1887
PDF

Abstract

Summary

Landslides are one of the most common forms of geodynamic hazards, causing significant damage to infrastructure and ecosystems, especially in mountainous regions. This study investigates the influence of geostructural, geomorphological, climatic and anthropogenic factors on the activation of landslide processes in the Ukrainian Carpathians, particularly in the Flysch Carpathians and the Transcarpathian Internal Depression. Using GIS and multiple linear regression, data on 2,325 landslides were analysed and classified according to slope morphotype, geological structure, absolute heights, proximity to watercourses, faults, roads and buildings, as well as microseismicity parameters. The model for the Flysch Carpathians revealed the decisive influence of slope morphology (especially complex and straight forms), high absolute elevations, seismic activity, and anthropogenic factors. Within the Transcarpathian depression, geolithological features and the influence of technogenic disturbances of slope equilibrium are dominant. The results confirm the spatial differentiation of the influence of factors within different tectonic units, which allows the creation of accurate landslide susceptibility maps for regional planning and risk management. The obtained regression models have high coefficients of determination (R2 > 0.79) and can be used for further forecasting of landslide intensification in the context of climate change, increasing urbanisation and seismic activity.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.2025520006
2025-09-15
2026-01-15
Loading full text...

Full text loading...

/deliver/fulltext/2214-4609/2025/landslide-2025/Landslide25_06.html?itemId=/content/papers/10.3997/2214-4609.2025520006&mimeType=html&fmt=ahah

References

  1. Informatsiinyi shchorichnyk shchodo aktyvizatsii nebezpechnykh ekzohennykh heolohichnykh protsesiv za danymy monitorynhu EHP (2021). Derzhavne naukovo-vyrobnyche pidpryiemstvo «Derzhavnyi informatsiinyi heolohichnyi fond Ukrainy». 104. https://geoinf.kiev.ua/wp/wp-content/uploads/2021/06/2021_sajt.pdf
    [Google Scholar]
  2. Derzhavna heolohichna karta Ukrainy masshtabu 1:200000, arkushi M-34-XXIX (Snina), M-34-XXXV(Uzhhorod), L-34-V (Satu-Mare). (2003). K.: Ministerstvo ekolohii ta pryrodnykh resursiv Ukrainy, derzhavne heolohichne pidpryiemstvo «Zakhidukrheolohiia», 96.
    [Google Scholar]
  3. 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. 16th International Conference “Monitoring 2022”, Kyiv, Ukraine, DOI: https://doi.org/10.3997/2214-4609.2022580129
    [Google Scholar]
  4. HostiukZ., PohribnyiO., BurianykO., KarabiniukM., MarkanychYa. (2021). Influence of geological structure and geomorphological features on landslides in the Pokut Carpathians. 15th International Conference Monitoring of Geological Processes and Ecological Condition of the Environment, P. 1–5. DOI: https://doi.org/10.3997/2214-4609.20215K2072
    [Google Scholar]
  5. Mandal, K. (2018). Modeling and mapping landslide susceptibility zones using GIS based multivariate binary logistic regression (LR) model in the Rorachu river basin of eastern Sikkim Himalaya, India. Modeling Earth Systems and Environment. https://doi.org/10.1007/S40808-018-0426-0
    [Google Scholar]
  6. Segoni, S., PappaficoG. F., Luti, T., & CataniF. (2020). Landslide susceptibility assessment in complex geological settings: sensitivity to geological information and insights on its parameterization. Landslides. 17. DOI: 10.1007/s10346‑019‑01340‑2
    https://doi.org/10.1007/s10346-019-01340-2 [Google Scholar]
  7. ShtohrynL. V., & KasiynchukD. V. (2024). Analysis of natural and man-made factors of landslide development in the Carpathian region using GIS. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, 5, pp. 093–098. https://doi.org/10.33271/nvngu/2024-5/093
    [Google Scholar]
  8. Sun, X., Chen, J., Bao, Y., Han, X., Zhan, J., & Peng, W. (2018). Landslide Susceptibility Mapping Using Logistic Regression Analysis along the Jinsha River and Its Tributaries Close to Derong and Deqin County, Southwestern China. ISPRS International Journal of Geo-Information, 7(11), 438. https://doi.org/10.3390/ijgi7110438
    [Google Scholar]
  9. Tektonichna karta Ukrainy. Masshtab 1:1 000 000. Poiasniuvalna zapyska. (2007). Ministerstvo okhorony navkolyshnoho pryrodnoho seredovyshcha Ukrainy, Derzhavna heolohichna sluzhba. Ukrainskyi derzhavnyi heolohorozviduvalnyi instytut. K.: UkrDHRI,: 132.
    [Google Scholar]
  10. Wasowski, J., Gaudio, V.Del. (2000). Evaluating seismically induced mass movement hazard in Caramanico Terme (Italy), Engineering Geology, Volume 58, Issues 3–4, Pages 291–311. https://doi.org/10.1016/S0013-7952(00)00040-5
    [Google Scholar]
/content/papers/10.3997/2214-4609.2025520006
Loading
/content/papers/10.3997/2214-4609.2025520006
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error