—weight 1). The final rating of each cadastral parcel is obtained by the sum of the ratio products of the same purpose cadastral parcel area to the total cadastral parcel area with the coefficient of the complexity degree product of the object and the weight according to each element.	Min
C2	The construction time of the buildings during the realization of spatial units was estimated according to their price, number of floors, area and comparison with real examples. Equally, the estimated construction time of traffic and pedestrian roads as well as green areas is 100 m2 in 3 days. The time required for the construction of an individual object is given in units of days. As in the case of criterion C1, the final assessment of each cadastral parcel is obtained by the sum of the ratio products of the same purpose cadastral parcel area to the total cadastral parcel area with the coefficient and the estimated construction time.	Min
C3	The degrees of readiness of the design and technical documentation were defined and weights were assigned to them: there is no documentation (weight 0), there is a conceptual solution (weight 1), there is a conceptual project (weight 2), there is the main project, but no building permit has been obtained (weight 3 ), there is the main project with a building permit (weight 4), there is an executive project (weight 5). The final assessment of each cadastral parcel is obtained by the sum of the ratio products of the same purpose cadastral parcel to the total cadastral parcel area with the weight of the degree of completion of the design and technical documentation.	Max
C4	The area of the cadastral parcel is defined according to official cadastre and land register data and is expressed in square meters.	Min
C5	The criterion is defined by the model explained in Section 3.2. called the Model of intended utility assessment.	Max
C6	The criterion is defined by the Model of index fragmentation assessment [40]. Values of the final assessment of the cadastral parcel fragmentation used for their priority ranking (Parcel Index Fragmentation) are provided in Table A1, in the Appendix A.	Max
C7	A weight of 0 was added to subprojects that were not included in the spatial plans, while a weight of 1 was added to the included subprojects.	Max
C8	The utilization coefficient is defined according to the method and conditions of construction of the UDP—Campus project, University in Split. The final rating of each cadastral parcel is obtained by the sum of the ratio products of the same purpose cadastral parcel area to the total cadastral parcel area with the utilization coefficient.	Max
C9	The criterion is defined according to the share of green areas in relation to the total area of an individual subproject—the coefficient of ecological importance. The final rating of each parcel of land is obtained by the sum of the ratio products of the same purpose cadastral parcel area to the total cadastral parcel area with the coefficient of ecological importance.	Max

shows the criteria with their evaluation method and the definition of min/max.

It should be emphasized that the same form of hierarchical structure can be used for the urban consolidation of another research area, but it is important to modify, add or remove some of the defined criteria depending on the needs of the task itself.

4.3. Validation of Model of Intended Utility Assessment

The model of intended utility assessment evaluates the usefulness of an individual cadastral parcel for the future realization of the project. Based on the analysis of the spatial belonging to a particular future purpose, its intended utility is assessed, which is defined as one of the spatial criteria in the Model of goal hierarchical structure. As already stated, after the definition and description of the research problem, the next step of the preparatory procedures continues with a preliminary analysis of the use and purpose of the area of the UDP Campus, University of Split. The scope of the Campus area is determined, and further analysis identifies the basic elements of the use and purpose, as well as all the cadastral parcels that spatially belong to the research area. The set of cadastral parcels for validation includes 62 private cadastral parcels located in a defined area. The last step in the preparatory procedures refers to the formation of an expert group. Consulting with experts in the field of research is an extremely important step in defining spatial models that have a subjective character. In most cases, the opinions of the experts are very similar, but the small differences in their views on the same problem are extremely important to make the solution, in this case, of spatial problems as objective as possible.

The first step of the implementation procedures refers to the basic and detailed classification of elements of use and purpose according to the UDP of the Campus, University of Split. The implementation of the model can be carried out according to both basic and detailed intended classification. Although the implementation would be much simpler and faster by taking the basic classification as a basis for analyzing the spatial belonging of cadastral parcels to a particular spatial purpose, precisely because of the specificity of the Campus construction project, the realization of which takes place in several phases where it is important to determine the dynamics of its realization, it was decided to use the detailed intended classification that determined the construction priorities of each element in the scope area. The following two steps are performed simultaneously; the first refers to the spatial analysis of each cadastral parcel separately, the result of which is its statement through the percentage shares of the areas of its parts according to each use and purpose in the Campus project, while the second refers to defining the importance of the elements of use and purpose to the priorities in the realization of the project. In

Table 3. Intended classification of elements according to the UDP of the Campus of the University of Split.

Basic Intended Classification	Detailed Intended Classification	Weight of Relative Importance
Buildings		10
Primary network roads	City road (CR)	0.5
	Collector road (CLR)	5.5
Secondary network roads	Access road (AR)	4.5
	Other roads (OR)	3
Other roads	Main pedestrian road (MP)	4
	Other pedestrian roads (OP)	3
	Parking lots (PL)	3.5
Green areas		1
No purpose		0
Outside the scope of the project		0

, the basic and detailed intended classification and the weights of their relative importance assigned to individual uses of the research area are given. For planning the implementation of a large public project, the essential characteristic of which is the technical limitation that determines the dynamics of construction, a detailed intended analysis of the construction area is very important. Weights of relative importance for each purpose are given in the range of values from 0 for areas for which there is no purpose and outside the scope of the project to 10 for areas of future buildings.

As can be seen, a very small weight was given to the city road. The reason is that a certain number of private cadastral parcels have been identified in the Campus area, which is partly located on already built spatial elements, and among them are cadastral parcels on the city road called “Matica hrvatska” for which the ownership issue has not yet been resolved. Cadastral parcels whose entire area is located on already built elements were not used when defining the set of private cadastral parcels. On the other hand, those cadastral parcels that were only partially located in the built-up area according to the UDP of the Campus, while the other still needs to be realized, were taken into account during the validation of this model, and also for the later priority ranking of cadastral parcels for urban consolidation planning. The built-up part of all such cadastral parcels is referred to as the city road “Matice Hrvatske”, and for this reason, a weight of 0.5 was assigned to that intended element.

In

Table 4. Statement of the cadastral parcels through the percentage shares of the cadastral parcel parts areas according to each use and purpose in the Campus project of the University of Split.

ID	Area (m2)	Constraction Utility	Transportation Utility							Green Areas	No Purpose	Outside the Campus
			Primary Network Roads		Secondary Network Roads		Other Roads
			CR	CLR	AR	OR	MP	OP	PL
Weight		10	0.5	5.5	4.5	3	4	3	3.5	1	0	0
Norm.weight		1	0.05	0.55	0.45	0.3	0.35	0.4	0.3	0.35	0.1	0
6505/1	124	0	0	0.15	0	0	0	0	0.85	0	0	0
6505/2	502	0	0	0.80	0	0	0	0	0.20	0	0	0
6541/1	307	1.00	0	0	0	0	0	0	0	0	0	0
6545	547	0.63	0	0	0.29	0	0	0	0.08	0	0	0
6541/2	158	0.14	0	0	0.62	0	0	0	0.24	0	0	0
6523	371	0.69	0	0	0	0	0	0.31	0	0	0	0
6536/2	526	0.52	0	0	0	0.17	0	0	0.18	0	0.13	0
6535/1	694	1.00	0	0	0	0	0	0	0	0	0	0
6535/2	699	1.00	0	0	0	0	0	0	0	0	0	0
6535/3	702	1.00	0	0	0	0	0	0	0	0	0	0

, a statement of cadastral parcels is presented through the percentage shares of its parts according to the future use of the area. For clarity, the results are shown for 10 parcels of land. Cadastral parcels that are partially located within the area of the Campus, and the area of the part outside the Campus does not exceed 400 m², were validated in their entire area (this provision leaves the possibility that their owners decide otherwise, and in that case, only their area part within the Campus was considered). Such parts of the cadastral parcels were treated in the same way as the areas within the Campus for which the purpose was not defined, and accordingly, they were assigned equal weights of importance. In addition to showing the percentage shares of cadastral parcel parts, weights of relative importance and their normalized amounts are also shown. The weights of relative importance were normalized by complex linear transformation according to the range of values with a preference for the highest value. The reason is that it was decided that the intended assessment utility will be given in the amount of 0 to 1, where a score of 1 is assigned to a cadastral parcel that is entirely located in the area for the construction of future buildings, while a score of 0 is assigned to a cadastral parcel that is located in an area with no purpose. Accordingly, the normalized weight of relative importance for areas of future construction should be equal to 1, while on the contrary, it should be 0 for areas without purpose.

The final intended utility assessment of cadastral parcels for the future realization of the project is expressed by the sum of the products of normalized weights and percentage shares of the areas of cadastral parcels parts according to individual purpose and is shown for all 62 parcels of land in

Table 5. Evaluation of the intended utility of cadastral parcels.

ID	IU	ID	IU	ID	IU	ID	IU
6505/1	0.3363	6565/1	10.000	6598/14	0.3000	6565/10	10.000
6505/2	0.5002	6565/2	0.0600	6598/15	0.2267	6565/11	0.6613
6541/1	10.000	6565/3	0.4386	6528/1	10.000	6565/12	10.000
6545	0.7858	6565/4	0.3868	6528/2	10.000	6565/13	0.8696
6541/2	0.4905	6565/5	0.5017	6528/3	0.4053	6536/1	0.7622
6523	0.8140	6565/6	0.9620	6528/4	10.000	6519	0.9807
6523	0.6384	6565/7	0.9501	6528/5	10.000	6518	0.3475
6535/1	10.000	6537/1	10.000	6528/6	10.000	6515/2	0.3477
6535/2	10.000	6633/1	0.4319	6528/7	0.3000	6515/3	0.6061
6535/3	10.000	6633/2	0.0500	6528/8	0.3000	6565/14	0.7757
6566/2	0.8151	6542/1	0.9494	6513/1	10.000	6552/2	0.4379
6550	0.9316	6542/2	0.4584	6513/2	0.3000	6566/3	0.3500
6543	10.000	6551/3	10.000	6538/1	10.000	6552/3	0.0246
6551/1	0.9066	6551/2	10.000	6539/1	0.4642	13662/2	0.0094
6516	0.4718	6538/2	10.000	6539/2	0.3967
6520	10.000	6565/8	10.000	6565/9	10.000

.

The values of the intended utility of private cadastral parcels in the area of the Campus of the University of Split range from (13662/2) = 0.0094 as the minimum value (the cadastral parcel with the lowest estimate of the intended utility) to 1000 as the maximum value of the intended utility (cadastral parcels that their entire area is located in the area of future construction of facilities within the Campus). The maximum estimated value of the intended utility has 22 of 62 cadastral parcels (approximately 35% of all cadastral parcels), while more than half, more precisely 39 of 62 cadastral parcels (approximately 63% of all parcels), have an estimated intended utility greater than 0.5. This kind of information also points to the fact that the majority of private cadastral parcels are located on future building construction, which can additionally affect the extension of time for their realization. The obtained values of the intended utility were used in the later calculation for the final ranking of cadastral parcels in the planning of urban consolidation.

The spatial distribution of private cadastral parcels in the construction area, together with their intended utility assessment, are shown in Figure 5. The range of values of intended utility is shown by a gradation of blue color (light blue tones show cadastral parcels with relatively low values of the intended utility assessment, while dark blue tones indicate cadastral parcels whose entire area or most of it is located in the area of future construction of buildings).

4.4. Validation of Model of Defining Weights

Defining the weights of the criteria was carried out using the AHP method and Saaty’s scale of relative importance. In

Table 6. Criteria weights for four scenarios obtained by the AHP method for each group of stakeholders and weights of the fifth compromise scenario.

ID	Criteria Weights for Stakeholder Groups
	University	Private Owners	City Administration	Experts	Compromise Weights
	(SC 1)	(SC 2)	(SC 3)	(SC 4)	(SC 5)
C1	13	14	10	18	13.75
C2	13	14	10	18	13.75
C3	13	14	10	18	13.75
C4	8	14	8	6	9.00
C5	15	11	8	9	10.75
C6	10	11	8	7	9.00
C7	12	8	8	9	9.25
C8	6	7	30	9	13.00
C9	10	7	8	6	7.75
Sum (Σ)	100.00	100.00	100.00	100.00	100.00

, the weights of nine criteria for each scenario, including the compromise scenario, are shown. The fifth compromise scenario is defined by the arithmetic mean of the weight criteria of the last level of the hierarchical structure.

4.5. Validation of Model of Priority Ranking of Cadastral Parcels

The evaluation of cadastral parcels according to the defined criteria is shown in

Table 7. The results of the evaluation of cadastral parcels according to defined criteria.

ID	C1	C2	C3	C4	C5	C6	C7	C8	C9
6505/1	3.44	34.57	0.00	124	0.34	0.63	1.00	1.00	0.00
6505/2	5.40	29.15	0.00	502	0.50	0.77	1.00	1.00	0.00
6541/1	2.74	1095.00	0.00	307	1.00	0.30	0.00	3.60	0.25
…	…	…	…	…	…	…	…	…	…
6566/3	6.00	51.84	0.00	82	0.35	0.41	1.00	1.00	0.14
6552/3	3.00	16.50	0.00	22	0.02	0.36	1.00	1.00	0.00
13662/2	3.00	16.50	0.00	159	0.01	0.30	1.00	1.00	0.00

in the form of a decision matrix (full data are provided in

Table A2. The results of the evaluation of cadastral parcels according to defined criteria (extended version of Table 8).

ID	C1	C2	C3	C4	C5	C6	C7	C8	C9
6505/1	3.44	34.57	0.00	124	0.34	0.63	1.00	1.00	0.00
6505/2	5.40	29.15	0.00	502	0.50	0.77	1.00	1.00	0.00
6541/1	2.74	1095.00	0.00	307	1.00	0.30	0.00	3.60	0.25
6545	5.55	65.71	0.57	547	0.79	0.41	1.00	0.46	0.60
6541/2	1.35	194.84	3.10	158	0.49	0.37	0.65	1.90	0.23
6523	15.66	523.01	0.00	371	0.81	0.48	0.31	4.17	0.35
6536/2	11.19	584.50	0.00	526	0.64	0.64	0.48	2.87	0.30
6535/1	20.00	1095.00	0.00	694	1.00	0.22	0.00	3.60	0.25
6535/2	20.00	1095.00	0.00	699	1.00	0.20	0.00	3.60	0.25
6535/3	20.00	1095.00	0.00	702	1.00	0.26	0.00	3.60	0.25
6566/2	12.08	313.25	0.01	3700	0.82	0.74	1.00	2.68	0.57
6550	2.36	82.30	0.16	572	0.93	0.38	1.00	0.24	0.84
6543	6.80	90.00	0.00	449	1.00	0.44	1.00	0.14	0.95
6551/1	2.37	79.70	0.14	378	0.91	0.46	1.00	0.27	0.81
6516	7.17	216.46	0.00	220	0.47	0.51	0.75	2.13	0.12
6520	20.00	730.00	0.00	501	1.00	0.46	0.00	5.60	0.50
6598/14	3.00	61.41	0.00	28	0.30	0.73	1.00	1.00	0.00
6598/15	4.96	37.87	1.09	318	0.23	0.26	1.00	1.00	0.11
6528/1	20.00	730.00	0.00	479	1.00	0.46	0.00	5.60	0.50
6528/2	20.00	730.00	0.00	185	1.00	0.36	0.00	5.60	0.50
6528/3	6.20	70.61	0.00	621	0.41	0.52	0.99	1.07	0.01
6528/4	9.49	1095.00	5.00	110	1.00	0.76	1.00	4.00	0.10
6528/5	3.00	1095.00	5.00	35	1.00	0.48	1.00	4.00	0.10
6528/6	16.02	730.00	3.00	816	1.00	0.96	1.00	5.20	0.20
6528/7	4.96	19.01	0.00	374	0.30	0.85	1.00	1.00	0.00
6528/8	3.40	11.43	0.00	15	0.30	0.37	1.00	1.00	0.00
6513/1	20.00	730.00	0.00	23	1.00	0.29	0.00	5.60	0.50
6513/2	5.09	19.64	0.00	23	0.30	0.39	1.00	1.00	0.00
6538/1	19.35	1095.00	0.00	832	1.00	0.38	0.00	3.60	0.25
6539/1	7.33	795.35	2.64	288	0.46	0.50	0.27	2.89	0.09
6539/2	6.65	977.27	1.74	1220	0.40	0.60	0.11	3.32	0.20
6565/1	16.38	41.50	0.00	884	1.00	0.42	1.00	3.82	0.55
6565/2	2.14	7.64	3.61	486	0.06	0.52	1.00	0.14	0.25
6565/3	4.95	37.47	0.00	284	0.44	0.37	1.00	1.43	0.20
6565/4	5.18	11.62	0.00	284	0.39	0.44	1.00	1.20	0.20
6565/5	4.49	507.59	0.44	626	0.50	0.47	1.00	1.70	0.22
6565/6	9.16	690.76	0.00	627	0.96	0.44	1.00	3.36	0.45
6565/7	11.02	681.15	0.00	1155	0.95	0.50	1.00	3.32	0.46
6537/1	20.00	1095.00	0.00	841	1.00	0.29	0.00	3.60	0.25
6633/1	3.82	229.97	0.17	226	0.43	0.42	1.00	1.41	0.53
6633/2	0.00	0.00	5.00	67	0.05	0.43	1.00	0.00	0.00
6542/1	9.93	84.06	0.00	263	0.95	0.41	1.00	0.20	0.90
6542/2	2.74	28.76	3.53	160	0.46	0.48	1.00	0.78	0.28
6551/3	2.00	90.00	1.00	141	1.00	0.35	1.00	0.14	0.95
6551/2	2.00	90.00	1.00	240	1.00	0.35	1.00	0.14	0.95
6538/2	20.00	1095.00	1.00	832	1.00	0.37	0.00	3.60	0.25
6565/8	20.00	178.87	0.00	302	1.00	0.41	1.00	2.85	0.90
6565/9	16.34	463.90	0.00	310	1.00	0.37	1.00	3.65	0.61
6565/10	6.90	547.50	0.00	345	1.00	0.36	1.00	3.90	0.52
6565/11	3.41	223.90	0.62	401	0.66	0.45	1.00	2.38	0.29
6565/12	16.81	730.00	0.00	401	1.00	0.38	1.00	3.50	0.45
6565/13	12.38	468.11	0.24	161	0.87	0.28	1.00	3.32	0.43
6536/1	11.38	735.31	0.00	926	0.76	0.60	0.34	3.53	0.18
6519	19.53	710.88	0.00	218	0.98	0.41	0.03	5.47	0.49
6518	4.15	82.24	0.00	59	0.35	0.58	0.93	1.31	0.03
6515/2	3.00	95.81	0.00	44	0.35	0.38	0.93	1.25	0.04
6515/3	8.29	347.01	0.00	263	0.61	0.73	0.56	2.62	0.24
6565/14	3.33	365.69	0.00	103	0.78	0.32	1.00	2.91	0.40
6552/2	8.43	219.33	0.62	1319	0.44	0.63	1.00	1.68	0.14
6566/3	6.00	51.84	0.00	82	0.35	0.41	1.00	1.00	0.14
6552/3	3.00	16.50	0.00	22	0.02	0.36	1.00	1.00	0.00
13662/2	3.00	16.50	0.00	159	0.01	0.30	1.00	1.00	0.00

, in Appendix A). The decision matrix consists of nine columns (criteria) and 62 rows (variant solutions, i.e., cadastral parcels).

The calculation of phase seven of the COPRAS method is the Performance Index (Pi) for each cadastral parcel, which defines their priority ranking. The results are given in

Table 8. Performance Index (Pi) for cadastral parcels.

ID	PI	ID	PI	ID	PI	ID	PI
6528/8	100.0000	13662/2	13.0632	6565/2	7.0312	6565/5	4.5559
6552/3	75.8721	6565/13	12.1269	6541/1	7.0146	6528/3	4.1389
6513/2	65.7766	6551/2	10.4126	6551/1	6.8994	6565/1	4.0836
6598/14	60.0375	6528/2	10.1602	6565/11	6.6572	6538/2	4.0834
6515/2	40.2555	6633/1	9.9001	6523	6.4626	6535/1	3.8416
6633/2	33.9001	6516	9.6514	6528/7	6.4214	6535/2	3.8184
6528/5	31.0930	6519	9.2494	6528/6	6.2409	6535/3	3.8052
6518	30.9749	6542/1	8.8116	6565/12	6.2400	6539/2	3.7308
6513/1	27.7372	6539/1	8.7546	6543	5.9926	6536/1	3.5303
6566/3	22.9246	6515/3	8.4933	6528/1	5.5454	6538/1	3.4994
6565/14	18.4110	6565/3	7.9921	6520	5.4603	6565/7	3.4540
6528/4	17.2950	6565/4	7.9919	6545	5.2751	6537/1	3.4359
6505/1	16.6295	6565/8	7.9378	6505/2	5.1441	6552/2	3.1009
6551/3	15.9376	6598/15	7.7116	6550	5.0640	6566/2	2.3817
6542/2	15.4481	6565/9	7.6539	6536/2	5.0261
6541/2	15.0165	6565/10	7.2617	6565/6	4.7918

.

Figure 6 shows the spatial distribution of private cadastral parcels and their performance index (PI) obtained by the COPRAS method. According to the obtained PI results, the cadastral parcels are grouped into three sets, as shown in Figure 6 (PI = 0.00–10.00 colored in red, PI = 10.01–20.00 colored in yellow, PI = 20.01–100.00 colored in blue). As can be concluded from the range of values, 42 out of 62 particles have extremely low PI values (less than 10). Only 10 parcels have a PI value greater than 20. All these parcels have an extremely small area (defined by spatial criterion C4), which separates them from the rest of the cadastral parcel set according to the final assessment.

5. Conclusions

The models proposed in this research show a complex decision-making process when solving the unstructured task of planning the urban consolidation implementation to realize a large public project, in the specific case of the Campus, University in Split. The models support the planning processes of urban spatial management in a way that enables the maximization of the positive technical and spatial impacts of large public projects on the local community. The proposed approach is easily adaptable to other spatial tasks by adapting the base elements with a special emphasis on the model of goal hierarchical structure (MGHS), the formation of which includes all relevant groups of stakeholders necessary for the implementation of the research. In particular, it is necessary to highlight the advantages of the model when successfully mastering the processing of a large amount of data, from which often conflicting and incomparable comparison criteria arise, and bringing them into relation with the preferences and different background knowledge of stakeholders in the decision-making process, all while respecting scientific and professional knowledge. The proposed model is unique and easy to apply and adapt and improves the processes of making quality strategic decisions by moving the traditional boundaries between governing bodies on the one hand and scientists and experts on the other. The structural concept of the proposed models is easy to understand and formed in a way that enables the inclusion and participation of the local community, which is directly affected by the decisions made. Informing the general public is of key importance in gaining trust in the proposed processes, and the identified guidelines for future research with the possibility of adding, removing, or modifying the proposed models create a quality basis for managing the development of urban space in the future.

A model of priority ranking (MPR) of cadastral parcels was implemented, which was used to obtain a ranking list of cadastral parcels according to priority for the implementation of urban consolidation. The MPR includes a Model of defining weights (MDW) and an MGHS, the last level of which is represented by the criteria for comparing cadastral parcels. For their definition, cadastral parcels attribute value assessment models were used to optimize the planning process of the Campus project implementation, which refers to the Model of intended utility assessment (MIU) and Model of index fragmentation assessment (MIF). Both assessments were based on determining the ideal spatial “status” of the cadastral parcels to achieve the final solution as efficiently as possible. The MIF was developed for three levels of planning the implementation of a large public project and was proposed as one of the essential spatial criteria from the selection of the construction location to the priority ranking of cadastral parcels in the planning of project implementation. In the process of realizing the MPR model, all relevant stakeholders organized into four groups were involved: representatives from the City of Split administration, representatives of private owners, representatives of the University of Split, and experts from the research field who expressed their preferences through weight values defined by the AHP method.

Given that the research is based on planning the construction of a large public project, which is realized over a long period, future research will go in the direction of defining a model for determining the phases of its realization, which will be based on the definition of the investor’s limitations. As already stated, the basic limitations during the implementation of the project are not only technical but also conditioned by the private ownership of cadastral parcels in the construction area. The combination of the mentioned limitations conditions the definition of project implementation phases through defined sets of cadastral parcels that enter into the processes of implementing urban consolidation. As stated in the introductory part of the second chapter, this research precedes the last, rounded unit in planning the implementation of urban consolidation for the realization of a large public project supported by a Spatial Decision Support System. The last phase of the research will cover the negotiation procedures and planning of land reallocation implementation. The research questions arising from this study are related to finding ways to combine the assessed cadastral parcels that enter the processes of urban consolidation, the preferences of private owners of cadastral parcels, and finally, the possibilities of investors of a large public project.