Decisions around distributing available funds among potential land consolidation projects require a thorough analysis in order to maximize the effects of land consolidation. In order to avoid choosing the wrong land consolidation projects, different methods can be used. Generally, there are two possible groups of methods: one based on a qualitative approach (DELPHI; SWOT) and one based on a quantitative approach (AHP, VIKOR, SAW, TOPSIS, etc.). In this research, the focus was on the sensitivity of the resulting rankings affected by varying the input data in multi-criteria analysis methods, with an emphasis on the variation in the weight and the choice of criteria. This research was motivated by the subjective character of the choice of criteria and their weighting before applying the multi-criteria analysis methods. Four methods were included (AHP, TOPSIS, VIKOR, and SAW) for the multi-criteria analysis, with three ways of defining weights (consistent, modified, or quasi-consistent and freely determined without taking consistency into account), in order to determine the influence of the different methods on the final ranking. The weights were defined only by an acceptable interval of values. The sensitivity of the methods was investigated using the differences in the obtained rankings between each method. A case study is provided on real data, and the results are discussed. The results showed a relatively small variance and possible equal rankings of projects by means of statistical analyses. This finding opens up the possibility of the valuation of projects instead of simple rankings.

Land consolidation (LC) is an activity that brings numerous benefits to rural areas. However, being resource demanding, the LC requires a decision on where it should be provided or where the limited resources should be distributed in order to maximize its effects. In order to avoid the subjective decision maker’s preferences, optimization methods for identifying the priorities are recommended. Bearing in mind that every optimization method could give different results, we proposed the utilization of multiple optimization methods for ranking the cadastral municipalities which are candidates for providing LC. In this research, the main aim was to find if it is possible to avoid the subjective decision making in cadastral municipalities (CM) as a candidate for LC ranking by utilizing the statistical approach. Additionally, in this research, the analysis was provided, varying the number of optimization criteria. In this research, two assumptions were adopted: (1) every single optimization method has the same weight, and (2) the differences between different ranks are results of random errors. After determining the average ranking of a certain cadastral municipality, its interval of ranking is calculated by using the Student’s distribution. Cadastral municipalities that belong within the interval of available resources are candidates for providing LC. In the case study, fifteen cadastral municipalities were researched, including eight and ten criteria for optimization, and results showed that there are significant differences between ranks of cadastral municipalities varying depending on the method utilized.

Multi-criteria decision-making models are very useful tools for use in the process of land consolidation project choice. However, they can lead to wrong or suboptimal choices. Under limited budgetary conditions (where the available budget does not cover all project candidates’ requirements for their realization), it is necessary to make a proper choice regarding financial asset distribution. This process should lead to the best possible budget distribution, i.e., to the choice of land consolidation projects that promises the maximal return on the assets invested. In this research, the authors have conducted theoretical research based on real data to determine the sensitivity of the choice of land consolidation projects with regard to the influence of the chosen criteria for decision-making. The utilized data were obtained via four multi-criteria decision-making (MCDM) methods (AHP, VIKOR, SAW and TOPSIS). The method used for investigating the influence of certain criteria on decision-making was based on a multidimensional linear regression method where the rank of a land consolidation project is a dependent variable, while the values of criteria are independent variables.

In this paper, a model has been created for the automated generation of DTM (Digital Terrain Models) using a hybrid data structure based on LiDAR (Light Detection and Ranging) data. The automated process facilitates the creation and implementation of...