Науковий вісник НГУ

Analysis of natural and man-made factors of landslide development in the Carpathian region using GIS

• 
• 

User Rating:  / 0

PoorBest 

Details

Category: Content №5 2024

Last Updated on 29 October 2024

Published on 30 November -0001

Hits: 761

Authors:

L.V.Shtohryn*, orcid.org/0000-0001-8381-1236, Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

D.V.Kasiynchuk, orcid.org/0000-0003-4761-5320, Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2024, (5): 093 - 098

https://doi.org/10.33271/nvngu/2024-5/093

Abstract:

Purpose. Determination of the dependencies of spatial relationships between landslides in the Carpathian region of Ukraine and the factors causing them, taking into account the differences in geomorphological, geological, climatic conditions and natural and geographical zoning according to the landscape principle.

Methodology. The morphometric analysis of the territory was carried out using QGIS tools to determine the slope angles and exposure; linear characteristics were calculated: distances to the river, road, and houses. Based on the image interpretation data, we calculated the total annual rainfall and average annual air temperature. The impact of the factors considered on landslide formation was assessed using multivariate statistical analysis: factor analysis and linear multiple regression.

Findings. Studies on the impact of natural and topographical conditions and anthropogenic activity on the development of landslide processes have been conducted. Orographic and climatic factors play the most important role. Construction of business facilities results in a decrease in the slope stability in 14–19 % of cases. The analysed independed factors showed good consistency between the distribution of existing landslides and the parameters under consideration: the share of the total variance of the factors under consideration is 71–76 %, the coefficient of determination of the regression model is 0.7. Based on the results of geoinformation and statistical analyses, it is proved that differences in geomorphological conditions and human activity (construction of roads, economic facilities) are dominant in the formation of landslides in different landscape zones.

Originality. It is established that there is a dynamic coherence between the spatial change in natural conditions and human settlement and activity, which interact with each other to create prerequisites for the development of landslides.

Practical value. This study is important from the point of view of understanding and mitigating the cause-and-effect relationship of landslide development for certain territories, and the results obtained can be useful in developing land use planning strategies, infrastructure development, and planning new construction works.

Keywords: landslides, GIS, natural and anthropogenic factors, geoinformation analysis, factor and regression analyses

References.

1. State Service of Geology and Mineral Resources of Ukraine. (2020). Information yearbook on the activation of hazardous exogenous geological processes according to EGP monitoring data. SRPE “State Information Geological Fund of Ukraine”. Retrieved from https://geoinf.kiev.ua/wp/wp-content/uploads/2021/06/2021_sajt.pdf.

2. Press service of the Chernivtsi Regional State Administration. (2024, April 08). Landslide damages road in Chernivtsi region. By UNIAN. Retrieved from https://www.unian.ua/pogoda/news/pogoda-v-ukrajini-u-cherniveckiy-oblasti-zsuv-gruntu-poshkodiv-dorogu-sinoptik-11022302.html.

3. LB (2024, April 08). Heavy rains in Zakarpattia caused dangerous landslidesу. Retrieved from https://lb.ua/society/2020/07/28/462816_potuzhni_zlivi_zakarpatti.html.

4. Kuzmenko, E. D. (ed.) (2016). Predicting landslides: monography. IFNTUOG. Retrieved from http://www.irbis-nbuv.gov.ua/publ/REF-0000621211.

5. Kuzmenko, E. D., Zhuravel, O. M., Chepurna, T. B., & Chepur­nyi, I. V. (2011). Forecasting of exogenous geological processes Part 1: Theoretical prerequisites for forecasting exogenous geological processes. Patterns of landslide activation. Geoinformatica, (3), 61-74.

6. Ivanik, O., Shevchuk, V., Kravchenko, D., & Hadiatska, K. (2023). Landslide hazard prediction and impact on comminity: main approaches, principles and methods. Visnyk Kyivskoho natsionalnoho universytetu imeni Tarasa Shevchenka, 1(100), 5-14.

7. Kasiianchuk, D. V., Kuzmenko, E. D., Chepurna, T. B., & Chepurnyi, I. V. (2016). Calculation of that environmental and geological landslide risk estimate. Eastern-European Journal of Enterprise Technologies, 1(10(79), 18-25. https://doi.org/10.15587/1729-4061.2016.59687.

8. Kasiyanchuk, D., Shtohryn, L., Yazlovetska, N., & Levitska, M. (2018). Methodology of time forecast of exogenous geological processes. 17 ^th International Conference on Geoinformatics – Theoretical and Applied Aspects, (pp.1-5). Taras Shevchenko National University of Kyiv. https://doi.org/10.3997/2214-4609.201801837.

9. Hablovskyi, B., Hablovska, N., Shtohryn, L., Kasiyanchuk, D., & Ko­nonenko, M. (2023). The Long-Term Prediction of Landslide Processes within the Precarpathian Depression of the Cernivtsi Region of Ukraine. Journal of Ecological Engineering, 24(7), 254-262. https://doi.org/10.12911/22998993/164753.

10. Hablovska, N. Y., Hablovskyi, B. B., Shtohryn, L. V., & Kasiyanchuk, D. V. (2022). Analysis of Natural Factors and Predictionof Landslide Activation Processes in the Folded Carpathians. 16 ^th International Conference Monitoring of Geological Processes and Ecological Condition of the Environment, (pp.1-5). Taras Shevchenko National University of Kyiv. https://doi.org/10.3997/2214-4609.2022580129.

11. Hoa, P. V., Tuan, N. Q., Hong, P. V., Thao, G. T. P., & Binh, N. A. (2023). GIS-based modeling of landslide susceptibility zonation by integrating the frequency ratio and objective–subjective weighting approach: a case study in a tropical monsoon climate region. Frontiers in Environmental Science, (11). https://doi.org/ 10.3389/fenvs.2023.1175567.

12. Chen, L., Guo, Z., Yin, K., Shrestha, D. P., & Jin, S. (2019). The influence of land use and land cover change on landslide susceptibility: a case study in Zhushan Town, Xuan’en County (Hubei, China). Natural Hazards and Earth System Science, 19(203), 2207-2228. https://doi.org/10.5194/nhess-19-2207-2019.

13. Reichenbach, P., Rossi, M., Malamud, B. D., Mihir, M., & Guzzetti, F. A. (2018). A review of statistically-based landslide susceptibility models. Earth-Science Reviews, (180), 60-91. https://doi.org/10.1016/j.earscirev.2018.03.001.

14. Arabameri, A., Chandra, Pal S., Rezaie, F., Chakrabortty, R., Saha, A., Blaschke, T., Di Napoli, M., …, & Ngo, T. (2021). Decision tree based ensemble machine learning approaches for landslide susceptibility mapping. Geocarto International, (37), 1-28. https://doi.org/10.1080/10106049.2021.1892210.

15. Nazarevich, A. V., & Nazarevich, L. E. (2013). Geodynamics, tectonics and seismicity of the Carpathian region of Ukraine. Geodynamica, (2), 247-249.

16. Kravchuk, Y. S., Adamenko, O. M., & Adamenko, Y. O. (2019). Geomorphological analysis of the relief of promising areas of the Ukrainian Carpathians for recreational needs (on the example of the Black Tisza basin). Problems of geomorphology and paleogeography of the Ukrainian Carpathians and adjacent territories: a collection of scientific papers. Ivan Franko National University of Lviv, 2(10), 18-41.  

17. Giletskyi, Y. R., & Tymofiychuk, N. M. (2019). Physical and geographical zoning of the Ukrainian Carpathians for the purposes of educational tourism. Geography and tourism, (53), 103-109. https://doi.org/10.17721/2308-135X.2019.53.104-110.

18. Kravtsiv, V. S. (Ed.) (2013). Carpathian region: actual problems and prospects of development: (Vol. 1). National Academy of Sciences of Ukraine. Institute of Regional Studies. Retrieved from http://ird.gov.ua/irdp/p20130001.pdf.

19. Guzzetti, F., Gariano, S. L., Peruccacci, S., Brunetti, M. T., Marchesini, I., Rossi, M., & Melillo, M. (2019) Geographical landslide early warning systems. Earth-Science Reviews, 200(12). https://doi.org/10.1016/j.earscirev.2019.102973.

20.  Pona, O., Shtogryn, L., & Kasianchuk, D. (2016). The analysis of the relationship between the phases of the Moon and the occurrence of landslides. Geoinformatics – 15 ^th EAGE International Conference on Geoinformatics – Theoretical and Applied Aspects, 1-5.  https://doi.org/10.3997/2214-4609.201600486.

21. Mattas, C., Dimitraki, L., Georgiou, P., & Venetsanou, P. (2021). Use of Factor Analysis (FA), Artificial Neural Networks (ANNs), and Multiple Linear Regression (MLR) for Electrical Conductivity Prediction in Aquifers in the Gallikos River Basin, Northern Greece. Hydrology, 8(3), 127. https://doi.org/10.3390/hydrology8030127.

22. Bo, Y., Chen, Y., Che, Q., Shi, Y., & Zhang, Y. (2022). Multivariate Statistical Analysis of the Spatial Variability of Hydrochemical Evolution during Riverbank Infiltration. Water, 14(23), 3800. https://doi.org/10.3390/w14233800.

• < Prev
• Next >