Decoding vegetation's role in landslide susceptibility mapping: An integrated review of techniques and future directions

Yangyang Li , Wenhui Duan

Biogeotechnics ›› 2024, Vol. 2 ›› Issue (1) : 100056

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Biogeotechnics ›› 2024, Vol. 2 ›› Issue (1) :100056 DOI: 10.1016/j.bgtech.2023.100056
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Decoding vegetation's role in landslide susceptibility mapping: An integrated review of techniques and future directions

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Abstract

Rainfall-induced landslides, exacerbated by climate change, require urgent attention to identify vulnerable regions and propose effective risk mitigation measures. Extensive research underscores the significant impact of vegetation on soil properties and slope stability, emphasizing the necessity to incorporate vegetation effects into regional landslide susceptibility mapping. This review thoroughly examines research integrating vegetation into landslide susceptibility mapping, encompassing qualitative, semi-quantitative, and quantitative forecasting methods. It highlights the importance of incorporating vegetation aspects into these methods for comprehensive and accurate landslide susceptibility assessment. This review explores the diverse roles of vegetation in slope stability, covering both aggregated impacts and individual influences, including mechanical and hydrological effects on soil properties, as well as the implications of evapotranspiration and rainwater interception on slope stability. While aggregated roles are integrated into non-deterministic methods as input layers, individual roles are considered in deterministic methods. In the application of deterministic methods, it is noteworthy that a considerable number of studies primarily concentrate on the mechanical impact, particularly the reinforcement provided by root cohesion. The review also explores limitations and highlights future research prospects. In the context of mapping landslide susceptibility amid changing climatic conditions, data-driven techniques encounter challenges, while deterministic methods present their advantages. Stressing the significance of hydrological impacts, the paper recommends incorporating vegetation influences on unsaturated soil properties, including the soil water characteristic curve and soil permeability, along with pre-wetting suction due to evapotranspiration and potential rainwater interception.

Keywords

Landslide Susceptibility Maps / Vegetation Impacts / Land Cover / Unsaturated Soil Mechanics / Rainfall-Induced Landslides

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Yangyang Li, Wenhui Duan. Decoding vegetation's role in landslide susceptibility mapping: An integrated review of techniques and future directions. Biogeotechnics, 2024, 2(1): 100056 DOI:10.1016/j.bgtech.2023.100056

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CRediT authorship contribution statement

Yangyang Li: Writing - original draft, Methodology, Formal analysis, Data curation, Conceptualization. Wenhui Duan: Writing - review & editing, Validation, Supervision, Methodology, Conceptualization.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

[1]

Aleotti, P., & Chowdhury, R. (1999). Landslide hazard assessment: Summary review and new perspectives. Bulletin of Engineering Geology and the Environment, 58, 21-44. https://doi.org/10.1007/s100640050066

[2]

Ali, F. H., & Osman, N. (2008). Shear strength of a soil containing vegetation roots. Soils and Foundations, 48, 587-596. https://doi.org/10.3208/sandf.48.587

[3]

Arabameri, A., Pradhan, B., Rezaei, K., & Lee, C. W. (2019). Assessment of landslide susceptibility using statistical- and artificial intelligence-based FR-RF integrated model and multiresolution DEMs. Remote Sensing, 11, 999. https://doi.org/10.3390/rs11090999

[4]

Ayalew, L., & Yamagishi, H. (2005). The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology, 65, 15-31. https://doi.org/10.1016/j.geomorph.2004.06.010

[5]

Bathurst, J. C., Burton, A., Clarke, B. G., & Gallart, F. (2006). Application of the SHETRAN basin-scale, landslide sediment yield model to the Llobregat basin, Spanish Pyrenees. Hydrological Processes, 20, 3119-3138. https://doi.org/10.1002/hyp.6151

[6]

Baum, R.L., Savage, W.Z., Godt, J.W., 2008. TRIGRS: A Fortran Program for Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis, Version 2.0. US Geological Survey Reston, VA, USA.

[7]

Bijukchhen, S. M., Kayastha, P., & Dhital, M. R. (2013). A comparative evaluation of heuristic and bivariate statistical modelling for landslide susceptibility mappings in Ghurmi-Dhad Khola, east Nepal. Arabian Journal of Geosciences, 6, 2727-2743. https://doi.org/10.1007/s12517-012-0569-7

[8]

Bordoloi, S., & Ng, C. W. W. (2020). The effects of vegetation traits and their stability functions in bio-engineered slopes: A perspective review. Engineering Geology, 275, Article 105742. https://doi.org/10.1016/j.enggeo.2020.105742

[9]

Bordoloi, S., Ni, J., & Ng, C. W. W. (2020). Soil desiccation cracking and its characterization in vegetated soil: A perspective review. Science of The Total Environment, 729, Article 138760. https://doi.org/10.1016/j.scitotenv.2020.138760

[10]

Bordoni, M., Meisina, C., Vercesi, A., Bischetti, G. B., Chiaradia, E. A., Vergani, C., Chersich, S., Valentino, R., Bittelli, M., Comolli, R., Persichillo, M. G., & Cislaghi, A. (2016). Quantifying the contribution of grapevine roots to soil mechanical reinforcement in an area susceptible to shallow landslides. Soil and Tillage Research, 163, 195-206. https://doi.org/10.1016/j.still.2016.06.004

[11]

Brardinoni, F., Slaymaker, O., & Hassan, M. A. (2003). Landslide inventory in a rugged forested watershed: A comparison between air-photo and field survey data. Geomorphology, 54, 179-196. https://doi.org/10.1016/S0169-555X(02)00355-0

[12]

Bregoli, F., Medina, V., Chevalier, G., Hürlimann, M., & Bateman, A. (2015). Debris-flow susceptibility assessment at regional scale: Validation on an alpine environment. Landslides, 12, 437-454. https://doi.org/10.1007/s10346-014-0493-x

[13]

Cascini, L. (2008). Applicability of landslide susceptibility and hazard zoning at different scales. Engineering Geology, 102, 164-177. https://doi.org/10.1016/j.enggeo.2008.03.016

[14]

Catani, F., Lagomarsino, D., Segoni, S., & Tofani, V. (2013). Landslide susceptibility estimation by random forests technique: Sensitivity and scaling issues. Natural Hazards and Earth System Sciences, 13, 2815-2831. https://doi.org/10.5194/nhess-13-2815-2013

[15]

Chen, C., & Fan, L. (2023a). An attribution deep learning interpretation model for landslide susceptibility mapping in the three gorges reservoir area. IEEE Transactions on Geoscience and Remote Sensing, 61, 1-15. https://doi.org/10.1109/TGRS.2023.3323668

[16]

Chen, C., & Fan, L. (2023b). Selection of contributing factors for predicting landslide susceptibility using machine learning and deep learning models. Stochastic Environmental Research and Risk Assessment. https://doi.org/10.1007/s00477-023-02556-4

[17]

Chigira, M., Duan, F., Yagi, H., & Furuya, T. (2004). Using an airborne laser scanner for the identification of shallow landslides and susceptibility assessment in an area of ignimbrite overlain by permeable pyroclastics. Landslides, 1, 203-209. https://doi.org/10.1007/s10346-004-0029-x

[18]

Ciurleo, M., Cascini, L., & Calvello, M. (2017). A comparison of statistical and deterministic methods for shallow landslide susceptibility zoning in clayey soils. Engineering Geology, 223, 71-81. https://doi.org/10.1016/j.enggeo.2017.04.023

[19]

Crosta, G. B., & Frattini, P. (2008). Rainfall-induced landslides and debris flows. Hydrological Processes, 22, 473-477. https://doi.org/10.1002/hyp.6885

[20]

Crozier, M. J. (2010). Deciphering the effect of climate change on landslide activity: A review. Geomorphology, 124, 260-267. https://doi.org/10.1016/j.geomorph.2010.04.009

[21]

Dai, F. C., Lee, C. F., Li, J., & Xu, Z. W. (2001). Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong. Environmental Geology, 40, 381-391. https://doi.org/10.1007/s002540000163

[22]

Devara, M., Tiwari, A., & Dwivedi, R. (2021). Landslide susceptibility mapping using MT- InSAR and AHP enabled GIS-based multi-criteria decision analysis. Geomatics, Natural Hazards and Risk, 12, 675-693. https://doi.org/10.1080/19475705.2021.1887939

[23]

Fan, X., Scaringi, G., Korup, O., West, A. J., van Westen, C. J., Tanyas, H., Hovius, N., Hales, T. C., Jibson, R. W., Allstadt, K. E., Zhang, L., Evans, S. G., Xu, C., Li, G., Pei, X., Xu, Q., & Huang, R. (2019). Earthquake-induced chains of geologic hazards: Patterns, mechanisms, and impacts. Reviews of Geophysics, 57, 421-503. https://doi.org/10.1029/2018RG000626

[24]

Feizizadeh, B., ShadmanRoodposhti, M., Jankowski, P., & Blaschke, T. (2014). A GIS- based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping. Computers & Geosciences, 73, 208-221. https://doi.org/10.1016/j.cageo.2014.08.001

[25]

Gariano, S. L., & Guzzetti, F. (2016). Landslides in a changing climate. Earth-Science Reviews, 162, 227-252. https://doi.org/10.1016/j.earscirev.2016.08.011

[26]

Gong, Q., Wang, J., Zhou, P., & Guo, M. (2021). A regional landslide stability analysis method under the combined impact of rainfall and vegetation roots in South China. Advances in Civil Engineering, 2021, Article e5512281. https://doi.org/10.1155/2021/5512281

[27]

Guo, Z., Chen, L., Gui, L., Du, J., Yin, K., & Do, H. M. (2020a). Landslide displacement prediction based on variational mode decomposition and WA-GWO-BP model. Landslides, 17, 567-583. https://doi.org/10.1007/s10346-019-01314-4

[28]

Guo, Z., Chen, L., Yin, K., Shrestha, D. P., & Zhang, L. (2020b). Quantitative risk assessment of slow-moving landslides from the viewpoint of decision-making: A case study of the Three Gorges Reservoir in China. Engineering Geology, 273, Article 105667. https://doi.org/10.1016/j.enggeo.2020.105667

[29]

Guo, Z., Torra, O., Hürlimann, M., Abancó C., & Medina, V. (2022). FSLAM: A QGIS plugin for fast regional susceptibility assessment of rainfall-induced landslides. Environmental Modelling & Software, 150, Article 105354. https://doi.org/10.1016/j.envsoft.2022.105354

[30]

Guzzetti, F., Mondini, A. C., Cardinali, M., Fiorucci, F., Santangelo, M., & Chang, K. T. (2012). Landslide inventory maps: New tools for an old problem. Earth-Science Reviews, 112, 42-66. https://doi.org/10.1016/j.earscirev.2012.02.001

[31]

Guzzetti, F., Peruccacci, S., Rossi, M., & Stark, C. P. (2008). The rainfall intensity-duration control of shallow landslides and debris flows: An update. Landslides, 5, 3-17. https://doi.org/10.1007/s10346-007-0112-1

[32]

Guzzetti, F., Reichenbach, P., Ardizzone, F., Cardinali, M., & Galli, M. (2006). Estimating the quality of landslide susceptibility models. Geomorphology, 81, 166-184. https://doi.org/10.1016/j.geomorph.2006.04.007

[33]

Haque, U., DaSilva, P. F., Devoli, G., Pilz, J., Zhao, B., Khaloua, A., Wilopo, W., Andersen, P., Lu, P., Lee, J., Yamamoto, T., Keellings, D., Wu, J. H., & Glass, G. E. (2019). The human cost of global warming: Deadly landslides and their triggers (1995-2014). Science of The Total Environment, 682, 673-684. https://doi.org/10.1016/j.scitotenv.2019.03.415

[34]

Huang, F., Chen, J., Liu, W., Huang, J., Hong, H., & Chen, W. (2022). Regional rainfall- induced landslide hazard warning based on landslide susceptibility mapping and a critical rainfall threshold. Geomorphology, 408, Article 108236. https://doi.org/10.1016/j.geomorph.2022.108236

[35]

Hürlimann, M., Guo, Z., Puig-Polo, C., & Medina, V. (2022). Impacts of future climate and land cover changes on landslide susceptibility: Regional scale modelling in the Val daAran region (Pyrenees, Spain). Landslides, 19, 99-118. https://doi.org/10.1007/s10346-021-01775-6

[36]

Keefer, D. K. (1984). Landslides caused by earthquakes. Geological Society of America Bulletin, 95, 406-421.

[37]

Kim, Y., Rahardjo, H., Nistor, M. M., Satyanaga, A., Leong, E. C., & Sham, A. W. L. (2022). Assessment of critical rainfall scenarios for slope stability analyses based on historical rainfall records in Singapore. Environmental Earth Sciences, 81, 39. https://doi.org/10.1007/s12665-021-10160-4

[38]

Kirschbaum, D., Stanley, T., & Zhou, Y. (2015). Spatial and temporal analysis of a global landslide catalog. Geomorphology, 249, 4-15. https://doi.org/10.1016/j.geomorph.2015.03.016

[39]

Lacasse, S.,Nadim, F., Kalsnes, B., 2010.Living with Landslide Risk 41.

[40]

Lambe, T. W., & Whitman, R. V. (1991). Soil Mechanics. volume 10John Wiley & Sons.

[41]

Lee, L. M., Gofar, N., & Rahardjo, H. (2009). A simple model for preliminary evaluation of rainfall-induced slope instability. Engineering Geology, 108, 272-285. https://doi.org/10.1016/j.enggeo.2009.06.011

[42]

Leung, A. K., Boldrin, D., Liang, T., Wu, Z. Y., Kamchoom, V., & Bengough, A. G. (2018). Plant age effects on soil infiltration rate during early plant establishment. Géotechnique, 68, 646-652. https://doi.org/10.1680/jgeot.17.T.037

[43]

Li, P., Xiao, X., Wu, L., Li, X., Zhang, H., & Zhou, J. (2022a). Study on the shear strength of root-soil composite and root reinforcement mechanism. Forests, 13, 898. https://doi.org/10.3390/f13060898

[44]

Li, S., Wang, Z., & Stutz, H. H. (2023). State-of-the-art review on plant-based solutions for soil improvement. BiogeotechnicsArticle 100035. https://doi.org/10.1016/j.bgtech.2023.100035

[45]

Li, Y., Rahardjo, H., Satyanaga, A., Rangarajan, S., & Lee, D. T. T. (2022b). Soil database development with the application of machine learning methods in soil properties prediction. Engineering Geology, 306, Article 106769. https://doi.org/10.1016/j.enggeo.2022.106769

[46]

Li, Y., Satyanaga, A., & Rahardjo, H. (2021). Characteristics of unsaturated soil slope covered with capillary barrier system and deep-rooted grass under different rainfall patterns. International Soil and Water Conservation Research, 9, 405-418. https://doi.org/10.1016/j.iswcr.2021.03.004

[47]

Li, Y., Wang, X., & Mao, H. (2020). Influence of human activity on landslide susceptibility development in the Three Gorges area. Natural Hazards, 104, 2115-2151. https://doi.org/10.1007/s11069-020-04264-6

[48]

Liu, J. G., Mason, P. J., Clerici, N., Chen, S., Davis, A., Miao, F., Deng, H., & Liang, L. (2004). Landslide hazard assessment in the Three Gorges area of the Yangtze river using ASTER imagery: Zigui-Badong. Geomorphology, 61, 171-187. https://doi.org/10.1016/j.geomorph.2003.12.004

[49]

Löbmann, M. T., Geitner, C., Wellstein, C., & Zerbe, S. (2020). The influence of herbaceous vegetation on slope stability - A review. Earth-Science Reviews, 209, Article 103328. https://doi.org/10.1016/j.earscirev.2020.103328

[50]

Mallick, J., Singh, R. K., AlAwadh, M. A., Islam, S., Khan, R. A., & Qureshi, M. N. (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

[51]

Masi, E. B., Segoni, S., & Tofani, V. (2021). Root reinforcement in slope stability models: A review. Geosciences, 11, 212. https://doi.org/10.3390/geosciences11050212

[52]

Masi, E. B., Tofani, V., Rossi, G., Cuomo, S., Wu, W., Salciarini, D., Caporali, E., & Catani, F. (2023). Effects of roots cohesion on regional distributed slope stability modelling. CATENA, 222, Article 106853. https://doi.org/10.1016/j.catena.2022.106853

[53]

Medina, V., Hürlimann, M., Guo, Z., Lloret, A., & Vaunat, J. (2021). Fast physically-based model for rainfall-induced landslide susceptibility assessment at regional scale. CATENA, 201, Article 105213. https://doi.org/10.1016/j.catena.2021.105213

[54]

Merghadi, A., Yunus, A. P., Dou, J., Whiteley, J., ThaiPham, B., Bui, D. T., Avtar, R., & Abderrahmane, B. (2020). Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance. Earth-Science Reviews, 207, Article 103225. https://doi.org/10.1016/j.earscirev.2020.103225

[55]

Mokarram, M., & 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

[56]

Mondini, A. C., Guzzetti, F., Chang, K. T., Monserrat, O., Martha, T. R., & Manconi, A. (2021). Landslide failures detection and mapping using synthetic aperture radar: Past, present and future. Earth-Science Reviews, 216, Article 103574. https://doi.org/10.1016/j.earscirev.2021.103574

[57]

Mondini, A. C., Guzzetti, F., Reichenbach, P., Rossi, M., Cardinali, M., & Ardizzone, F. (2011). Semi-automatic recognition and mapping of rainfall induced shallow landslides using optical satellite images. Remote Sensing of Environment, 115, 1743-1757. https://doi.org/10.1016/j.rse.2011.03.006

[58]

Montgomery, D. R., & Dietrich, W. E. (1994). A physically based model for the topographic control on shallow landsliding. Water Resources Research, 30, 1153-1171. https://doi.org/10.1029/93WR02979

[59]

Montrasio, L. (2000). Stability analysis of soil-slip. WIT transactions on ecology and the environment, 45.

[60]

Montrasio, L., Gatto, M. P. A., & Miodini, C. (2023). The role of plants in the prevention of soil-slip: The G-SLIP model and its application on territorial scale through G-XSLIP platform. Landslides, 20, 1149-1165. https://doi.org/10.1007/s10346-023-02031-9

[61]

Myronidis, D., Papageorgiou, C., & Theophanous, S. (2016). Landslide susceptibility mapping based on landslide history and analytic hierarchy process (AHP). Natural Hazards, 81, 245-263. https://doi.org/10.1007/s11069-015-2075-1

[62]

Nandi, A., & Shakoor, A. (2010). A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses. Engineering Geology, 110, 11-20. https://doi.org/10.1016/j.enggeo.2009.10.001

[63]

Ng, C. W. W., Kamchoom, V., & Leung, A. K. (2016). Centrifuge modelling of the effects of root geometry on transpiration-induced suction and stability of vegetated slopes. Landslides, 13, 925-938. https://doi.org/10.1007/s10346-015-0645-7

[64]

Ni, J., Leung, A., & Ng, C. (2019a). Modelling effects of root growth and decay on soil water retention and permeability. Canadian Geotechnical Journal, 56, 1049-1055. https://doi.org/10.1139/cgj-2018-0402

[65]

Ni, J., Leung, A., Ng, C., & Shao, W. (2018). Modelling hydro-mechanical reinforcements of plants to slope stability. Computers and Geotechnics, 95, 99-109. https://doi.org/10.1016/j.compgeo.2017.09.001

[66]

Ni, J., Leung, A. K., & Ng, C. W. W. (2019b). Unsaturated hydraulic properties of vegetated soil under single and mixed planting conditions. Géotechnique, 69, 554-559. https://doi.org/10.1680/jgeot.17.T.044

[67]

Niethammer, U., James, M. R., Rothmund, S., Travelletti, J., & Joswig, M. (2012). UAV- based remote sensing of the Super-Sauze landslide: Evaluation and results. Engineering Geology, 128, 2-11. https://doi.org/10.1016/j.enggeo.2011.03.012

[68]

Pack, R.T., Tarboton, D.G., Goodwin, C.N., 1998. The SINMAP Approach to Terrain Stability Mapping.

[69]

Petley, D. (2012). Global patterns of loss of life from landslides. Geology, 40, 927-930. https://doi.org/10.1130/G33217.1

[70]

Rahardjo, H., Li, Y., & Satyanaga, A. (2023a). The importance of unsaturated soil properties in the development of slope susceptibility map for Old Alluvium in Singapore. E3S Web of Conferences, 382, 06009. https://doi.org/10.1051/e3sconf/202338206009

[71]

Rahardjo, H., Ong, T. H., Rezaur, R. B., & Leong, E. C. (2007). Factors controlling instability of homogeneous soil slopes under rainfall. Journal of Geotechnical and Geoenvironmental Engineering, 133, 1532-1543. https://doi.org/10.1061/(ASCE)1090-0241(2007)133:12(1532)

[72]

Rahardjo, H., Satyanaga, A., Leong, E. C., Santoso, V. A., & Ng, Y. S. (2014). Performance of an instrumented slope covered with shrubs and deep-rooted grass. Soils and Foundations, 54, 417-425. https://doi.org/10.1016/j.sandf.2014.04.010

[73]

Rahardjo, H., Satyanaga, A., Wang, C. L., Wong, J. L. H., & Lim, V. H. (2020). Effects of unsaturated properties on stability of slope covered with Caesalpinia crista in Singapore. Environmental Geotechnics, 7, 393-403. https://doi.org/10.1680/jenge.17.

[74]

Rahardjo, H., Zhai, Q., Satyanaga, A., Li, Y., Rangarajan, S., & Rahimi, A. (2023b). Slope susceptibility map for preventive measures against rainfall-induced slope failure. Urban Lifeline, 1, 5. https://doi.org/10.1007/s44285-023-00006-9

[75]

Rahimi, A., Rahardjo, H., & Leong, E. C. (2011). Effect of antecedent rainfall patterns on rainfall-induced slope failure. Journal of Geotechnical and Geoenvironmental Engineering, 137, 483-491. https://doi.org/10.1061/(ASCE)GT.1943-5606.0000451

[76]

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. https://doi.org/10.1016/j.earscirev.2018.03.001

[77]

Reid, M. E., Christian, S. B., Brien, D. L., & Henderson, S. (2015). Scoops3D—software to analyze three-dimensional slope stability throughout a digital landscape. US Geological Survey Techniques and Methods, book, 14.

[78]

Rigon, R., Bertoldi, G., & Over, T. M. (2006). GEOtop: A distributed hydrological model with coupled water and energy budgets. Journal of Hydrometeorology, 7, 371-388. https://doi.org/10.1175/JHM497.1

[79]

Rossi, G., Catani, F., Leoni, L., Segoni, S., & Tofani, V. (2013). HIRESSS: A physically based slope stability simulator for HPC applications. Natural Hazards and Earth System Sciences, 13, 151-166. https://doi.org/10.5194/nhess-13-151-2013

[80]

Saadatkhah, N., Mansor, S., Kassim, A., Lee, L. M., Saadatkhah, R., & Sobhanmanesh, A. (2016). Regional modeling of rainfall-induced landslides using TRIGRS model by incorporating plant cover effects: Case study in Hulu Kelang, Malaysia. Environmental Earth Sciences, 75, 445. https://doi.org/10.1007/s12665-016-5326-x

[81]

Saaty, T. L. (1980). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. New York; London: McGraw-Hill International Book Co.

[82]

Salvatici, T., Tofani, V., Rossi, G., D’Ambrosio, M., TacconiStefanelli, C., Masi, E. B., Rosi, A., Pazzi, V., Vannocci, P., Petrolo, M., Catani, F., Ratto, S., Stevenin, H., & Casagli, N. (2018). Application of a physically based model to forecast shallow landslides at a regional scale. Natural Hazards and Earth System Sciences, 18, 1919-1935. https://doi.org/10.5194/nhess-18-1919-2018

[83]

Satyanaga, A., & Rahardjo, H. (2022). Role of unsaturated soil properties in the development of slope susceptibility map. Proceedings of the Institution of Civil Engineers - Geotechnical Engineering, 175, 276-288. https://doi.org/10.1680/jgeen.20.00085

[84]

Scaioni, M., Longoni, L., Melillo, V., & Papini, M. (2014). Remote sensing for landslide investigations: An overview of recent achievements and perspectives. Remote Sensing, 6, 9600-9652. https://doi.org/10.3390/rs6109600

[85]

Schulz, W. H. (2007). Landslide susceptibility revealed by LIDAR imagery and historical records, Seattle, Washington. Engineering Geology, 89, 67-87. https://doi.org/10.1016/j.enggeo.2006.09.019

[86]

Shano, L., Raghuvanshi, T. K., & Meten, M. (2020). Landslide susceptibility evaluation and hazard zonation techniques -a review. Geoenvironmental Disasters, 7, 18. https://doi.org/10.1186/s40677-020-00152-0

[87]

Shou, K. J., & Chen, J. (2021). On the rainfall induced deep-seated and shallow landslide hazard in Taiwan. Engineering Geology, 288, Article 106156. https://doi.org/10.1016/j.enggeo.2021.106156

[88]

Shu, H., Hürlimann, M., Molowny-Horas, R., González, M., Pinyol, J., Abancó C., & Ma, J. (2019). Relation between land cover and landslide susceptibility in Val d’Aran, Pyrenees (Spain): Historical aspects, present situation and forward prediction. Science of The Total Environment, 693, Article 133557. https://doi.org/10.1016/j.scitotenv.2019.07.363

[89]

Simoni, S., Zanotti, F., Bertoldi, G., & Rigon, R. (2008). Modelling the probability of occurrence of shallow landslides and channelized debris flows using GEOtop-FS. Hydrological Processes, 22, 532-545. https://doi.org/10.1002/hyp.6886

[90]

Sorbino, G., Sica, C., & Cascini, L. (2010). Susceptibility analysis of shallow landslides source areas using physically based models. Natural Hazards, 53, 313-332. https://doi.org/10.1007/s11069-009-9431-y

[91]

Teza, G., Galgaro, A., Zaltron, N., & Genevois, R. (2007). Terrestrial laser scanner to detect landslide displacement fields: A new approach. International Journal of Remote Sensing, 28, 3425-3446. https://doi.org/10.1080/01431160601024234

[92]

Tsaparas, I., Rahardjo, H., Toll, D. G., & Leong, E. C. (2002). Controlling parameters for rainfall-induced landslides. Computers and Geotechnics, 29, 1-27. https://doi.org/10.1016/S0266-352X(01)00019-2

[93]

Tyagi, A., Tiwari, R. K., & James, N. (2023). Mapping the landslide susceptibility considering future land-use land-cover scenario. Landslides, 20, 65-76. https://doi.org/10.1007/s10346-022-01968-7

[94]

USDA, UD., 1986.Urban Hydrology for Small Watersheds. Technical Release. Technical Report.TR-55), Soil Conservation Service, Washington, DC. USA.

[95]

Van Asch, T., Buma, J., & Van Beek, L. (1999). A view on some hydrological triggering systems in landslides. Geomorphology, 30, 25-32. https://doi.org/10.1016/S0169-555X(99)00042-2

[96]

Vanacker, V., Vanderschaeghe, M., Govers, G., Willems, E., Poesen, J., Deckers, J., & De Bievre, B. (2003). Linking hydrological, infinite slope stability and land-use change models through GIS for assessing the impact of deforestation on slope stability in high Andean watersheds. Geomorphology, 52, 299-315. https://doi.org/10.1016/S0169-555X(02)00263-5

[97]

Varnes, D. J. (1978). Slope movement types and processes. Special report, 176, 11-33.

[98]

Vivaldi, V., Bordoni, M., Mineo, S., Crozi, M., Pappalardo, G., & Meisina, C. (2023). Airborne combined photogrammetry - Infrared thermography applied to landslide remote monitoring. Landslides, 20, 297-313. https://doi.org/10.1007/s10346-022-01970-z

[99]

Xiao, L., Zhang, Y., & Peng, G. (2018). Landslide susceptibility assessment using integrated deep learning algorithm along the China-Nepal highway. Sensors, 18, 4436. https://doi.org/10.3390/s18124436

[100]

Yesilnacar, E., & Süzen, M. L. (2006). A land-cover classification for landslide susceptibility mapping by using feature components. International Journal of Remote Sensing, 27, 253-275. https://doi.org/10.1080/0143116050030042

[101]

Yoshimatsu, H., & Abe, S. (2006). A review of landslide hazards in Japan and assessment of their susceptibility using an analytical hierarchic process (AHP) method. Landslides, 3, 149-158. https://doi.org/10.1007/s10346-005-0031-y

[102]

Zhai, Q., Rahardjo, H., & Satyanaga, A. (2016). Variability in unsaturated hydraulic properties of residual soil in Singapore. Engineering Geology, 209, 21-29. https://doi.org/10.1016/j.enggeo.2016.04.034

[103]

Zhang, C. B., Chen, L. H., Liu, Y. P., Ji, X. D., & Liu, X. P. (2010). Triaxial compression test of soil-root composites to evaluate influence of roots on soil shear strength. Ecological Engineering, 36, 19-26. https://doi.org/10.1016/j.ecoleng.2009.09.005

[104]

Zhang, J., Qiu, H., Tang, B., Yang, D., Liu, Y., Liu, Z., Ye, B., Zhou, W., & Zhu, Y. (2022). Accelerating effect of vegetation on the instability of rainfall-induced shallow landslides. Remote Sensing, 14, 5743. https://doi.org/10.3390/rs14225743

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