Introducing a geospatial database and GIS techniques as a decision-making tool for multicriteria decision analysis methods in landslides susceptibility assessment


Published: May 18, 2022
Keywords:
Landslides GIS Geodatabase MCDA LSA
Constantinos Nefros
https://orcid.org/0000-0002-2075-4112
Constantinos Loupasakis
https://orcid.org/0000-0003-1822-6510
Abstract

Every year landslides cause many fatalities and destroy numerous infrastructures around the world. Due to their catastrophic results, scientific research studies are conducted, on a continuous basis, trying to determine the controlling and triggering factors, and to evaluate their contribution-weight to that phenomenon. In this direction, many of these studies use multicriteria decision analysis methods as they are quite effective and can be applied rather quickly. However, a large percentage of the new studies that use these methods, is usually devoted to the analysis of many previous research studies and the validation of their results, which usually leads to serious delays and requires significant resources. In this research, 82 relevant past studies are evaluated, and their results are integrated into a worldwide geospatial database, to present its potential as a decision-making tool, during the landslide susceptibility assessment. As it is revealed the results of its statistical and spatial correlation with the examined region’s prevailing parameters in a geographical information system environment, can provide critical indications- suggestions to a researcher and along with the applicability of the multicriteria decision analysis methods, that contain the use of other experts’ knowledge and experience, to lead to the rapid identification of the most critical landslide causal factors and the initial evaluation of their contribution-weight. These indications accelerate significant the whole process and reduce the risk for possible biased conclusions, which can render the whole method ineffective. Moreover, this study highlights the geodatabase’s potential to incorporate open-access data, from external spatial databases and to use them, during the process of the landslide susceptibility assessment.

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References
Abay, A., Barbieri, G. and Woldearegay, K. 2019. GIS-based landslide susceptibility evaluation using Analytical Hierarchy Process (AHP) approach: The case of Tarmaber District, Ethiopia. Momona Ethiopian Journal of Science, 11(1), 14-36. https://doi.org/10.4314/mejs.v11i1.2 .
Abedini, M., and Tulabi, S. 2018. Assessing LNRF, FR, and AHP models in landslide susceptibility mapping index: a comparative study of Nojian watershed in Lorestan province, Iran. Environmental Earth Sciences, 77, 405. https://doi.org/10.1007/s12665-018-7524-1.
Achu, A.L., and Reghunath, R. 2017. Application of analytical hierarchy process (AHP) for Landslide Susceptibility Mapping: A study from southern Western Ghats, Kerala, India. Proceedings of the Disaster, Risk and Vulnerability Conference (DRVC2017), Thiruvananthapuram, India, 29–31 March 2017.
Ajin, R.S., Loghin, A.M,. Vinod, P.G., Jacob, M.K,. Krishnamurthy, R.R. 2016. Landslide susceptible zone mapping using ARS and GIS techniques in selected taluks of Kottayam district, Kerala, India, International Journal of Applied Remote Sensing and GIS, 3(1), 16-25.
Akgun, A., Kıncal, C., and Pradhan, B. 2011. Application of remote sensing data and GIS for landslide risk assessment as an environmental threat to Izmir city (west Turkey). Environmental monitoring and assessment, 184, 5453-70. https://doi.org/10.1007/s10661-011-2352-8.
Ali, S., Biermanns, P., Haider, R., and Reicherter, K. 2019. Landslide susceptibility mapping by using a geographic information system (GIS) along the China–Pakistan Economic Corridor (Karakoram Highway), Pakistan. Natural Hazards and Earth System Science, 19, 999–1022. https://doi.org/10.5194/nhess-19-999-2019.
Anbalagan, R., Kumar, R., Lakshmanan, K., Parida, S., and Neethu, S. 2015. Landslide hazard zonation mapping using frequency ratio and fuzzy logic approach, a case study of Lachung Valley, Sikkim. Geoenviron. Disasters, 2, (1). https://doi.org/10.1186/s40677-014-0009-y.
Arabameri, A., Pradhan, B., Rezaei, K., Lee, S., and Sohrabi, M. 2019. An Ensemble Model for Landslide Susceptibility Mapping in a Forested Area. Geocarto International, 1-25. https://doi.org/10.1080/10106049.2019.1585484.
Bachri, S., and Shresta, R.P. 2010. Landslide Hazard Assessment Using Analytic Hierarchy Processing (AHP) and Geographic Information System in Kaligesing Mountain Area of Central Java Province Indonesia. 5th Annual International Workshop & Expo on Sumatra Tsunami Disaster & Recovery 2010, 9, 108–112.
Beck, H. E., Zimmermann, N. E., McVicar, T. R., Vergopolan, N., Berg, A., & Wood, E. F. 2018. Present and future Köppen–Geiger climate classification maps at 1-km resolution. Scientific Data, 5, 180214. https://doi.org/10.1038/sdata.2018.214.
Bhatt, B.P., Awasthi, K.D., Heyojoo, B.P., Silwal, T., and Kafle, G. 2013. Using Geographic Information System and Analytical Hierarchy Process in Landslide Hazard Zonation. Applied Ecology and Environmental Sciences, 1(2), 14-22. https://doi.org/10.12691/aees-1-2-1.
Blais-Stevens, A., Behnia, P., Kremer, M., Page A., Kung R., and Bonha-Carter G. 2012. Landslide susceptibility mapping of the Sea to Sky transportation corridor, British Columbia, Canada: comparison of two methods. Bulletin of Engineering Geology and the Environment, 71. 447–466. https://doi.org/10.1007/s10064-012-0421-z.
Boroumandi, M., Khamehchiyan, M., and Nikudel, M.R. 2015. Using of Analytic Hierarchy Process for Landslide Hazard Zonation in Zanjan Province, Iran. In: Lollino G. et al. (Eds) Engineering Geology for Society and Territory. Springer, Cham, 951-955. https://doi.org/10.1007/978-3-319-09057-3_165.
Chalkias, C., Ferentinou, M., and Polykretis, C. 2014. GIS Supported Landslide Susceptibility Modeling at Regional Scale: An Expert-Based Fuzzy Weighting Method. ISPRS International Journal of Geoinformation, 3, 523-539. https://doi.org/10.3390/ijgi3020523.
Chen, W., Hong, H., Panahi, M., Shahabi, H., Wang, Y., Shirzadi, A., Pirasteh, S., Alesheikh, A.A., Khosravi, K., Panahi, S., Rezaie, F., Li S., Jaafari, A., Bui, D.T. and Bin Ahmad, B. 2019. Spatial Prediction of Landslide Susceptibility Using GIS-Based Data Mining Techniques of ANFIS with Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO). Applied Sciences, 9, 3755. https://doi.org/10.3390/app9183755.
Cignetti, M., Godone, D., and Giordan, D. 2019. Shallow landslide susceptibility, Rupinaro catchment, Liguria (northwestern Italy). Journal of Maps, 15:2, 333-345, https://doi.org/10.1080/17445647.2019.1593252.
Cruden, D., and Vandine, D. 2013. Classification, Description, Causes and Indirect Effects: Canadian Technical Guidelines and Best Practices related to Landslides. Geological Survey of Canada. Open File 7359, 22p.
Dilley, M., Chen, R.S., Deichmann, U., Lerner-Lam, A.L. and Arnold, M. 2005. Natural Disaster Hotspots: A Global Risk Analysis. Washington, DC: World Bank. © World Bank. https://openknowledge.worldbank.org/handle/10986/7376.
El Bchari, F., Theilen-Willige, B., and Ait Malek, H. 2019. Landslide hazard zonation assessment using GIS analysis at the coastal area of Safi (Morocco). Proceeding of the International Cartographic Association (ICA), 2, 24. https://doi.org/10.5194/ica-proc-2-24-2019.
El Jazouli, A., Barakat, A., and Khellouk, R. 2019. GIS-multicriteria evaluation using AHP for landslide susceptibility mapping in Oum Er Rbia high basin (Morocco). Geoenvironmental Disasters, 6, 3 2019. https://doi.org/10.1186/s40677-019-0119-7.
Ercanoglu, M., Kasmer, O, and Temiz, N. 2008. Adaptation and comparison of expert opinion to analytical hierarchy process for landslide susceptibility mapping. Bulletin of Engineering Geology and the Environment, 67, 565-578. https://doi.org/10.1007/s10064-008-0170-1.
Ganas, A., Oikonomou, I. A., & Tsimi, C. (2013). NOAfaults: a digital database for active faults in Greece. Bulletin of the Geological Society of Greece, 47(2), 518-530. https://doi.org/10.12681/bgsg.11079.
Gorsevski, P., Jankowski, P., and Gessler, P. 2006. Heuristic approach for mapping landslide hazard integrating fuzzy logic with analytic hierarchy process. Control and Cybernetics, 35, 121–146.
Grozavu, A., Patriche, C., and Mihai, F. 2017. Application of AHP method for mapping slope geomorphic phenomena. Proceedings of the 17th International Multidisciplinary Scientific GeoConference SGEM 2017, 29 June - 5 July 2017, Albena, Bulgaria. https://doi.org/10.5593/sgem2017/23/S11.046.
Guzzetti, F. 2005. Landslide Hazard and Risk Assessment– Concepts, Methods and Tools for the Detection and Mapping of Landslides, for Landslides Susceptibility Zonation and Hazard Assessment, and for Landslide Risk Evaluation. PhD Thesis. Mathematics-Scientific Faculty, University of Bonn, Bonn, Germany. 389 p. https://nbn-resolving.org/urn:nbn:de:hbz:5N-08175.
Hervas de Diego, J., and Barredo Cano, J. I. 2001. Evaluacion de la Susceptibilidad de Deslizamientos mediante el uso conjunto de SIG, teledeteccion y metodos de evaluacion multicriterio. Aplicacion al barranco de Tirajana (Gran Canaria). V Simposio Nacional sobre Taludes y Laderas Inestables, Madrid, Spain, 27–30 November 2001, 305-316.
IGOS, 2004. Geohazards Theme Report: For the Monitoring of our Environment from Space and from Earth. European Space Agency Publication, Rome (Italy), p.55.
Intarawichian, N., and Dasananda, S. 2010. Analytical Hierarchy Process for landslide susceptibility mapping in lower Mae Chem watershed, Northern Thailand. Suranaree Journal of Science and Technology, 17(3), 277–92.
Ivanova, E. 2014. Landslide Susceptibility Mapping using Frequency Ratio and Analytic Hierarchy Process (AHP): Comparative study of two areas in Bulgaria. Analysis and Management of Changing Risk for Natural Hazards: International Conference, Padua, Italy, 18-19 Nov, p. AP23-1–AP23-9.
Jana, Sujoy & Sekac, Tingneyuc & Pal, Dilip. 2015. Landslide Hazard Investigation in Papua New Guinea-A Remote Sensing & GIS Approach. International Journal of Scientific Engineering and Research, 3, 79-83.
Jishnu E S, Ajith Joseph K, Sreenal Sreedhar, George Basil. 2017. Hazard mapping of landslide vulnerable zones in a Rainfed region of southern peninsular India – A Geospatial Perspective. International Research Journal of Engineering and Technology, 4, 7, pp.1350-1357.
Kavoura, K., and Sabatakakis, N. 2020. Investigating landslide susceptibility procedures in Greece. Landslides, 17, 127–145. https://doi.org/10.1007/s10346-019-01271-y.
Khodadad, S., and Jang, D.H. 2015. A comparative study of Analytical Hierarchy Process and Ordinary Least Square methods for landslide susceptibility mapping using GIS technology. Tojsat - Journal of science and technology, 2015, 5 (2), 7–16. https://www.tojsat.net/journals/tojsat/volumes/tojsat-volume05-i02.pdf.
Kil, S.H., Lee, D.K., Kim, J.H., Li, M.H., and Newman, G. 2016. Utilizing the Analytic Hierarchy Process to Establish Weighted Values for Evaluating the Stability of Slope Revegetation based on Hydroseeding Applications in South Korea. Sustainability, 8(1), 58. https://doi.org/10.3390/su8010058.
Kirschbaum, D., Stanley, T., and Zhou, Y. 2015. Spatial and temporal analysis of a global landslide catalog. Geomorphology, 249, p.4-15. https://doi.org/10.1016/j.geomorph.2015.03.016.
Komac, B., and Zorn, M. 2009. Statistical landslide susceptibility modeling on a national scale: The example of Slovenia. Revue roumaine de géographie, 53(2), 179-195.
Komac, M. 2006. A landslide susceptibility model using the Analytical Hierarchy Process method and multivariate statistics in perialpine Slovenia. Geomorphology, 74, 17-28. https://doi.org/10.1016/j.geomorph.2005.07.005.
Kottek, M., J. Grieser, C. Beck, B. Rudolf, and Rubel, F. 2006. World Map of the Köppen-Geiger climate classification updated. Meteorologische Zeitschrift, 15, 3, 259 - 263. https://doi.org/10.1127/0941-2948/2006/0130.
Kouli, M., Loupasakis, C., Soupios, P., Rozos, D., and Vallianatos, F. 2014. Landslide Susceptibility Mapping by comparing the WLC and WofE Multi-Criteria Methods in the West Crete Island, Greece. Environmental Earth Sciences, 72. https://doi.org/10.1007/s12665-014-3389-0.
Krušić, J., Marjanović, M., Samardzic-Petrovic, M., Abolmasov, B., Andrejev, K., and Miladinović, A. 2017. Comparison of expert, deterministic and Machine Learning approach for landslide susceptibility assessment in Ljubovija Municipality, Serbia. Geofizika, 34. 251-273. https://doi.org/10.15233/gfz.2017.34.15.
Kumar, R., and Anbalagan, R. 2016. Landslide Susceptibility Mapping Using Analytical Hierarchy Process (AHP) in Tehri Reservoir Rim Region, Uttarakhand. Journal of the Geological Society of India, 87. https://doi.org/10.1007/s12594-016-0395-8.
Ladas I., Fountoulis I., and Mariolakos I. 2007a. Using GIS and Multicriteria decision analysis in landslide susceptibility mapping - A case study in Messinia Prefecture area (SW Peloponnesus, Greece). Bulletin of the Geological Society of Greece, 40 (4): 1973‐1985 https://doi.org/10.12681/bgsg.17240.
Ladas I., Fountoulis I., and Mariolakos I. 2007b. Large scale landslide susceptibility mapping using gis-based weighted linear combination and multicriteria decision analysis – a case study in northern Messinia (SW Peloponnesus, Greece). Proceedings of the 8th Panhellenic Congress of the Geographical Society of Greece, 1, 99‐108.
Laldintluanga H., Lalbiakmawia, F. and Lalbiaknungi, Er. 2016. Landslide Hazard Zonation Along State Highway Between Aizawl City and Aibawk Town, Mizoram, India. Using Geospatial Techniques, 5, 342-355.
Lallianthanga R.K., and Lalbiakmawia, F. 2013. Micro-Level Landslide Hazard Zonation of Saitual Town, Mizoram, India Using Remote Sensing and GIS Techniques. International Journal of Engineering Sciences & Research Technology, 2(9), 2531-2546.
Lallianthanga R.K., and Lalbiakmawia, F. 2014. Landslide Susceptibility Zonation of Kolasib District, Mizoram, India Using Remote Sensing and GIS Techniques. International Journal of Engineering Sciences & Research Technology, 3 (3), 1402-1410.
Laltlankima, F. and Lalbiakmawia, F. 2016. Landslide Hazard Zonation Along National Highway Between Aizawl City and Lengpui Airport, Mizoram, India Using Geospatial Techniques. International Journal of Engineering Sciences & Research Technology, 5(7), 1024–1033. https://doi.org/10.5281/zenodo.57980.
Lin, L., Lin, Q., and Wang, Y. 2017. Landslide susceptibility mapping on a global scale using the method of logistic regression. Natural Hazards and Earth System Sciences, 17, 1411-1424. https://doi.org/10.5194/nhess-17-1411-2017.
Malamud, B.D., Turcotte, D.L., Guzzetti, F. and Reichenbach, P. 2004. Landslide inventories and their statistical properties. Earth Surf. Process. Landforms, 29, 687-711. https://doi.org/10.1002/esp.1064.
Maleki, Mohammad & Rahmati, Mahdis & Sadidi, Javad & Babaee, Ehsan. 2014. Landslide risk zonation using AHP method and GIS in Malaverd catchment, Kermanshah, Iran. Conference Paper at the International Conference on Geospatial Information Research (GI Research 2014), 15-17 November 2014, Iran.
Mallick, J., Singh, R.K., AlAwadh, M.A., Islam S., Khan R. A. and Qureshi N. M. 2018. GIS-based landslide susceptibility evaluation using fuzzy-AHP multi-criteria decision-making techniques in the Abha Watershed, Saudi Arabia. Environmental Earth Sciences, 77, 276. https://doi.org/10.1007/s12665-018-7451-1.
Mandal, S., and Maiti, R. 2011. Landslide Susceptibility Analysis of Shiv-Khola Watershed, Darjiling: A Remote Sensing & GIS Based Analytical Hierarchy Process (AHP). Journal of the Indian Society of Remote Sensing, 40. https://doi.org/10.1007/s12524-011-0160-9.
Mandal, B., and Mandal, S. 2018. Analytical hierarchy process (AHP) based landslide susceptibility mapping of Lish river basin of Eastern Darjeeling Himalaya, India. Advances in Space Research. 62. https://doi.org/10.1016/j.asr.2018.08.008.
Marjanović, M., Abolmasov, B., Djuric, U., and Bogdanovic, S. 2013. Impact of geo-environmental factors on landslide susceptibility using an AHP method: A case study of Fruska Gora Mt., Serbia. Geoloski anali Balkanskoga poluostrva, 74, 91-100. https://doi.org/10.2298/gabp1374091m.
Mijani, N. and Neysani Samani, N. 2017. Comparison Of Fuzzy-Based Models in Landslide Hazard Mapping. International Archives of the Photogrammetry. Remote Sensing and Spatial Information Science, XLII-4/W4, 407–416. https://doi.org/10.5194/isprs-archives-XLII-4-W4-407-2017.
Milevski, I., Dragicevic, S., and Zorn, M. 2019. Statistical and expert-based landslide susceptibility modeling on a national scale applied to North Macedonia. Open Geosciences, 11, 750-764. https://doi.org/10.1515/geo-2019-0059.
Mokarram, M., and Zarei, A.R. 2018. Landslide Susceptibility Mapping Using Fuzzy-AHP. Geotechnical and Geological Engineering, 36, 3931–3943. https://doi.org/10.1007/s10706-018-0583-y.
Moradi, M., Bazyar, M.H., and Mohammadi, Z. 2012. GIS-based landslide susceptibility mapping by AHP method, a case study, Dena City, Iran. Journal of Basic and Applied Scientific Research, 2(7), 6715-6723.
Moradi, S., and Rezaei, M. 2014. A GIS-based comparative study of the analytic hierarchy process, bivariate statistics and frequency ratio methods for landslide susceptibility mapping in part of the Tehran metropolis, Iran. Geopersia, 4, 45-61. https://doi.org/10.22059/jgeope.2014.51191.
Myronidis, D., Papageorgiou, C., and Theophanous, S. 2015. Landslide susceptibility mapping based on landslide history and analytic hierarchy process (AHP). Natural Hazards, 81. https://doi.org/10.1007/s11069-015-2075-1.
Nahayo, L., Kalisa, E., Maniragaba, A., and Nshimiyimana, F. 2019. Comparison of analytical hierarchy process and certain factor models in landslide susceptibility mapping in Rwanda. Modeling Earth Systems and Environment, 5, 885–895. https://doi.org/10.1007/s40808-019-00575-1.
Nguyen T.T.N., and Liu, C.C. 2019. A New Approach Using AHP to Generate Landslide Susceptibility Maps in the Chen-Yu-Lan Watershed, Taiwan. Sensors, 19, 505. https://doi.org/10.3390/s19030505.
Nicu, I. C. 2018. Application of analytic hierarchy process, frequency ratio, and statistical index to landslide susceptibility: an approach to endangered cultural heritage. Environmental Earth Sciences, 77, 79. https://doi.org/10.1007/s12665-018-7261-5.
Papanikolaou D., and Diakakis M. 2011. Changes in the intensity and distribution of natural disasters. Report for the Climate Change Impacts Study Committee. Bank of Greece.
Patil, A.S., and Panhalkar, S.S. 2019. Analytical hierarchy process for landslide hazard zonation of South-Western ghats of Maharashtra, India. Disaster Advances, 12(1), 26-33.
Perera, E., Ranagalage, M., Jayawardana, D., and Jayasingha, P. 2018. Spatial Multi Criteria Evaluation (SMCE) Model for Landslide Hazard Zonation in Tropical Hilly Environment: A Case Study from Kegalle. Geoinformatics and Geostatistics: An Overview, S3, 1-9. https://doi.org/10.4172/2327-4581.S3-004 .
Pourghasemi, H. R., Moradi, H. and Aghda, S. 2013. Landslide susceptibility mapping by binary logistic regression, analytical hierarchy process, and statistical index models and assessment of their performances. Natural Hazard, 69, 749–779. https://doi.org/10.1007/s11069-013-0728-5 .
Quan, H.C., and Lee, B.G. 2012. GIS-based landslide susceptibility mapping using analytic hierarchy process and artificial neural network in Jeju (Korea). KSCE Journal of Civil Engineering, 16, 1258-1266. https://doi.org/10.1007/s12205-012-1242-0.
Rahaman, S. A., Aruchamy S., and Jegankumar R. 2014. Geospatial Approach on Landslide Hazard Zonation Mapping Using Multicriteria Decision Analysis: A Study on Coonoor and Ooty, Part of Kallar Watershed, The Nilgiris, Tamil Nadu. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL, 1417-1422. https://doi.org/10.5194/isprsarchives-XL-8-1417-2014.
Reichenbach, P., Rossi, M., Malamud, B., Mihir, M., and Guzzetti, F. 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.
Rodriguez, A., Tapia, A., and Albornoz C. 2013. Mass Movement Susceptibility in the Socoroma Valley Andean Precordillera of Arica and Parinacota. Diálogo Andino, 44, 25–39. https://doi.org/10.4067/S0719-26812014000200004.
Roy, J., and Saha, S. 2019. Landslide susceptibility mapping using knowledge driven statistical models in Darjeeling District, West Bengal, India. Geoenvironmental Disasters, 6, 11. https://doi.org/10.1186/s40677-019-0126-8.
Rozos, D., Bathrellos, G., and Skilodimou, H. 2010. Landslide susceptibility mapping of the northeastern part of Achaia Prefecture using Analytical Hierarchical Process and GIS techniques. Bulletin of Geological Society of Greece, 43, 1637–1646. https://doi.org/10.12681/bgsg.11338.
Rozos, D., Bathrellos, G., and Skillodimou, H. 2011. Comparison of the implementation of rock engineering system and analytic hierarchy process methods, upon landslide susceptibility mapping, using GIS: A case study from the Eastern Achaia County of Peloponnesus, GREECE. Environmental earth sciences, 63, 49-63. https://doi.org/10.1007/s12665-010-0687-z.
Ruff, M. and Czurda, K. 2008. Landslide susceptibility analysis with a heuristic approach in the Eastern Alps (Vorarlberg, Austria). Geomorphology, 94(3–4), 314-324. https://doi.org/10.1016/j.geomorph.2006.10.032.
Saranathan, S.E., and Mani, S. 2016. Landslide Susceptibility Zonation mapping using Multi-criterion Analysis–CNG 37 Ghat section, Nadugani, Gudalur Taluk, The Nilgiris–Using Geological Factors. International Journal of Earth Sciences and Engineering, 09(04), 1441 - 1446.
Sauerborn, R., and Ebi, K. 2012. Climate change and natural disasters – integrating science and practice to protect health. Global Health Action, 5, 1-7. https://doi.org/10.3402/gha.v5i0.19295.
Semlali, I., Ouadif, L., and Bahi, L. 2019. Landslide susceptibility mapping using the analytical hierarchy process and GIS. Current Science, 116(5), 773-779. https://doi.org/10.18520/cs/v116/i5/773-779.
Shahabi, H., and Hashim, M. 2015. Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment. Scientific Reports, 5, 9899. https://doi.org/10.1038/srep09899.
Sprague- Wheeler, D.K. 2003. The use of remote sensing imagery for evaluation of post-wildfire susceptibility to landslide and erosion hazards in the Salmon Challis National Forest, Lemhi County, Idaho. MSc Thesis, Idaho State University, Idaho, Pocatello ID 83209-8130.
Starkel, L. and Sarkar, S. 2002. Different frequency of threshold rainfalls transforming the margin of Sikkimese and Bhutanese Himalayas. Studia Geomorphologica Carpatho–Balcanica, 36, 51-67.
Styron, R., and Pagani, M. 2020. The GEM Global Active Faults Database. Earthquake Spectra, 36, 160-180. https://doi.org/10.1177/8755293020944182.
Tavoularis, N., Koumantakis, I., Rozos, D., Koukis, G. 2015. An implementation of rock engineering system (RES) for ranking the instability potential of slopes in Greek territory. An application in Tsakona area (Peloponnese -prefecture of Arcadia). Bulletin of the Geological Society of Greece, 49, 38-58. https://doi.org/10.12681/bgsg.11049.
Tavoularis, N., and Kirkos M. 2019. Estimation of landslide susceptibility in some islands of the Attica Region, through the use of Rock Engineering System (RES). Conference: 8th Hellenic Congress of Geotechnical Engineering, 6-8 November 2019, Athens, Greece.
Tazik, E., Jahantab, Z., Bakhtiari, M., Rezaei, A., and Kazem Alavipanah, S. 2014. Landslide susceptibility mapping by combining the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process in Dozain basin. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-2/W3, 267–272. https://doi.org/10.5194/isprsarchives-XL-2-W3-267-2014.
Tsangaratos, P., and Rozos, D. 2013. Producing landslide susceptibility maps by applying expert knowledge in a GIS – based environment. Bulletin of the Geological Society of Greece, 47(3), 1539-1549. https://doi.org/10.12681/bgsg.10993.
Vijith H., and Dodge-Wan, D. 2019. Modelling terrain erosion susceptibility of logged and regenerated forested region in northern Borneo through the Analytical Hierarchy Process (AHP) and GIS techniques. Geoenvironmental Disasters, 6, 8. https://doi.org/10.1186/s40677-019-0124-x.
Westen, C.J., Asch, T.W.J., and Soeters, R. 2006. Landslide hazard and risk zonation-why is it so difficult? Bull Eng Geol Environ. Bulletin of Engineering Geology and Environment, 65, 167-184. https://doi.org/10.1007/s10064-005-0023-0 .
Xiong, T., Indrawan, I., and Putra, D. 2018. Landslide Susceptibility Mapping Using Analytical Hierarchy Process, Statistical Index, Index of Enthropy, and Logistic Regression Approaches in the Tinalah Watershed, Yogyakarta. Journal of Applied Geology, 2(1), 78-93. https://doi.org/10.22146/jag.39983.
Yi, Y., Zhang, Z., Zhang, W., Xu, Q., Deng, C., and Li, Q. 2019. GIS-based earthquake-triggered-landslide susceptibility mapping with an integrated weighted index model in Jiuzhaigou region of Sichuan Province, China. Natural Hazards and Earth System Sciences, 19, 1973–1988. https://doi.org/10.5194/nhess-19-1973-2019.
Zhao H, Yao L, Mei G, Liu T, Ning Y. A. 2017. Fuzzy Comprehensive Evaluation Method Based on AHP and Entropy for a Landslide Susceptibility Map. Entropy, 19(8), 396. https://doi.org/10.3390/e19080396.
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