THE COMPLEX PROBLEM OF EXPANDING THE CAPABILITIES OF CADASTRAL SYSTEMS AND WAYS TO SOLVE IT

Authors

  • K. Meteshkin O.M. Beketov National University of Urban Economy in Kharkiv
  • M. Pilicheva O.M. Beketov National University of Urban Economy in Kharkiv
  • L. Maslii O.M. Beketov National University of Urban Economy in Kharkiv

DOI:

https://doi.org/10.33042/2522-1809-2023-6-180-110-117

Keywords:

cadastral system, geoinformation system, decision support system, thematic layer manipulation system, formalisation

Abstract

The development of cadastral systems in various countries, including Ukraine, has gone through creating information systems that serve users (stakeholders) in one of the subject areas, such as land administration, real estate construction, water resources, and others. Modern cadastral systems have no capacity to solve complex problems, and, at the same time, their structure does not contain specialised mathematical support in the form of models capable of simulating complex processes. Intelligent cadastres will be able to solve complex problems. Along with the existing types of cadastre support, intelligent cadastres should have well-structured mathematical and heuristic support. It should allow for solving private computing and service tasks, as well as loosely structured ones with a high degree of uncertainty, and provide good visualisation and detailing of objects, processes, and phenomena based on cloud and other modern information technologies. We propose introducing an intelligent cadastral system, presented as a geoinformation system with components of both a decision support system and a system for manipulating thematic layers. The decision support system should contain typical models used during the formalisation of one or another subject area or as a variant of the formal model of the subject areas’ description. The thematic layers manipulation system should allow the integration of attributive data belonging to different subject areas. In this case, ensuring prompt and fruitful work of cognitologists with experts is essential. The shortage of time and the variety of problems to be solved require the development of technology for formalising the knowledge of experts or specific subject areas. Implementing this technology and ensuring its implementation will require the creation of banks of typical knowledge models, which should store standardised procedures for formal representations. The bank of formal representations of heuristic knowledge includes procedures for forming production rules, building semantic and other networks, building frame representations and genetic algorithms, and so on. The bank of formal logical procedures contains procedures for creating logical rules based on the logic of statements, rules of logical inference based on the predicate logic, procedures of other modal logics, in particular, the presence logic, and procedures for building logical constructions based on the theory of categories and functors.

Author Biographies

K. Meteshkin, O.M. Beketov National University of Urban Economy in Kharkiv

Doctor of Technical Sciences, Full Professor, Professor at the Department of Land Administration and Geographic Information Systems

M. Pilicheva, O.M. Beketov National University of Urban Economy in Kharkiv

Candidate of Technical Sciences, Associate Professor, Department of Land Administration and Geographic Information Systems

L. Maslii, O.M. Beketov National University of Urban Economy in Kharkiv

Senior Lecturer at the Department of Land Administration and Geographic Information Systems

References

Meteshkin, K., Pilicheva, M., & Masliy, L. (2023). Comparative analysis of characteristics of cadastral systems of European Union countries. Municipal Economy of Cities. Series: Engineering science and architecture, 3(177), 85–91. DOI: 10.33042/2522-1809-2023-3-177-85-91 [in Ukrainian]

Cabinet of Ministers of Ukraine. (2022, October 4). On approval of the Procedure for information interaction between the State Land Cadastre, other cadastres and information systems: Resolution of June 3, 2013, No. 483. Verkhovna Rada of Ukraine. Retrieved from https://zakon.rada.gov.ua/laws/show/483-2013-%D0%BF#Text [in Ukrainian]

Cabinet of Ministers of Ukraine. (2023, January 20). Some aspects of electronic interaction of electronic information resources: Resolution of September 8, 2016, No. 606. Verkhovna Rada of Ukraine. Retrieved from https://zakon.rada.gov.ua/laws/show/606-2016-п#Text [in Ukrainian]

Hubar, Yu., Khavar, Yu., & Vash, Ya. (2021). Ways of development of national cadastral systems. Modern achievements of geodesic science and industry, І(41), 151–163. Retrieved from http://zgt.com.ua/wp-content/uploads/2021/05/20.pdf [in Ukrainian]

Anopriienko, T. V., Pilicheva, M. O., Masliy, L. O., & Kulish, Yu. R. (2020). Current trends of the information supply of the land cadastre in Ukraine and the world. Scientific notes of TNU named after V. I. Vernadskyi. Series: Technical sciences, 31(70)(1), 146–152 [in Ukrainian]

Lisova, T. V., & Leiba, L. V. (2023). Certain issues of maintaining the state land cadastre. Analytical and Comparative Jurisprudence, (3), 224–228. DOI: 10.24144/2788-6018.2023.03.40 [in Ukrainian]

Cemellini, В., Thompson, R., De Vries, M., & Van Oosterom, P. (2018). Visualization/dissemination of 3D Cadastral Information. Proceedings of the FIG Congress 2018: Embracing our smart world where the continents connect: enhancing the geospatial maturity of societies (article 9591). International Federation of Surveyors (FIG). Retrieved from http://www.gdmc.nl/3dcadastre/literature/3Dcad_2018_51.pdf

Аien, A., Rajabifard, A., Kalantari, M., & Wiliamson, I. (2011). Aspects of 3D Cadastre – A Case Study in Victoria. Proceedings of the FIG Working Week 2011: Bridging the Gap between Cultures (pp. 1–15). International Federation of Surveyors (FIG). Retrieved from http://www.gdmc.nl/3dcadastre/literature/3Dcad_2011_01.pdf

Bydłosz, J., & Bieda, A. (2020). Developing a UML Model for the 3D Cadastre in Poland. Land, 9(11), 466. DOI: 10.3390/land9110466

Khalfa, A. Z., Alwan, I. A. K., & Hamed, N. H. (2014). Updating Urban Cadastral Map and Database Designing by GIS Using Aerial Photos. Engineering and Technology Journal, 32(8), 2020–2029. DOI: 10.30684/etj.32.8A.11

Kohli, D., Unger, E.-M., Lemmen, C., Bennett, R., Koeva, M., Friis, J., & Bhandari, B. (2018). Validation of a cadastral map created using satellite imagery and automated feature extraction techniques: A case of Nepal. Proceedings of the FIG Congress 2018: Embracing our smart world where the continents connect: enhancing the geospatial maturity of societies (article 9566). International Federation of Surveyors (FIG). Retrieved from https://www.fig.net/resources/proceedings/fig_proceedings/fig2018/papers/ts08c/TS08C_kohli_unger_et_al_9566.pdf

Boosarapu, A., Kakunuri, S., & Chitta, H. N. (2020). Progress In Artificial Intelligence: Technological Singularity The Future. International Journal of Grid and Distributed Computing, 13(2), 2571–2580. Retrieved from https://www.researchgate.net/publication/352211159

Meteshkin, K., Pilicheva, M., & Masliy, L. (2022). The state land cadastre in the V.I. Vernadsky noospheric concept. Municipal Economy of Cities. Series: Engineering science and architecture, 6(173), 86–90. DOI: 10.33042/2522-1809-2022-6-173-86-90 [in Ukrainian]

Meteshkin, K., & Levchenko, A. (2019). Parallels and meridians of geodesy and informatics or the basics of noo-geomatics: study guide. O. M. Beketov NUUE. Retrieved from https://eprints.kname.edu.ua/55317/1/2019%20ПЕЧ.%2052Н_26.09.pdf

García-Díaz, V. (Ed.). (2021). Algorithms in Decision Support Systems. MDPI. DOI: 10.3390/books978-3-0365-0589-3

Meteshkin, K., Kondrashchenko, O., & Pilicheva, M. (2021). Method and experience of implementation of quantitative assessment of dissertations quality of doctors of philosophy on the example of the specialty Geodesy and Land Management. Municipal Economy of Cities. Series: Engineering science and architecture, 3(163), 39–46. DOI: 10.33042/2522-1809-2021-3-163-39-46 [in Ukrainian]

Hull, S., & Whittal, J. (2013). Good e-Governance and Cadastral Innovation: In Pursuit of a Definition of e-Cadastral Systems. South African Journal of Geomatics, 2(4), 342–357. Retrieved from https://www.ajol.info/index.php/sajg/article/view/106975

Gold, R. (2004). Petri Nets in Software Engineering. Arbeitsberichte – Working Papers, (5), 1–24. Retrieved from https://www.thi.de/fileadmin/daten/Working_Papers/thi_workingpaper_05_gold.pdf

Chathuranga, K. M., Adikari, A. M. J. P., & Dammalage, T. L. (2017). Artificial neural networks based automatic linear and area feature extraction from Worldview-02 satellite images for cadastral data collection; a case study in Belihuloya, Sri Lanka. Proceedings of the 37th Asian Conference on Remote Sensing (ACRS 2016) (pp. 732–740). Curran Associates, Inc. Retrieved from https://www.researchgate.net/profile/Manjula-Chathuranga/publication/358570030

Shnaidman, A., Shoshani, U., & Doytsher, Y. (2012). Genetic Algorithms: a stochastic approach for improving the current cadastre accuracies. Survey Review, 44(325), 102–110. DOI: 10.1179/1752270611Y.0000000012

Kohli, A., & Jenni, L. (2008). Transformation of Cadastral Data between Geodetic Reference Frames using Finite Element Method. Proceedings of the FIG Working Week 2008: Integrating the Generations (pp. 1–15). International Federation of Surveyors (FIG). Retrieved from https://www.fig.net/resources/proceedings/fig_proceedings/fig2008/papers/ts02a/ts02a_05_kohli_jenni_2623.pdf

Published

2023-12-04

How to Cite

Meteshkin, K., Pilicheva, M., & Maslii, L. (2023). THE COMPLEX PROBLEM OF EXPANDING THE CAPABILITIES OF CADASTRAL SYSTEMS AND WAYS TO SOLVE IT. Municipal Economy of Cities, 6(180), 110–117. https://doi.org/10.33042/2522-1809-2023-6-180-110-117

Most read articles by the same author(s)