The combination of geographic information systems (GIS) and remote sensing data analysis tools will make it possible to assess in a short time and with high accuracy the suitability of an area for the construction of land or linear structures in the areas where dangerous geological processes are developed. In this article we use the example of karst area in Kisherstky district of Perm region as an example to carry out the karts hazard zoning of the territory according to geomorphological indicators by analyzing ALOS-DEM digital elevation model (DEM). Patterns in the distribution of karst forms in the study area were evaluated depending on the dissection of the relief, its slope and distance from the watercourses. Based on the patterns, an integral map was constructed. The approach allows to do zoning the territory with respect to the studied danger geological process in a short time and with high accuracy, which is due to the use of patterns of forms distribution in the analysis.

Marina A. Kitaeva
Student
Perm State National Research University
15, Bukireva Str., Perm, 614068, Russia
Geological Engineer
LLC «Karst-Control and Bank Protection» (Perm’ Branch)
4, Sergey Danschin Str., Perm, 614068, Russia
e-mail: kitaeva0822@yandex.ru
ORCID 0009-0001-5405-0578

Elena V. Drobinina
Candidate of Geological and Mineralogical Sciences
Researcher, Associate Professor
Perm State National Research University
15, Bukireva Str., Perm, 614068, Russia
e-mail: alenadrobinina@yandex.ru
ORCID 0000-0002-6756-7947
Web of Science ResearcherID GQY-6222-2022
SPIN-код: 4500-3517
Scopus AuthorID 56416422000
AuthorID 879933

1. Butyrina K.G. Gipsovyi karst tsentral’noi chasti Permskoi oblasti [Gypsum karst in the central part of Perm region]: dissertation for the degree of candidate of geographical sciences. Perm: PGU; 1968. 380 p.
2. Osipov V.I. (ed.) Geologicheskii risk urbanizirovannykh territorii [Geological risk of urbanized territories]. Moscow: RUDN; 2020. 316 p.
3. Drobinina E.V. Ispol’zovanie instrumentov gidrologicheskogo analiza v karstologicheskom prognoze [Using tools of hydrological analysis in karst hazard assessment]. In: Materialy 20 Mezhdunarodnoi konferentsii «Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa» (Moscow, 14–18 November 2022). Moscow: IKI RAN, 2022. p. 267. DOI: 10.21046/20DZZconf-2022a.
4. Drobinina E.V. Optimization of office studies of the engineering surveys results using GIS. In: Prospects for development of engineering survey in Russian Federation: materials of the XVI All-Russian conference of prospecting organizations (Moscow, 1‒3 December 2021). Moscow: Geomarketing; 2021. pp.93–99.
5. Erofeev E.A., Kataev V.N. Identification of the surface karst forms on materials of satellite images. Geologiya i poleznye iskopaemye Zapadnogo Urala. 2017;(17):193–197.
6. Erofeev E.A., Kataev V.N. Results of analysis of the surface of the basin r. Iren’ by remote methods. In: Hydrogeology and Karstology: Proceeding Interuniversity Collection. Vol. 20. Perm’: PGNIU; 2020. pp. 166–176.
7. Erofeev E.A., Kataev V.N. Geological regulations of karst development on the example of the Nizhniirensky-Ordinsky support area (Perm territory). Scientific Notes of V.I. Vernadsky Crimean Federal University. Geography. Geology. 2020;6(3):301–320.
8. Kataev V.N., Ermolovich I.G. Cracks in the side rebound and karst formation within the Kamsko-Chusovsky interfluve. Geologiya i poleznye iskopaemye Zapadnogo Urala. 2021;41:223–232.
9. Kovaleva T.G. Karst hazards assessment based on the general geological approach at the territory of city of Kungur. Bulletin of Perm University. Geology. 2016;33:26–35. DOI: 10.17072/psu.geol.33.26.
10. Kurlovich D.M. Ispol’zovanie Model Builder pri razrabotke nabora instrumentov «Strukturno-geomorfologicheskii GIS-analiz» dlya ArcToolbox GIS ArcGIS 9.3 [Using Model Builder to develop a set of tools “Structural-geomorphological GIS analysis” for ArcToolbox GIS ArcGIS 9.3]. In: International congress on computer science: information systems and technologies: proceedings of International Scientific Congress (Minsk, 31 October – 3 November 2011). Pt. 2. Minsk: BGU; 2011. P. 193–198.
11. Nazarov N.N. Karst of Prikamye. Physical-geographical (geomorphological) aspects. Perm’: PGNIU; 1996. 93 p.
12. Polyakova E.V., Kutinov Yu.G., Mineev A.L., Chistova Z.B. Geoehkologicheskaya otsenka veroyatnosti aktivizatsii karstovykh protsessov na osnove tsifrovogo modelirovaniya rel’efa [Geoecological assessment of the probability of activation of karst processes based on digital relief modeling]. In: Analiz, prognoz i upravlenie prirodnymi riskami s uchetom global’nogo izmeneniya klimata «Georisk – 2018»: materialy X Mezhdunarodnoi nauchno-prakticheskoi konferentsii (Moscow, 23–24 October 2018). Mavlyanova N.G. (ed.). Vol. 2. Moscow: RUDN; 2018. pp. 221–225.
13. Polyakova E.V., Kutinov Y.G., Mineev A.L., Chistova Z.B., Belenovich T.Ya. Using the ASTER GDEM v.2 global digital elevation model to identify areas of possible activation of karst processes in the Arkhangelsk region (Russia). Uchenye zapiski Kazanskogo universiteta. Seriya Estestvennye nauki. 2021;163(2): 302–319. DOI: 10.26907/2542-064X.2021.2.302-319.
14. Alexander S.C., Rahimi M., Larson E., Bomberger, C., Greenwaldt B., Alexander E.C. Combining LiDAR, aerial photography and pictometric tools for karst features database management. In: NCKRI Symposium 2. Proceedings of the 13th Multidisciplinary Conference on Sinkholes and the Engineering and Environmental Impacts of Karst (KIP Talks and Conferences, 36). 2013. pp. 441–448. Available at: https://digitalcommons.usf.edu/kip_talks/36 (accessed 20.11.2023).
15. Burrough P.A., McDonell R.A. Principles of geographical information system. Oxford – New York: Oxford University Press; 1998. 333 p.
16. Carvalho Júnior O.A de., Guimarães R.F., Montgomery D.R., Gillespie A.R., Gomes R.A.T., Martins É.d.S., Silva N.C. Karst depression detection using ASTER, ALOS/PRISM and SRTM-derived digital elevation models in the Bambuí Group, Brazil. Remote Sensing. 2014;6(1):330–351. DOI: 10.3390/rs6010330.
17. Garas K.L., Madrigal M.F.B., Agot R.D.D., Canlas M.C.M., Manzano L.S.J. Karst depression detection using IFSAR-DEM: A tool for subsidence hazard assessment in Panglao, Bohol. Carsologica Sinica. 2020;39(6):928–936. DOI: 10.11932/karst20200612.
18. Hofierka J., Gallay M., Bandura P., Šašak J. Identification of karst sinkholes in a forested karst landscape using airborne laser scanning data and water flow analysis. Geomorphology. 2018;308:265–277. DOI: 10.1016/j.geomorph.2018.02.004.
19. Kobrick M., Crippen R. SRTMGL1 v003. NASA Shuttle Radar Topography Mission Global 1 arc second. 2000. Available at: https://lpdaac.usgs.gov/products/srtmgl1v003/ (accessed 08.04.2022).
20. Panno S.V., Luman D.E. Mapping palimpsest karst features on the Illinois sinkhole plain using historical aerial photography. Carbonates and Evaporites. 2013;28:201–214. DOI: 10.1007/s13146-012-0107-4.
21. Panno S.V., Weibel C.P., Li W. Karst regions of Illinois (Open File Series 1997-2). Champaign: Illinois State Geological Survey; 1997. 90 p.
22. Preety K., Prasad A.K., Varma A.K., El-Askary H. Accuracy assessment, comparative performance, and enhancement of public domain digital elevation models (ASTER 30 m, SRTM 30 m, CARTOSAT 30 m, SRTM 90 m, MERIT 90 m, and TanDEM-X 90 m) using DGPS. Remote Sensing. 2022;14(6):1334. DOI: 10.3390/rs14061334.
23. Siart C., Bubenzer O., Eitel B. Combining digital elevation data (SRTM/ASTER), high resolution satellite imagery (Quickbird) and GIS for geomorphological mapping: A multi-component case study on Mediterranean karst in Central Crete. Geomorphology. 2009;112(1-2):106–121. DOI: 10.1016/j.geomorph.2009.05.010.