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Due to stalling land consolidation process and limited resources, Slovak administration needs to prioritize new projects. 120 cadastral areas are currently selected annually based on weights and different point-scales for the criteria. It can be argued that the evaluation of the official governmental special non-departmental criteria (6) for 2023, targeted to social, environmental, landscape, and development issues, is flawed and should be modified. Normalized relative magnitudes (particularly where the areal extent of the phenomenon represented by a given criterion is measurable and data is available) are suggested. Only 4 areas from the 2023 official selection would place in the first 120 (13 in the first 500) by the simple average ranking with modified criteria values. The criteria (M1, least developed districts; M2, transport infrastructure; M3, protected natural areas; M4, protected water management areas; M5, natural disasters; M6, risk of erosion) could be complemented by 4 new ones, namely: M7, critical profiles and integrated area protection; M8, marginalized population groups; M9, strategic projects and industrial parks; M10, agro-forestry systems. Using severity of risk for a cadastral area (i.e. percentages of appropriately measured and subsequently normalized criteria) could contribute to improved selection by removing unnecessary distortion by a point scheme.
Czasopismo
Rocznik
Tom
Strony
15--23
Opis fizyczny
Bibliogr. 23 poz., rys., tab.
Twórcy
autor
- Institute of Landscape Engineering, Faculty of Horticulture and Landscape Engineering, Slovak University of Agriculture in Nitra, Nitra, Slovakia
autor
- Institute of Landscape Engineering, Faculty of Horticulture and Landscape Engineering, Slovak University of Agriculture in Nitra, Nitra, Slovakia
autor
- Institute of Landscape Engineering, Faculty of Horticulture and Landscape Engineering, Slovak University of Agriculture in Nitra, Nitra, Slovakia
autor
- Institute of Landscape Engineering, Faculty of Horticulture and Landscape Engineering, Slovak University of Agriculture in Nitra, Nitra, Slovakia
Bibliografia
- 1. de Vries, W.T. (2022). Social aspects in land consolidation processes. Land, 11(3), 452. https://doi.org/10.3390/land11030452
- 2. Demetriou, D. (2014). The development of an integrated planning and decision support system (IPDSS) for land consolidation. Springer Theses Recognizing Outstanding PhD Research.
- 3. Dudzinska, M., Kocur-Bera, K. (2014). Land consolidation as the driving force behind ecological and economic development of rural areas. 12th International Conference “Environmental Engineering”, http://dx.doi.org/10.3846/enviro.2014.204
- 4. Ertunç, E., Janus, J., Uyan, M. (2023). Prioritization of land consolidation projects using the multi-criteria Best-Worst Method: A case study from Poland. Environ. Monit. Assess., 195(9), 1045. https://doi.org/10.1007/s10661-023-11712-w
- 5. Harasimowicz, S., Bacior, S., Gniadek, J., Ertunç, E., Janus, J. (2021). The impact of the variability of parameters related to transport costs and parcel shape on land reallocation results. Comput. Electron. Agric. 185, 106137. https://doi.org/10.1016/j.compag.2021.106137
- 6. Hartvigsen, M. B. (2005). Land reform and land consolidation in central and Eastern Europe after 1989: Experiences and Perspectives. Aalborg Universitetsforlag. https://doi.org/10.5278/vbn.phd.engsci.00019
- 7. Choubin, B., Moradi, E., Golshan, M., Adamowski, J. (2019). An ensemble prediction of flood susceptibility using multivariate discriminant analysis, classification and regression trees, and support vector machines. An ensemble prediction of flood susceptibility using multivariate discriminant analysis, classification and regression trees, and support vector machines. Sci. Total Environ. 658, 61–77. https://doi.org/10.1016/j.scitotenv.2018.10.064
- 8. Janus, J., Taszakowski, J. 2018. Spatial differentiation of indicators presenting selected barriers in the productivity of agricultural areas: A regional approach to setting land consolidation priorities. Ecological Indicators, 93, 718–729. https://doi.org/10.1016/j.ecolind.2018.05.050
- 9. Jiang, Y., Tang, Y. T., Long, H., Deng, W. (2022). Land consolidation: A comparative research between Europe and China. Land Use Policy, 112. https://doi.org/10.1016/j.landusepol.2021.105790
- 10. Karásek, P., Konečná, J., Pochop, M., Kučera, J., Podhrázská, J. (2018). Priority areas for initiating land consolidations related to erosion and water retention in the landscape, Czech Republic. J. Ecol. Eng., 19(4), 16–28. https://doi.org/10.12911/22998993/89655
- 11. Kupidura, P. (2019). The comparison of different methods of texture analysis for their efficacy for land use classification in satellite imagery. Remote Sens., 11, 1233. https://doi.org/10.3390/rs11101233
- 12. Leń, P. (2018). An algorithm for selecting groups of factors for prioritization of land consolidation in rural areas. Computers and Electronics in Agriculture, 144, 216–221. https://doi.org/10.1016/j.compag.2017.12.014
- 13. Leń, P., Król, Ż. (2018). Analysis of economic and environmental effects of land consolidation on the example of Hucisko village. Journal of Ecological Engineering, 17(5), 232–239. https://doi.org/10.12911/22998993/65090.
- 14. Lisec, A.; Cerjak, M.; Pintar, M. (2005). The influence of the land consolidation on the ecological elements in the rural landscape. In: Cygas, D., Froehner, K.D. (Eds.), The 6th International Conference “Environmental Engineering.”. Vilnius Gediminas Technical University Press, “Technika,” Vilnius, 164–170.
- 15. Marinković, G.; Ilić, Z.; Trifković, M.; Tatalović, J.; Božić, M. (2022). Optimization methods as a base for decision making in land consolidation projects ranking. Land, 11(9), 1466. https://doi.org/10.3390/land11091466
- 16. Muchová, Z. (2019). Assessment of land ownership fragmentation by multiple criteria. Survey Review, 51, 366. https://doi.org/10.1080/00396265.2017.1415663
- 17. Muchová, Z.; Petrovič, F. (2019). Prioritization and Evaluation of Land Consolidation Projects—Žitava River Basin in a Slovakian Case. Sustanability, 11, 2041. https://doi.org/10.3390/su11072041
- 18. Pašakarnisa, G., Malienea, V., Dixon-Goughc, R., Malysd, N. (2021). Decision support framework to rank and prioritise the potential land areas for comprehensive land consolidation. Land Use Policy, 100, 104908. https://doi.org/10.1016/j.landusepol.2020.104908
- 19. Peng, J., Yan, S., Strijker, D., Wu, Q., Chen, W., Ma, Z. (2020). The influence of place identity on perceptions of landscape change: Exploring evidence from rural land consolidation projects in Eastern China. Land Use Policy, 99, 104891. https://doi.org/10.1016/j.landusepol.2020.104891
- 20. Pitel, J. (1990). Multicriterion optimization and its utilization in agriculture. Elsevier: Amsterdam, Netherlands, 1–250.
- 21. Sklenička, P. (2006). Applying evaluation criteria for the land consolidation effect to three contrasting study areas in the Czech Republic. Land Use Policy, 23(4), 502–510. https://doi.org/10.1016/j.landusepol.2005.03.001
- 22. Strek, Z., Len, P., Wojcik-Len, J. (2019). Hierarchization of Land Consolidation Works in the Rural Areas of Central Poland. IOP Conf. Ser.: Earth Environ. Sci. 221, 012066. https://doi.org/10.1088/1755-1315/221/1/012066
- 23. Vinge, H. (2018). Farmland conversion to fight climate change? Resource hierarchies, discursive power and ulterior motives in land use politics. J. Rural. Stud. 64, 20–27. https://doi.org/10.1016/j.jrurstud.2018.10.002
Typ dokumentu
Bibliografia
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