Marko Sinčić, mag. ing. geol.
Landslide susceptibility is defined as the spatial, time independent probability of landslide occurring in an area depending on the local terrain conditions (Guzzeti et al., 1999). A landslide susceptibility map is a map showing the sub-division of the terrain into zones (classes) that have a different likelihood of a landslide occurring (Corominas et al, 2013).
Landslide susceptibility maps are based on the assumption that landslides are likely to occur under the same conditions as those under which they occurred in the recent past. Due to that reason, the preparation of landslide susceptibility maps requires a landslide inventory map indicating where landslide already occurred used in combination with a series of conditioning factors answering what terrain conditions caused for landslide occurrence. According to Soeters & van Westen, 1996, and Corominas et al., 2013 some of the commonly used conditioning factors are elevation, slope gradient, slope orientation, relief dissection, lithological map, faults, geological contact, drainage network, flow accumulation, topographic wetness, land use, roads, and buildings, some of which are shown in Figure 1.
Figure 1 An overview of landslide conditioning factors used in landslide susceptibility modelling, an example from the modelling of the City of Karlovac (Sinčić et al., 2022)
Landslide susceptibility maps are a result of landslide susceptibility assessments defined as quantitative or qualitative assessments of the classifications and spatial distribution of landslides which exist of potentially may occur in an area. There are several methods of landslide susceptibility assessments, as shown in Figure 2.
Figure 2 Methods for landslide susceptibility assessment (Corominas et al., 2013)
Moreover, for commonly used data-driven statistical methods, according to Reichenbach et al., 2018, nine steps for preparing a landslide susceptibility assessment and for proper use of associated terrain classifications are: (i) obtain relevant landslide information, (ii) obtain relevant conditioning factor information, (iii) select appropriate mapping unit, (iv) select appropriate statistical model, (v) evaluate the model fitting performance, (vi) evaluate the model predictive performance, (vii) estimate the model uncertainty, (viii) rank the model quality, and (ix) design a landslide protocol. An example of a complex landslide susceptibility modelling testing different combinations of statistical methods, mapping units and types of landslide inventory maps is shown in Figure 3.
Figure 3 An example of complex landslide susceptibility modelling, including testing types of landslide inventory maps, statistical methods and mapping units (Bernat Gazibara et al., 2022)
Landslide susceptibility maps can be created in several scales, depending on the available data and the purpose of the landslide susceptibility assessment. Namely, the scales are site-specific (>1:5 000), local (1:25 000 – 1:5 000), regional (1:250 000 – 1:25 000), and national (<1:250 000) (Corominas et al., 2013). An example of a City District, City, County and national landslide susceptibility map are shown in Figure 4-A, 4-D, 4-C, and 4-B, respectively.
Figure 4 Landslide susceptibility maps: A part of the Podsljeme Zone (City District), B Croatia (national), C Primorsko-Goranska County (County), D the City of Karlovac (City)
Answering “where?” landslides are likely to occur, landslide susceptibility maps make up the input data for landslide hazard maps answering “where and when?”, followed by a landslide risk map answering “where, when, and what?”. In combination, landslide inventory, susceptibility, hazard and risk maps make key tools in landslide management, necessary for landslide mitigation. Identification and map portrayal of areas highly susceptible to landslide occurrence are the first and necessary steps towards loss reduction (Mihalić Arbanas & Arbanas, 2015). Concretely, portraying highly susceptible areas, i.e. classification is defined as the act of dividing land into homogenous areas or domains and ranking them according to degrees of actual or potential landslide susceptibility (Corominas et al., 2013). Landslide susceptibility maps are mostly used by relevant stakeholders in the domain of construction, spatial planning, civil protection and environment protection.
Reference:
Bernat Gazibara, S.; Mihalić Arbanas, S; Sinčić, M.; Krkač, M.; Lukačić, H.; Jagodnik, P.; Arbanas, Ž. (2022): LandSlidePlan - Scientific research project on landslide susceptibility assessment in large scale. In: Peranić, J., Vivoda Prodan, M., Bernat Gazibara, S., Krkač, M., Mihalić Arbanas, S., Arbanas, Ž. Rijeka (eds.): Proceedings of the 5th ReSyLAB 'Landslide Modelling & Applications': Faculty of Civil Engineering, University of Rijeka and Faculty of Mining, Geology and Petroleum Engineering, University of Zagreb, 99-106, 257 p.
Corominas, J., van Westen, C., Frattini, P., Cascini, L., Malet, J.P., Fotopolou, S., Catani, F., Van Den Eeckhaut, M., Mavrouli, O., Agliardi, F., Pitilakis, K., Winger, M.G., Pastor, M., Ferlisi, S., Tofani, V., Hervas, J., Smith, J.T. (2013): Recommendations for the quantitative analysis of landslide risk. Bulletin of Engineering Geology and the Environment, 73, 209–263.
Guzzeti, F., Galli, M., Reichenbach P., Ardizzone, F., Cardinali, M. (1999): Landslide Hazard assessment in the Collazzone area, Umbria, Central Italy. Natural hazards and earth system sciences, 6, 1, 115-131.
Mihalić Arbanas, S., Arbanas, Ž. (2015): Landslides: A Guide to Researching Landslide Phenomena and Processes. In: Gaurina Međimurec, N. (eds.): Handbook of Research on Advancements in Environmental Engineering. IGI Global, 474-510, 660 p.
Reichenbach, P., Rossi, M., Malamud, B.D., Mihir, M., Guzzetti, F. (2018): A review of statistically-based landslide susceptibility models, Earth-Science Reviews, 180, 60-91.
Sinčić, M.; Bernat Gazibara, S.; Krkač, M.; Mihalić Arbanas, S. (2022): Landslide susceptibility assessment of the City of Karlovac using the bivariate statistical analysis. Rudarsko-geološko-naftni Zbornik, 37(2), 149-170.
Soeters. R., van Westen. C.J. (1996): Slope instability recognition, analysis and zonation. In: Turner, A.K., Schuster, R.L. (eds.): Landslides investigation and mitigation. TRB Special Report 247. National Academy Press, Washington, DC, 129–177, 685 p.
Marko Sinčić, mag. ing. geol. is a Junior Researcher – Assistant at the Faculty of Mining, Geology and Petroleum Engineering, University of Zagreb. He finished Graduate studies in Geological Engineering in 2020 and in 2021 he enrolled in Doctoral studies of Applied Geosciences, Mining and Petroleum Engineering while working on the Croatian Science Foundation LandSlidePlan project.
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