Design of an Automated Algorithm for Delimiting Land Use/Soil Valuation Classes as a Tool Supporting Data Processing in the Land Consolidation Procedure

Abstract

The consolidation of land to improve the agrarian structure and provide for sustainable rural development is a complex and multi-faceted process, and its efficiency depends on a considerable number of factors associated with its respective stages of desk studies and fieldwork. In order to ensure the highest-quality concepts and their efficient implementation, various measures are undertaken to improve, among other things, the methods for acquiring, collecting, and processing spatial data representing elements of reality saved in cadastral databases. There are a wide variety of available solutions oriented towards land consolidation improvement, but most of them refer to modifications that are difficult to implement due to, for instance, high costs, high technical requirements, and the absence of relevant legal regulations. Our study aimed to find a practical and applicable solution to a material problem in terms of land consolidation projects in Poland, a task associated with the necessity of converting cadastral database objects so that they were suitable for appraising the value of land, and designing new farmsteads based on the value of land held by particular participants of the land consolidation project. It involved the development and implementation of a self-designed algorithm for automated processing of auxiliary land-use/soil-valuation class objects into separate classes representing soil class contours and land use contours, in compliance with the current regulations governing the structure of the cadastre in Poland. The work resulted in the development of an innovative tool, making it possible, among other functions, to align object-generating methods as preferred by the administrator of the cadastral database. The designed algorithm model reduces data processing time to several seconds, while simultaneously eliminating the risk of error. The tool was thoroughly evaluated and then implemented at the Subcarpathian Office of Land Surveying and Agricultural Areas in Rzeszów, which is in charge of land consolidation projects in south-eastern Poland.

1. Introduction

A characteristic feature of the technical aspect of works related to land consolidation is their complexity, with multiple stages, even irrespective of specific local laws. The activities include several land-surveying and design tasks. A significant issue tackled in the worldwide literature is the efficiency of land consolidation works, as described by working time and the quality of outcomes. Janus and Ertunç specified the main scopes of ongoing and potential studies regarding the optimisation of the rate of land consolidation work where the main research directions included: land consolidation work planning, valuation of land in the consolidated area, methods of designing new plot arrangements (in particular, using process automation algorithms), and land-consolidation evaluation tools [1].

Yan et al. presented the concept of SWOT as applied to strategic planning of land consolidation works and examined the criteria, which were constituted by the strengths, weaknesses, chances, and risks due to the implementation of the land consolidation programme, including various economic, environmental, and social factors [2].

Using the example of the historical and present consolidation of land in Poland, Janus and Markuszewska identified the low efficiency of consolidation works compared with the time and financial resources involved. They designed a tool for verifying the efficiency of land consolidation that determined the directions for desired changes and worked out suggested solutions for the revealed inconsistencies [3].

Solutions have been proposed by Xia and Yang, focusing on the comprehensive consolidation concept, in order to boost land consolidation efficiency and maximise potential benefits. The outcomes of their study on selected land consolidation projects in China, in which they used a self-designed multivariate tool for evaluation, showed significant variations in the levels of satisfaction among farmers and investors. The authors highlighted the necessity for modifying the previous classical approach for the benefit of comprehensive consolidation, taking equal note of the interests of all participants, and following the assumptions of sustainable development [4]. The outcomes of land consolidation in China were also investigated by Zou and Li. The use of evolving GIS technology empowered the parametrisation of geospatial data and constructive conclusions regarding the priorities of potential optimisation [5]. Additionally, Lisec et al. tackled the assessment of satisfaction among land consolidation participants. Drawing on their experience acquired in Slovenia, the authors enunciated and substantiated the need for optimising the land consolidation process by increasing the perceivable advantages of land consolidation procedures, as manifested in the general increase in the support for such projects [6].

Munnangi et al. discussed land consolidation issues in India. They criticised the insufficient land consolidation measures undertaken by public administration that were limited to only the state of Uttar Pradesh, despite a clear need for land consolidation in various regions of India. Simultaneously, they presented concepts for increasing the efficiency of land consolidation projects at the technological and administrative, as well as political, levels [7].

Hakli et al. described the specificity of land consolidation in Central and Eastern Europe, emphasising problems related to plot design. Since manual processing is time-consuming, attempts are made to develop algorithms for the automated processing of tasks. However, the authors found most of the solutions described in the reference literature insufficient in terms of work efficiency. In response to the problem, they introduced their own algorithm for designing plots, with a set of values based on the Delaunay triangulation and binary search [8]. Harasimowicz et al. also presented the concept of a tool supporting land reallocation projects. The proposed heuristic algorithms based on an indicator describing the relation between plot shape and the calculated cost of transport stemming from the configuration of the land are an alternative to conventional methods that are considered time-consuming and insufficient [9]. Additionally, Grudzień and Kurpiel displayed technical solutions for the automated delimitation of areas of land using values estimated based on selected criteria [10].

An extensive monograph by Demetriou tackles the issue of land reallocation as a stage of land consolidation projects in Cyprus. As a result of detailed surveys, the author, among other things, identified recommended indicators describing the geometry of plots that would be necessary for setting a correct direction for the land consolidation procedure. The use of objectively justified tools improves work efficiency and ensures the correctness of assumptions adopted at the initial planning stage, hence contributing to maximising the benefits derived from land consolidation [11]. Cay and Uyan also suggested a solution to boost the efficiency of the land reallocation process. Their proposed analytic hierarchy process (AHP) model, developed for the needs of land consolidation projects in Turkey, effectively optimises the geometry and location of land, while simultaneously taking into account the declared hierarchy of the needs of landholdings. The evaluation of the tool demonstrated a significant advantage of the algorithm over conventional land reallocation methods based on the standard wish lists of the participants in a consolidation project [12]. Uyan et al. verified this thesis in their surveys comparing the satisfaction-level of the owners of conventionally consolidated land (ca. 66% satisfied respondents) and the participants of land consolidation projects using automated reallocation algorithms (ca. 90% satisfied respondents). The outcome of the surveys corroborated a considerably higher quality of the results of the proposed tools compared with the previously practiced techniques [13].

Branković et al. tackled land value estimation in the land consolidation process, seen as a ’sensitive and demanding’ stage of the work. To ensure efficient and fair valuation, the authors offer a self-designed tool for extending the scope of data previously covered by GIS tools. In addition, they point to the significant necessity of aligning the regulatory solutions currently in force to enable the modernisation of land consolidation methods [14]. Another author investigating automated valuation of land for consolidation works is Demetriou. The proposed algorithm model tested in Cyprus showed material advantages over standard methods, including accuracy, reliability, and consistency of the calculation procedure and the time required for land valuation [15]. Tezcan et al. presented an analogous tool adapted for implementation in the land consolidation process in Turkey. Based on fourteen different factors determining land value, and aggregated into a unified ratio, it provided objective results and improved the efficiency of analyses [16]. By contrast, Ertunç and Uyan proposed a new BWM (best worst method), considering the weights of respective factors, for the valuation of land [17]. Muchová et al. highlighted the urgency of changes to land valuation methods used in Slovakia, claiming that the previous approach based on soil-quality ecological units was ineffective and did not reflect the actual value of the land. They saw their self-designed multivariate method, integrating the existing criteria with additional indicators depending on, for instance, the location and level of economic development of the study area, as a solution to the problem [18]. In addition, they discussed the substantive selection of potential objects for consolidation.

Janus and Taszakowski, using the example of Poland, noted that the requirement for land consolidation works is considerably higher than the technical and financial possibilities of conducting such works. To mitigate the adverse phenomenon of insufficient funds, the authors suggested a hierarchy of needs using a multivariate ratio describing the specific features of the land in the study sites. They recommended the tool as potentially supporting the qualification process of villages on the waiting list for land consolidation and as a method for creating rankings useful for long-term work scheduling [19]. Wójcik-Leń et al. wrote on a similar topic. Their proposed tool was an algorithm supporting priority object identification for land consolidation. The main selection criterion was based on data describing the agricultural suitability of soils, translating into material benefits derived from the potential consolidation project [20]. Janus and Taszakowski also suggested a hierarchy of land for consolidation based on the possible benefits. The proposed tool relied on characteristics calculated based on a cadastral data set, including, but not limited to, the number and size of agricultural plots, fragmentation (partitioning) of land, and soil quality [21]. Bożek is another author exploring the fragmentation of arable land in detail and has presented a tool for calculating the land fragmentation index based on geometric cadastral data [22]. Leń described a more in-depth method for sorting objects in terms of the requirement for land consolidation. His self-designed concept of systematic grouping and hierarchisation of factors for ordering and selecting data sets used in the analysis of specific features of respective areas of land offered a significant extension of the commonly used multivariate methods. The solution proposed can be used for efficient delimitation of potential consolidation objects with flexible terms and conditions for their assessment [23]. Wójcik-Leń used the criterion of agricultural suitability of land, extended by additional factors such as geomorphological and hydrological characteristics, for delimiting areas of low value for agriculture. Her self-designed tool identified the problem areas’ locations, providing useful information at the stage of selecting potential objects for consolidation and within a process of allocating non-agricultural land [24].

Stręk and Noga, aiming to improve the efficiency of land consolidation in Poland, suggested practical uses for the concept of clustering adjacent objects for consolidation. The proposed algorithm, relying on a set of geometric and tabular cadastral data, aggregated objects with similar parameters for consolidation by clustering. This method can significantly extend the options for designing an optimised spatial structure for farmsteads [25].

The specificity of a system of legal regulations is a material factor determining the efficiency of land consolidation processes and the possibility of taking various measures to enhance them. On the example of historical and present-day legal regulations in Estonia, Jürgenson raised the subject of the relationship between the efficiency of land consolidation works and the standards regulating the operation of the cadastral system and the ownership of land holdings. She mentioned a clear need for modifying previous regulations that prevent land consolidations involving the use of present-day technology. The adverse regulatory framework stemming from, among other things, the limitations of ownership of land holdings in the Socialist regime and the interim solutions applied in the course of the political transformation can pose a real problem in Central and Eastern Europe, including the post-Soviet states [26]. By contrast, Ertunç et al. conducted a multi-faceted comparative analysis of the regulatory framework of land value estimation methods in Turkey, Poland, Croatia, and Slovakia. Despite material differences in the applicable regulations and practices, they observed various similarities regarding difficulties due to the specificity of the land valuation procedures. The main conclusion of their study was that taking measures to parametrise the factors considered and to design efficient computing algorithms is reasonable [27].

The quoted areas of study and suggested lines of development are only a part of the vast scope of researchers’ interests in the context of land consolidation. Numerous concepts for optimising respective measures are associated with the use of various solutions, such as research methods and technical tools for data processing. The tools used include mathematical and statistical analysis [28,29], GIS techniques [30], photogrammetric methods and remote sensing, and calculations involving neural networks [31,32,33]. Despite there being a range of various concepts with specific applications, the common factor is still the broadly-interpreted improvement of respective stages of the land consolidation process, which contributes to increasing the efficiency of performance and maximising the benefits for sustainable rural development [34].

Changes in rural areas’ spatial and ownership structure are reflected in extensive sets of generated spatial data that constitute elements of necessary records forming part of cadastral databases. The methods employed in creating and modifying them have a significant impact on the time and quality of land consolidation. However, it should be highlighted that a considerable number of the presented concepts incorporate innovative solutions that necessitate an advanced modification of the land consolidation methodology. Implementing such tools requires that the existing legal and technical solutions be aligned with complex procedures, as suggested by the authors. Since the comprehensive restructuring of the complex land consolidation process is an extremely cost- and time-consuming procedure, and since the continuity of long-term tasks should be maintained, a systematically recurring modernisation of the methodological assumptions of the procedure, one considering the latest proposals for technical improvements, can be deemed unprofitable and potentially undesirable. This phenomenon might be one of the reasons for the outdated, low-efficiency procedures observed by researchers. To solve this problem, we recommend expanding the range of designed tools to support land consolidation works with technical solutions optimising individual tasks, while simultaneously satisfying applicable legal standards and generally applicable methodological assumptions. An example of such a proposal is the concept that is the object of this study.

Our research intends to provide a solution to the problem of a deficiency of practical tools for optimising land consolidation work, to the extent of aligning the generated studies with Polish standards regarding the cadastral database. We believe that a smooth and correct alignment is possible using dedicated algorithms implemented in a GIS environment. The research work described in this paper aims to design a new algorithm for the automated creation of soil class contours and land use designation, factors constituting obligatory elements of the cadastral database in Poland and significantly relevant to land consolidation [35,36]. The target objects are generated based on a technical layer of land-use classes and applied soil-valuation classes, for instance, at the stage of making comparative land estimates, designing the spatial arrangement of plots and describing the types and uses of respective areas. The resulting tool, designed and built based on present-day GIS techniques, eliminates the need for manual processing of a considerable number of sets of spatial data, thereby optimising task performance time and minimising the risk of errors.

The proposed solutions were evaluated using cadastral data for 11 villages of the Subcarpathian Voivodeship (Figure 1), extending over a total area of ca. 17,845 km², where actual objects covered by the land consolidation procedure are located [37]. This region is characterised by a particularly high percentage of land consolidation projects, due to the unfavourable geospatial parameters of the agrarian structure and intensive efforts to improve such parameters. Following necessary tests for substantive correctness, functionality, and operating efficiency, the algorithm was put into common use at the Subcarpathian Office of Land Surveying and Agricultural Areas in Rzeszów, as an entity holding an exclusive authorisation to conduct land consolidation works within the Subcarpathian Voivodeship.

2. Materials and Methods

For the needs of the conducted research, including the design, development, and evaluation of the tool for converting technical land use/soil valuation classes into correct cadastral database objects, first, the research material was obtained in the form of complete data consisting of the vector layers of land-use/soil-valuation classes and cadastral databases for 11 villages covered by the land consolidation procedure. All layers were verified for the presence of the necessary attribute defining land-use/soil-valuation class type based on designations of land use type and soil classification contour, including soil class. The detailed characteristics of the input data used are presented in

Table 1. Description of data in use. Source: authors’ elaboration.

Type of Data	Source	Use
Vector layer of land-use/soil-valuation classes with an attribute describing land use type	Subcarpathian Office of Land Surveying and Agricultural Areas in Rzeszów	− Processing of the existing geometry into separate geometries of soil class contours. − Values of standard attributes such as OFU (land use type), OZU (soil class contour type) and OZK (soil class).

.

In line with the objective of this paper, we mainly aimed at creating an intuitive tool for efficient and substantively correct conversion of the technical vector layer of land-use/soil-valuation classes into separate layers of soil class contours and land use contours. Figure 2 is a simplified flow chart of the procedure.

Due to the practical nature of this project, we aligned the workflow chart with specific available input data and the precisely specified form of the desired output data. Cadastral database management software determined the target structure of the soil class contours and land use contours database, but correct objects were created by correctly imported elements saved in a format compatible with the computer programme supporting land consolidation works.

The designed tool was based on solutions used in popular programmes such as EWMAPA 14.08 (supporting the graphics in land surveying databases) and SCALENIA 2.34 (providing tools for improving the implementation of land consolidation processes), developed by Geobid Sp. z o.o. The spatial data processing platform was the free-to-use common access version of QGIS 3.28.0 (with an option of aligning the designed solutions with subsequent programme versions). For smooth data exchange between applications, we used the interoperable SHP format to store the graphic data file together with the attribute data file.

While working to accomplish the adopted objective using the available geoprocessing tools of QGIS 3.28.0 and dedicated SQL-based instructions, we developed a universal model of algorithms supported by the QGIS 3.28.0 interface. Embedded in the common-access technical framework of QGIS 3.28.0, the tool became intuitive, and results could be verified effectively, simultaneously reducing the time required for designing and optimising the solutions in use. The designed model, after the inclusion of necessary input data in the form of vector layers consisting of polygons and vertices of land-use/soil-valuation classes and the specification of attribute fields representing unique numbers and designations of land use/soil valuation classes, is a multistage, conditional instruction schematically represented in Figure 3 and described below.

The tool’s workflow is determined by correct data input. Apart from identifying the right vector layers and attributes, the operator selects a contour aggregation method relevant to the form of the output data. Having filled in the input data and launched data processing, the algorithm first classifies the designations of the inserted polygon layer of land-use/soil-valuation classes based on the set attribute-identifying information on the types of soil class contours, including soil valuation classes, and information on land use classes (1). Clear information is obtained by queries searching for the values of attributes such as OFU, OZU, and OZK in respective parts of the text attribute of land-use/soil-valuation class designations [36].

Afterwards, relying on the classification of values of relevant attributes, two parallel, initially geometrically-uniform layers are created that represent soil-class contours and land-use contours (2). In order to ensure substantive correctness, objects making up the layer of soil class contours are filtered according to applicable legal regulations assuming that soil-class contours cover only arable land, orchards, permanent meadows, permanent pastures, built-up agricultural land, pond bottoms, ditch bottoms, tree stands and shrubs within the utilised agricultural areas, forests, and tree stands and shrubs. Objects for further processing are assigned unique numbers of polygons compatible with the cadastral database management software. Thanks to information on the numbering of the input layer of land-use/soil-valuation classes, sections of unique numbers referring to the numbers of precincts in the national land register can be identified correctly [36]. In addition to unique numbers, the layers are also assigned adequate designations representing the OFU (designation of land use class) attribute for land use and a combination of OZU (designation of soil class contour) and OZK (specification of soil valuation class) for soil class contours. The designations are verified for compliance with the range of possible values defined by the application schema of the land- and building-register database.

At the next stage, the algorithm optionally aggregates adjacent objects displaying identical OFU attributes (for land use) and OZU + OZK attributes (for soil class contours) (3). A necessity for aggregation does not stem directly from the legislation but is a requirement that the local land-surveying and cartography centre has imposed on the land-surveying and the cartographic works contractor. When adjacent polygons with identical designations are consolidated, the density of object segments is reduced to the minimum, which improves the legibility of the graphic content of the database as well as maps and extracts generated based on such content. Concurrently, the presence of extensive, fragmented polygons created by consolidating a considerable number of component objects can obstruct the administration of graphic data. In addition, using a single label for a contour with a considerable surface area and a complex shape can lead to a visual misinterpretation of cartographic data. One consequence of the lack of a clear optimal solution is the variety of preferences among database managers. In the guidelines noted, three commonly practised approaches can be identified:

(a)

Full aggregation—complete aggregation of land use classes with identical OFU attributes and soil valuation classes with an identical combination of OZU and OZK attributes.

(b)

Partial aggregation—aggregation of adjacent land use classes having identical OFU attributes and soil valuation classes with an identical combination of OZU and OZK attributes, except for land forming extensive and complex networks such as ditches and roads.

(c)

No aggregation—leaving adjacent land use classes with identical OFU attributes and soil valuation classes with an identical combination of OZU and OZK unchanged.

The concepts specified above and illustrated by examples in Figure 4 are reflected in the structure of the selective object aggregation module providing three optional pathways. Global consolidation of polygons in layers is based on the designation attribute, simultaneously excluding the possibility of generating ‘multi-polygons’ by aggregating objects with distinctive topological features. The polygon layers of soil class contours and land use contours, optionally subjected to aggregation of elements, are a part of the set of the model’s output data. The labels displayed on the contours indicate the value of the designation attribute: “dr” for roads, “B” for built-up areas, “Ps” for pastures and “R” for arable lands.

At the final stage, the algorithm delimits the set of input vertices of land-use/soil-valuation classes into separate vertices of land use classes (4a) and separate vertices of soil class contours (4b). The generated point-layers of the vertices, containing elements delimited based on topological conditions relating to adequate polygon layers, are assigned secondary numbers to ensure that the identifiers are unique. The breakpoints of soil-class contours and land-use contours are not objects defined by the laws in force but are necessary for correctly importing geometric data into EWMAPA 14.08, a computer programme for managing the graphic contents of the cadastral database. Certain alternative software systems, including the popular TurboMAP developed by Geomatyka Kraków s.c., are based exclusively on layers representing the range of respective contours.

A correct procedure for delimiting land-use classes from soil-valuation classes using the presented tool results in two separate sets of output data, consisting of polygon and point vector layers for soil-classification contours and land-use contours. The objects formed can be saved in a desired format using the QGIS 3.28.0 interface and then imported into the target software, supporting the management of land surveying and cartographic databases.

The proposed solution can be used in land-consolidation projects in any location. The methods used are based on applicable legal standards and are compatible with the current application scheme of the cadastral database. This testifies to the fact that our tool is competitive with most of the available solutions described in the worldwide literature that, in order to be implemented, need a general modification of the land consolidation methodology, which is a highly complicated undertaking.

3. Results

Our work resulted in the development of a complete model of algorithms, supported by QGIS 3.28.0, for smooth conversion of the geometric sets of land-use/soil-valuation classes into separate layers of soil-class contours and land-use contours satisfying standards displayed by the laws in force and adapted to implementation in software supporting land-surveying database management. The tool–user interface of the model is presented in Figure 5.

The computing module has an intuitive and simple graphical user interface invoked from the algorithm panel of QGIS 3.28.0. The dialogue-box style is identical to that of other geoprocessing algorithms available in the default programme package. To activate the tool, vector layers of polygon geometry representing land-use/soil-valuation classes and points’ vertices should be identified. Attribute fields storing information such as land-use number and type should also be defined. In addition, the user chooses one of the available methods for aggregating adjacent soil class contours or identical types of land use.

The tool was tested using vector layers of land-use/soil-valuation classes derived from cadastral databases maintained for the districts of the Subcarpathian Voivodeship. For full verification of how efficiently the algorithms work, we ran tests on objects from databases maintained by entities with different preferences of aggregation methods used in the case of soil class contours and land use contours. The results corroborated that the assumptions had been fulfilled.

The results of the test procedure conducted in the village of Zagórze (Przeworsk dis-trict) are presented on the map in Figure 6. The meanings of the designation labels’ values are: “dr”—roads, “Lzr-R”—wooded and bushy lands on arable lands, “Ls”—forests, “R”—arable lands, and “Lzr”—wooded and bushy lands. The Roman numerals determine the soil classes.

The initiated object conversion procedure produced separate layers of soil-class contours and land-use classes. Object labels in Figs. 6b and 6c above correspond to the values of attributes such as OZU (soil-class contour type) and OZK (soil class) for the layer of soil class contours (Figure 6b), and OFU (land-use type; Figure 6c). The previously-split land use designated as “dr” (road), shown in Figure 6c, was aggregated based on the request for full aggregation of adjacent contours of identical type. An analogous representation refers to the soil class contour “RIVa” denoting class IVa arable land. In order to fully verify whether the tool operated correctly, we launched the procedure again using other possible assumptions regarding the adjacent contours’ aggregation method. Figure 7 and Figure 8 present the results for alternative assumptions, together with necessary comments.

The outcomes of the procedure provided for a partial aggregation of adjacent contours of identical types (Figure 7) imply that the applied solutions are substantively and technically correct. Similar observations were made when converting objects without the contour-aggregation mechanism (Figure 8).

An additional analysis compared the range of the created layers of land use classes with the actual orthophotomap (current in 2019), provided by the Head Office of Geodesy and Cartography in the national geoportal free of charge [38]. Figure 9 illustrates the result of this comparison.

A comparison of the range of generated land-use contours and land-use forms visible in aerial images demonstrated the relative compatibility of the output algorithm data with the real status. The borderline between land with trees or shrubs (designated as Lzr) and arable land (R) is particularly well-marked. However, we should note that the distribution of soil-class contours and land-use contours is the result of land surveying presentation and can differ from the real status, among other reasons, due to the dynamics of land-use structure.

4. Discussion

An advantage of the presented solution is the high intuitiveness of the tool and a relatively short data processing time (several seconds). Fully-automated processes effectively replace labour-consuming manual operations (taking even a few days) and prevent potential errors. The possibility of choosing the method for aggregation of adjacent polygons with identical attribute-values together with the attribute-correctness-checking module determines the technological advantage of the tool over a considerable part of the available alternative solutions, including the methods for delimiting land-use/soil-valuation classes available in software supporting the graphic content of cadastral databases.

Correct results rely on proper selection and the substantive and topological correctness of the input data. The tool is equipped with a mechanism for the checking compliance of the attributes with dictionaries saved in the application schema of the land- and building-register database and eliminating the overlapping polygons. However, a considerable number of errors in the geometry and attributes of the input data, including undesirable gaps between objects and unspecified values of OFU, OZU, and OZK attributes, are copied into output files and can be saved in the cadastral database. Solutions for automated correction of topological errors would ensure technically correct results irrespective of input data quality but could lead to the making of unauthorised changes remaining the responsibility of the database manager. For a superior quality of results, it is suggested that the data be checked, as necessary, first, and the procedure for handling inconsistencies, if any, then be agreed upon.

After successful testing, the designed solution was implemented at the Subcarpathian Office of Land Surveying and Agricultural Areas in Rzeszów, which is in charge of land consolidation processes in the Subcarpathian Voivodeship. The main practical use of the tool is the mass conversion of land-use/soil-valuation classes generated in the course of land-consolidation works into soil-class contours and land-use contours to update the district land surveying and cartographic database. The practical application of the proposed solutions significantly reduced land surveying and cartographic data processing time, improving the efficiency of land consolidation procedures.

The undertaken measures are a response to the necessity of optimising the performance of land consolidation projects that are documented in the worldwide literature. This solution corresponds to the progress, observed by Janus and Ertunç, in using GIS elements for solving problems related to respective stages of the land consolidation process [27]. Additionally, Tezcan et al. formulated theoretical grounds for the concept of developing methods to support, for instance, land valuation during land consolidation projects. In their opinion, it is necessary to use innovative methods based on high-technology [17]. However, in this context, the innovativeness of proposed solutions should coincide with the technical possibility of implementing them, depending on, among other factors, the regulations in force, the availability of necessary means, and the approach of entities in charge of land consolidation. The algorithm presented in this paper was designed in consideration of the current land consolidation methodology and is oriented toward the real and immediate optimisation of work using recognised and commonly practised methods.

5. Conclusions

A specific feature of the land consolidation procedure is that it is multi-faceted, which affects the complexity of operations. Access to adequate tools supporting the respective stage of the work determines their efficient performance and the quality of the end result. Therefore, when time-consuming operations become automated, it has a real impact on the whole procedure and, as a consequence, is associated with an increase in the potential number of objects that can be possibly consolidated in a given period. This advantage is of particular importance to south-eastern Poland, where the need for land consolidation is relatively high and where the number of land consolidation procedures is the highest in Poland.

The tool presented in this paper is an essential element in modernising the mass data-processing techniques used in land consolidation procedures. The solutions used considerably reduce the data processing time, while simultaneously ensuring correct results. The output data are compatible with available software supporting cadastral databases and consistent with the applicable laws governing the structure of spatial data to the extent of the cadastre. Satisfactory evaluation results allowed us to implement the tool at the Subcarpathian Office of Land Surveying and Agricultural Areas in Rzeszów and use the proposed solutions for optimising the performance of current and potential land consolidation projects. The universal algorithm makes it possible to use the model in any land consolidation project in Poland. Some modifications in the algorithm structure, for instance, declaring possible dictionary values of object attributes, would also make this solution suitable for use in selected countries of Europe and the world. Our research plans assume the continuing development of this concept and working out solutions to improve other land consolidation operations and ensure the smooth alignment of the tool with the legal standards of other countries.

Despite the high efficiency of the algorithm, as documented in the course of our evaluation, for the presented tool to be used correctly, it is necessary to consider its technical constraints associated with, among other things, the specificity of processed data and possible modifications of applicable laws regarding the cadastral database application scheme. Correct results can be obtained after entering substantively correct input data with correct geometries and attributes compliant with applicable standards. If a layer containing errors such as gaps or overlapping contours is entered, the inconsistencies will become permanent in the output geometry. In addition, incorrect values of the attribute defining the land-use/soil-valuation class type prevent generating the correct output objects and entering them into the district cadastral database. Prior verification of the substantive and technical correctness of processed data makes it possible to avoid inconsistencies in object conversion and generating incorrect output files.

As an element of the continually evolving GIS technology, the geoprocessing tools have real applications in land-surveying and cartographic practice and support operations in the course of works related to land consolidation for sustainable rural development. It would also be reasonable to implement, in subsequent works, automation stages for optimised use of available resources, which is equivalent to maximising the quantity and quality of the results. Thus, the use of present-day developments in information technology, commonly occurring in many areas of the global economy, should also be deemed a key element of progress in land surveying and cartography.