Linear Parameters Causing Landslides: A Case Study of Distance to the Road, Fault, Drainage

Seda Çellek

doi:10.34088/kojose.1117817

Research Article

BibTex

RIS

Cite

Linear Parameters Causing Landslides: A Case Study of Distance to the Road, Fault, Drainage

Year 2023, Volume: 6 Issue: 2, 94 - 113, 30.11.2023

Seda Çellek

https://doi.org/10.34088/kojose.1117817

Abstract

Choosing the right parameters for the study area is a compelling process. Parameters provide different results when applied to different areas, and some of these parameters can be evaluated generally, while others reflect the characteristics and properties of the areas. A comprehensive literature study was conducted for this purpose. By conducting this study, only the studies in which the distance to the road, drainage and fault were effective in the formation of landslides were evaluated. 64 landslide areas in Turkey were selected for samplings used in the study. Literature research and case studies were compared, and the effects of the distance from the road, fault and drainage on landslides were investigated. Landslide-prone areas were determined according to the classification ranges for the parameters. The classification ranges were selected according to the literature. This study, which is different from the examples in the literature, was carried out in the form of comprehensive literature research and a comparison of analyzes.

Keywords

Distance to Road, Distance to Fault, Distance to Drainage, Landslide Susceptibility, Parameter

Supporting Institution

Kırşehir Ahi Evran University BAP

Project Number

MMF.A4.18.017

Thanks

I thank Kırşehir Ahi Evran University for their support in funding the maps used in the study.

References

[1] Dağ, S., Akgün, A., Kaya, A., Alemdağ S., Bostancı H. T., 2020. Medium scale earthflow susceptibility modelling by remote sensing and geographical information systems based multivariate statistics approach: an example from Northeastern Turkey. Environ Earth Sci., 79, pp. 468.
[2] Kornejady A., Ownegh M., Bahremand A., 2017. Landslide susceptibility assessment using maximum entropy model with two different data sampling methods. Catena, 152, pp. 144–162.
[3] Chen W., Pourghasemi H. R., Kornejady A., Zhang N., 2017. Landslide spatial modeling: Introducing new ensembles of ANN, MaxEnt, and SVM machine learning techniques”. Geoderma, 305, pp. 314–327.
[4] Hong H., Naghibi S. A., Pourghasemi, H. R., Pradhan, B., 2016. GIS-based landslide spatial modeling in Ganzhou city, China. Arab J Geosci., 9, pp. 1-26.
[5] Jaafari A, Najafi A, Rezaeian J, Sattarian A., 2015. Modeling erosion and sediment delivery from unpaved roads in the north mountainous forest of Iran. International Journal on Geomathematics, 6, pp. 343
[6] Pancha S, Shrivastava A. Kr., 2022. Landslide hazard assessment using analytic hierarchy process (AHP): A case study of National Highway 5 in India. Ain Shams Engineering Journal, 13, pp. 101626.
[7] Xu C., Xu X. W., 2012. Spatial prediction models for seismic landslides based on support vector machine and varied kernel functions: A case study of the 14 April 2010 Yushu earthquake in China. Chin J Geophys, pp. 666–679.
[8] Rozos D., Bathrellos G. D., Skilodimou H. D., 2010. Landslide susceptibility mapping of the northeastern part of Achaia Prefecture using Analytical Hierarchical Process and GIS techniques. Paper presented at the Proceeding of the12th International Congress, Patras, Greece, XLIII May, 3, pp. 1637-1646.
[9] Kumtepe P., Nurlu Y, Cengiz T., Sütçü E., 2009. Bolu çevresinin heyelan duyarlılık analizi [Bildiri]. TMMOB Coğrafi Bilgi Sistemleri Kongresi, 02-06 Kasım, İzmir: TMMOB Yayınları, pp 1-8.
[10] Pourghasemi H. R., Rossi M., 2017. Landslide susceptibility modeling in a landslide prone area in Mazandarn Province, north of Iran: A comparison between GLM, GAM, MARS, and M-AHP methods. Theor Appl Climatol, 130, pp. 609–633.
[11] Tanoli J. I., Ningsheng C, Regmi A. D., Jun L., 2017. Spatial distribution analysis and susceptibility mapping of landslides triggered before and after Mw7.8 Gorkha earthquake along Upper Bhote Koshi, Nepal. Arabian Journal of Geosciences, 10, pp. 13.
[12] Zhang J. Q., Liu R. K., Deng W., Khanal N. R., Gurung D. R., Sri Ramachandra Murthy M., Wahid S. 2016. Characteristics of landslide in Koshi River Basin, Central Himalaya. Journal of Mountain Science, pp. 1711–1722.
[13] Kamp U., Growley B. J., Khattak G. A., Owen L. A. 2008. GIS-based landslide susceptibility mapping for the 2005 Kashmir earthquake region. Geomorphology, 101, pp. 631–642.
[14] Blesius L., Weirich F. 2010. Shallow landslide susceptibility mapping using stereo air photos and thematic maps. Cartography and Geographic Information Science, 37.
[15] Van Westen C. J., Rengers N., Soeters R., 2003. Use of geomorphological information in indirect landslide susceptibility assessment. Natural Hazards, 30, pp. 399-419.
[16] Poudyal C. P., Chang C., Oh H. J., Lee S. 2010. Landslide susceptibility maps comparing frequency ratio and artificial neural networks: A case study from the Nepal Himalaya. Environmental Earth Sciences, 61 pp. 1049-1064.
[17] Preuth T., Glade T., Demoulin A., 2010. Stability analysis of a human-influenced landslide in eastern Belgium. Geomorphology, 120, pp. 38-47.
[18] Lee Y. F., Chi Y. Y., 2011. Rainfall-induced landslide risk at Lushan, Taiwan. Engineering Geology, 123, pp. 113-121.
[19] Bai S. B., Wang J., Thiebes B., Cheng C., Chang Z. Y. 2014. Susceptibility assessments of the Wenchuan earthquake-triggered landslides in Longnan using logistic regression. Environmental Earth Sciences, pp. 731–743.
[20] Özdemir A., 2009. Landslide susceptibility mapping of vicinity of Yaka Landslide [Gelendost, Turkey] using conditional probability approach in GIS. Environ Geol., 57, pp. 1675–1686
[21] Barredo J. I., Hervas J., Lomoschitz A., Benavides A., Van W. C. 2000. Landslide hazard assessment using GIS and multi-criteria evaluation techniques in the Tirajana Basin, Gran Canaria Island. 5th EC GIS Workshop.
[22] Kavzoğlu T., Şahin E. K., Çölkesen İ. 2014. Factor Selection based on Chi-Square Test in Landslide Sensitivity Analysis. V. Remote Sensing and Geographical Information Systems Symposium [UZAL-GIS], 14-17 Oct., İstanbul.
[23] Saadatkhahi N., Kassimi A., Lee M. L., 2014. Qualitative and quantitative landslide susceptibility assessments in Hulu Kelang area, Malaysia. EJGE, 19, pp. 545-563.
[24] Dragicevi C. S., Lai, T., Balram S., 2015. GIS-based multicriteria evaluation with multiscale analysis to characterize urban landslide susceptibility in data-scarce environment. Habitat International, pp.114–125.
[25] Aghdam I. N., Varzandeh M. H. M., Pradhan B., 2016. Landslide susceptibility mapping using an Ensemble Statistical İndex [Wi] and adaptive Neuro-Fuzzy İnference System [ANFIS] Model at Alborz Mountains [Iran]. Environ Earth Sci., 75, pp. 1-20.
[26] Stanley T., Kirschbaum D. K., 2017. A heuristic approach to global landslide susceptibility mapping. Natural Hazards, 87, pp. 145, 164.
[27] Yılmaz Ç., Topal T., Süzen M. L., 2012. GIS-based landslide susceptibility mapping using bivariate statistical analysis in Devrek [Zonguldak-Turkey]. Environmental Earth Sciences, 65, pp. 2161-2178,
[28] Alemdağ S., Kaya A., Karadağ, M., Gurocak, Z., Bulut, F. (2015). Utilization of the limit equilibrium and finite element methods for the stability analysis of the slope debris An example of the Kalebasi District NE Turkey. Journal of African Earth Sciences, 106, pp. 134-146.
[29] Akıncı H., Kılıçoğlu C., 2015. Production of landslide susceptibility map of Atakum [Samsun] district. MÜHJEO’2015: National Engineering Geology Symposium, 3-5 September, Trabzon.
[30] Kaya A., Alemdağ S., Dağ S., Gürocak Z. 2016. Stability assessment of high steep cut slope debris on a landslide Gumushane NE Turkey. Bulletin of Engineering Geology and the Environment, 75, pp. 89-99.
[31] Meinhardt M., Fink M., Tünschel H., 2015. Landslide susceptibility analysis in central Vietnam based on an incomplete landslide inventory: Comparison of a new method to calculate weighting factors by means of bivariate statistics. Geomorphology, 234, pp. 80-97.
[32] Tazik E., Jahantab Z., Bakhtiari M., Rezae A., Alavipanah S. K., 2014. Landslide susceptibility mapping by combining the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process in Dozain Basin. International Conference on Geospatial Information Research [GI Research]. pp 15-17 November, Tehran, Iran.
[33] Pourghasemi H. R., Pradhan B., Gökçeoğlu C. 2012. Remote sensing data derived parameters and its use in landslide susceptibility assessment using Shannon’s entropy and GIS. AEROTECH IV, Appl Mech Mater, 225, pp. 486–491.
[34] Mashari S., Solaimani K., Omidvar E., 2012. Landslide susceptibility mapping using multiple regression and GIS tools in Tajan Basin, north of Iran. Environment and Natural Resources Research, 2, pp. 43-51.
[35] Mohammady M., Pourghasem H. R., Pradhan B. 2012. Landslide susceptibility mapping at Golestan Province Iran: A comparison between frequency ratio, Dempster-Shafer, andweights of evidence models. J Asian Earth Sci., 61, 221.
[36] Pourghasemi H. R., Moradi H. R., Aghda S. F., 2013. Landslide susceptibility mapping by binary logistic regression, analytical hierarchy process, and statistical index models and assessment of their performances. Nat Hazards, 69, pp. 749–779.
[37] Feizizadeh B., Blaschke T., Nazmfar H., 2014. GIS-based ordered weighted averaging and Dempster-Shafer methods for landslide susceptibility mapping in the Urmia Lake Basin, Iran. International Journal of Digital Earth, 7, pp. 688-708.
[38] Jebur M. N., Pradhan B., Tehrany M. S. 2015. Manifestation of LiDAR derived parameters in spatial prediction of landslides using a novel ensemble evidential belief functions and support vector machine models in GIS. IEEE J Sel Top Appl Earth Obs Remote Sens., 8, pp. 674-689.
[39] Pawluszek K., Borkowski A., 2017. Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland. Natural Hazards, 86, pp. 919–952.
[40] Dehnavi A., Aghdam I. N., Pradhan B., Varzandeh M. H. M., 2015. A new hybrid model using step-wise weight assessment ratio analysis [SWARA] technique and adaptive neuro-fuzzy ınference system [ANFIS] for regional landslide hazard assessment in Iran. Catena, 135, pp. 122–148.
[41] Chen W., Wang J., Xie X., Hong H., Trung Van N., Bui D. T., Wang G., Li X., 2016. Spatial prediction of landslide susceptibility using integrated frequency ratio with entropy and support vector machines by different kernel functions. Environ, Earth Sci., 75, pp. 1344.
[42] Sangchini E. K., Emami S. N., Tahmasebipour N., Pourghasemi H. R., Naghibi S. A., Arami S. A., Pradhan B., 2016. Assessment and comparison of combined bivariate and AHP models with logistic regression for landslide susceptibility mapping in the Chaharmahal-e-Bakhtiari Province, Iran. Arabian Journal of Geosciences, 9, pp. 201.
[43] Wang J.-J., Liang Y., Zhang H.-P., Wu Y., Lin X., 2014. A loess landslide induced by excavation and rainfall. Landslides, 11, pp. 141-152.
[44] Gökçe O., Özden Ş., Demir A., 2008. Spatial and Statistical Distribution of Disasters in Turkey Inventory of Disaster Information. Ministr of Public Works and Settlement General Directorate of Disaster Affairs, Department of Disaster Survey and Damage Assessment, Ankara [In Turkish].
[45] Timilsina M., Bhandary N. P., Dahal R. K., Yatabe R., 2014. Distribution probability of large-scale landslides in central Nepal. 226, pp. 236-248.
[46] Avcı V., Günek H., 2014. The distribution of active landslides in Karlıova Basin and surrounding [Bingöl] according to lithology, elevation, slope, inspection and NDVI Parts. International Journal of Social Science, pp. 445-464.
[47] Özşahin E., 2015. Landslide susceptibility analysis by geographical information systems: the case of Ganos Mount [Tekirdağ] [in Turkish]. Electronic Journal of Map Technologies, 7, pp. 47-63.
[48] Avcı V., 2016a. Analysis of landslide succeptibility of Manav Stream Basin [Bingöl], The Journal of International Social Research., 9, pp. 42-9.
[49] Laldintluanga Er H., Lalbiakmawia F., Lalbiaknungi Er R., 2016. Landslide hazard zonation along state highway between Aizawl City and Aibawk Town, Mizoram, India Using Geospatial Techniques. International Journal of Engineering Sciences and Research Technology, 5.
[50] Correa-Muñoz N. A., Higidio-Castro J. F., 2017. Determination of landslide susceptibility in linear infrastructure. Case: Aqueduct network in Palacé, Popayan [Colombia]. Ingeniería e Invest, 37, pp. 17–24.
[51] Pham B. T., Bui D. T., Prakash I., Dholakia M. B., 2017. Hybrid integration of multilayer perceptron neural networks and machine learning ensembles for landslide susceptibility assessment at Himalayan area [India] using GIS. Catena, 149, pp. 52–63.
[52] Sarkar S., Kanungo D. P., 2017. GIS Application in Landslide Susceptibility Mapping of Indian Himalayas, GIS. Landslide, pp. 211-219.
[53] Çevik E., Topal T., 2003. GIS-based landslide susceptibility mapping for a problematic segment of the natural gas pipeline, Hendek [Turkey]. Environmental Geology, pp. 949-962.
[54] Moradi S., Rezaei M. A. 2014. 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. J Geope., 4, pp. 45-61.
[55] Meng X., Pei X., Liu Q., Zhang X., Hu Y., 2016. GIS-based environmental assessment from three aspects of geology, ecology and society along the road from Dujiangyan to Wenchuan. Mt. Res., 34, pp. 110–120.
[56] Komac M., 2006. A landslide susceptibility model using the analytical hierarchy process method and multivariate statistics in perialpine Slovenia. Geomorphology, 74, pp. 17-28.
[57] Achour Y., Boumezbeur A., Hadji R., Chouabbi A., Cavaleiro V., Bendaoud E. A., 2017. Landslide susceptibility mapping using analytic hierarchy process and information value methods along a highway road section in Constantine, Algeria. Arabian J. Geosci., 10 pp. 194.
[58] Bourenane H., Bouhadad Y., Guettouche M. S., Braham M., 2015. “GIS-based landslide susceptibility zonation using bivariate statistical and expert approaches in the city of Constantine [Northeast Algeria]”. Bulletin of Engineering Geology and the Environment, 74, pp. 337-355.
[59] Dou J., Yamagishi H., Xu Y., Zhu Z., Yunus A. P., 2017. Characteristics of the torrential rainfall-ınduced shallow landslides by typhoon bilis, in July 2006, using remote sensing and GIS”. In book: GIS Landslide Publisher: Springer Japan.
[60] Avcı V., 2016b. Analysis of landslide succeptibility of Manav Stream Basin [Bingöl]. The Journal of International Social Research, 9, pp. 42-9.
[61] Avcı V., 2016c. Landslide susceptibility analysis of Esence Stream Basin [Bingöl] by weight- of- evidence method. International Journal of Social Science, 44, pp. 287-310.
[62] Simon N. de Róiste M., Crozier M., Rafek A. G., 2017. Representing Landslides as Polygon [Areal] or Points? How Different Data Types Influence the Accuracy of Landslide Susceptibility Maps. Sains Malaysiana, pp. 27-34.
[63] Conforti M., Pascale S., Robustelli G., Sdao F., 2014. Evaluation of prediction capability of the artificial neural networks for mapping landslide susceptibility in the Turbolo River catchment [northern Calabria Italy]. Catena, pp. 236-250.
[64] Wang H. Q., He J., Liu Y., Sun S., 2016. Application of analytic hierarchy process model for landslide susceptibility mapping in the Gangu County, Gansu Province, China. Environ Earth Sci., 75, pp. 422.
[65] Çellek S., Bulut F., Ersoy H., 2015. Utilization and Application of AHP Method in Landslide Susceptibility Mapping Production [Sinop and its Surroundings]. Journal of Geological Engineering, 39 pp. 59-90.
[66] Bostanci H. T., Alemdağ, S., Gürocak Z., Gökçeoğlu 2018. Combination of discontinuity characteristics and GIS for regional assessment of natural rock slopes in a mountainous area (NE Turkey). Catena, 165, pp. 487-502.
[67] Mathew J., Jha V. K., Rawat G. S. 2007. Weights of evidence modelling for landslide hazard zonation mapping in part of Bhagirathi valley, Uttarakhand. Current science, 92, pp. 628-638.
[68] Özşahin E., 2014. The mass movement vulnerability evaluation of Antakya [Hatay] city through Geographic Information Systems [GIS] and Analytic Hierarchy Process [AHP]. Ege Coğrafya Dergisi, 23, pp. 19-35.
[69] Korkmaz H., 2006. Antakya’da zemin özellikleri ve deprem etkisi arasındaki ilişki. Ankara Üniversitesi, Türkiye Coğrafya Araştırma ve Uygulama Merkezi, Coğrafi Bilimler Dergisi, 4, pp. 47- 63.
[70] Regmi N. R., Giardino J. R., McDonald E. V., Vitek J.D., 2014. A comparison of logistic regression-based models of susceptibility to landslides in western Colorado, USA. Landslides, 11, pp. 247-262.
[71] Ahmed M.F., Androgersj D., 2014. Creating reliable, first-approximation landslide inventory maps using ASTERDEM data and geomorphic indicators, an example from theupper Indus River in northern Pakistan. Environmental Engi-neering Geoscience, 20, pp. 67–83.
[72] Kayastha P., Bijukchhen S.M., Dhital M.R., De Smedt F., 2013. GIS based landslide susceptibility mapping using a fuzzy logic approach: A case study from Ghurmi-Dhad Khola area, Eastern Nepal. Journal of the Geological Society of India, 82, pp. 249–261.
[73] Zhang M.S., Dong Y., Sun P.P., 2012. Impact of reservoir impoundment-caused groundwater level changes on regional slope stability: A case study in the Loess Plateau of Western China. Environ Earth Sci., pp. 1715–1725.
[74] Pareek N., Pal S., Sharma M.L., Arora M., K., 2013. Study of effect of seismic displacements on landslide susceptibility zonation [LSZ] in Garhwal Himalayan region of India using GIS and remote sensing techniques. Computers & Geosciences, 61, pp. 50-63.
[75] Wu Y., Li W., Liu P., Bai H., Wang Q., He J., Liu Y., Sun S., 2016. Application of analytic hierarchy process model for landslide susceptibility mapping in the Gangu County, Gansu Province, China. Environ Earth Sci, 75, pp. 422.
[76] Wan S., 2013. Entropy-based particle swarm optimization with clustering analysis on landslide susceptibility mapping. Environmental Earth Sciences, 68, pp. 1349-1366.
[77] Abedini M., Ghasemyan B., Mogaddam M.H. 2017. Landslide susceptibility mapping in Bijar City, Kurdistan Province, Iran: A comparative study by logistic regression and AHP models. Environ Earth Sci., 76, pp. 308.
[78] Acharya S., Pathak D., 2017. Landslide hazard assessment between Besi Sahar and Tal area in Marsyangdi River Basin, West Nepal”. Int. Journal of Advances in Remote Sensing and GIS, 5, pp. 29-38.
[79] Raja N.B., Çiçek I., Türkoğlu N., Aydin O., Kawasaki A., 2017. Landslide susceptibility mapping of the Sera River Basin using logistic regression model. Natural Hazards, 85, pp. 1323-1346.
[80] Çan T., Duman T.Y., Olgun Ş., Çörekçioğlu Ş., Gülmez-Karakaya F., Elmacı H., Hamzaçebi S., Emre Ö., 2013. Türkiye Heyelan Veri Tabanı. TMMOB Coğrafi Bilgi Sistemleri Kongresi, 11-13 Kasım, Ankara.
[81] Dağ S., Bulut F., 2012. Preparation of GIS-based landslide susceptibility maps: Çayeli [Rize, NE Türkey]. Journal of Geological Engineering, pp. 35-62.
[82] Gurocak, Z., Alemdag, S., Bostanci, H.T. and Gokceoglu, C. (2017). Discontinuity controlled slope failure zoning for a granitoid complex: A fuzzy approach. Rock Mechanics and Engineering, 5, pp. 1–25.
[83] Hasekioğulları G.D., 2011. Assessment of parameter effects in producing landslide susceptibility maps. Master Thesis [in Turkish], Hacettepe University, Turkey.
[84] Süzen M.L., Kaya B.Ş., 2011. Evaluation of environmental parameters in logistic regression models for landslide susceptibility mapping. Int J Digit Earth, 5, pp. 1–18.
[85] Harr R.D., Nichols R., 1993. A Stabilizing Forest Roads to Help Restore Fish Habitats: A Northwest Washington Example. Environmental Science, 18.
[86] Fransen P.J., Phillips B., Chris J., Fahey Barry D., 200. Forest road erosion in New Zealand: overview. Earth Surface Processes and Landforms, 1.
[87] Ekinci D., 2014. Zonguldak-Hisarönü Arasındaki Karadeniz Akaçlama Havzasının Kütle Hareketleri Duyarlılık Analizi. Titiz Yayınları, İstanbul.
[88] Kouli M., Loupasakis C., Soupios P., Rozos D., Vallianatos F., 2014. Landslide susceptibility mapping by comparing the WLC and WofE mutli-criteria methods in the West Crete Island, Greece. Environ Earth Sci., 72, pp. 1-25.
[89] Che V.B., Kervyn M., Suh C.E., Fontijn K., Ernst G.G.J., del Marmol M.A., Trefois P., Jacobs P., 2012. Landslide susceptibility assessment in Limbe [SW Cameroon]: A field calibrated seed cell and information value method. Catena, 92, 83-98.
[90] Guri P.K., Champati ray P.K., Patel R.C., 2015. Spatial prediction of landslide susceptibility in parts of Garhwal Himalaya, India, using the weight of evidence modelling. Environmental Monitoring and Assessment, 187, pp. 324.
[91] Youssef A.M., Al-Kathery M., Pradhan B., 2015. Landslide susceptibility mapping at Al-Hasher Area, Jizan [Saudi Arabia] using GIS-based frequency ratio and index of entropy models. Geosci J., 19, pp. 113–134.
[92] Devkota K.C., Regmi A.D., Pourghasemi H.R., Yoshida K., Pradhan B., Ryu I.C., 2013. Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling–Narayanghat road section in Nepal Himalaya. Nat. Hazards., 65, pp. 135-165.
[93] Tsangaratos P., Benardos A., 2014. Estimating landslide susceptibility through A artificial neural network classifier. Natural Hazards, 74, pp. 3.
[94] Liu C-N., Wu C-C. 2007. Mapping susceptibility of rainfall-triggered shallow landslides using a probabilistic approach. Environmental Geology, 55, pp. 907-915.
[95] Çellek S., 2013. Landslide susceptibility analysis of Sinop-Gerze region. Doctora Thesis [in Turkish], KTU, Turkey.
[96] Tangestani M.H., 2004. Landslide susceptibility mapping using the fuzzy gamma approach in a GIS, Kakan catchment area, southwest Iran. Australian Journal of Earth Sciences, 51, pp. 439–450.
[97] Dahal R.K., 2014. Regional-scale landslide activity and landslide susceptibility zonation in the Nepal Himalaya. Environmental Earth Sciences, 71, pp. 5145-5164.
[98] Ataol M., Yeşilyurt S., 2014. Identification of landslide risk zones along the Çankırı-Ankara [between Akyurt and Çankırı] state road. Journal of Geography, 29, pp. 51-69.
[99] Sidle R.C., 1985. Influence of Forest Harvesting Activities on Debris Avalanches and Flows. Debris-flow Hazards and Related Phenomena, book.
[100] Piehl B.T., Beschta R.L. Pyles M.R., 1988 .Ditch-relief culverts and low-volume forest roads in the Oregon Coast Range. Northwest Sci., 62, pp. 91-98.
[101] Demir G., 2011. GIS based landslide susceptibility analysis of an area [Niksar-Suşehri] on North Anatolian fault zone. Karadeniz Teknik Üniversitesi, Doctorate Thesis, Trabzon, Turkey.
[102] Alexakis D.D., Agapiou A., Tzouvaras M., Themistocleous K., Neocleous K., Michaelides S., Hadjimitsis D.G., 2014. Integrated use of GIS and remote sensing for monitoring landslides in transportation pavements: the case study of Paphos area in Cyprus. Natural Hazards, 72, pp. 119-141.
[103] Alemdağ S., Akgun A., Kaya A., Candan G., 2014. A large and rapid planar failure causes mechanism and consequences Mordut Gumushane Turkey. Arabian Journal of Geosciences, 7, pp. 1205-1221.
[104] Mittal S.K., Singh M., Kapur P., Sharma B.K., Shamshi M.A., 2008. Design and development of instrument network for landslide monitoring, an issue an early warning. Journal of Scientific &Industrial research, 67, pp. 361-365.
[105] 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, pp. 15-31.
[106] Pradhan B., 2010a. Landslide susceptibility mapping of a catchment area using frequency ratio, fuzzy logic and multivariate logistic regression approaches. J Ind Soc Rem Sens, 38, pp. 301-320.
[107] Pradhan B., 2010b. Remote sensing and GIS based landslide hazard analysis and cross validation using multivariate logistic regression model on three test areas in Malaysia. Advncs Space Res, 45, pp. 1244-1256.
[108] Demir G., Aytekin M., Akgün A., İkizler S.B., Tatar O., 2013. A comparison of landslide susceptibility mapping of the eastern part of the North Anatolian Fault Zone [Turkey] by likelihood-frequency ratio and analytic hierarchy process methods. Natural Hazards, 65, pp. 1481-1506.
[109] Jacobs L., Dewitte O., Poesen J., Maes J., Mertens K., Sekajugo J., Kervyn M., 2017. Landslide characteristics and spatial distribution in the Rwenzori Mountains, Uganda. Journal of African Earth Sciences, 134, pp. 917-930.
[110] Zeng B., Xiang W., Rohn J., Ehret D., Chen X. 2017. Assessment of shallow landslide susceptibility using an artificial neural network in Enshi region, China. Nat. Hazards Earth Syst. Sci., Discuss, 176.
[111] Dahal R.K., Hasegawa S., Nonomura A., Yamanaka M., Dhakal S., Paudyal P., 2008. Predictive modeling of rainfall-induced landslide hazard in the Lesser Himalaya of Nepal based on weights-of-evidence. Geomorphology, 102, pp. 496–510.
[112] Özşahin E., Kaymaz Ç.K., 2013. Landslide susceptibility analysis of Camili [Macahel] Biosphere Reserve Area [Artvin, NE Turkey]. Turkish Studies - International Periodical For The Languages, Literature and History of Turkish or Turkic, Turkey, 8, pp. 471-493.
[113] Petley D.N., Hearn G.J., Hart A., Rosser N.J., Dunning S.A., Oven K., Mitchell W.A., 2007. Trends in landslide occurrence in Nepal. Natural Hazards, 43, 23-44.
[114] Kuşku İ, Dalgıç S., 2020. Modeling of support system for preventing retrogressive slide of Ambarlı landslide in Avcılar district, Istanbul. Pamukkale Univ Muh Bilim Derg, 26, pp. 1401-1407.
[115] Mirsanei R., Mahdifar M., 2006. Methods and optimal criteria for preparing Landslide hazard zonation maps, Center for Natural Disasters, Iran. Conference Paper.
[116] Kritikos T., Davies T., 2014. Assessment of rainfall‐generated shallow landslide/debris‐flow susceptibility and runout using a GIS‐based approach: Application to western Southern Alps of New Zealand. Landslides, 12, pp. 1051–1075.
[117] Saponaro A., Pilz M., Wieland M., Bindi D., Moldobekov B., Parolai B., 2015. Landslide susceptibility analysis in data-scarce regions: The case of Kyrgyzstan. Bulletin of Engineering Geology and the Environment, 74, pp. 1117–1136.
[118] Ramakrishnan D., Singh T.N., Verma A.K., Gulati A., Tiwari K.C., 2013. Soft computing and GIS for landslide susceptibility assessment in Tawaghat area, Kumaon Himalaya, India. Natural Hazards, 65, pp. 315–330.
[119] Chen C.W., Saito H., Oguchi T., 2015. Rainfall intensity–duration conditions for mass movements in Taiwan, Progress in. Earth and Planetary Science, 2, pp. 1–13.
[120] Li C., Xu W., Wu J., Gao M., 2016. Using new models to assess probabilistic seismic hazard of the North–South Seismic Zone in China. Nat Hazards, 82 pp. 659–681.
[121] Hessami K., Jamali F., 2006. Explanatory notes to the map of major active faults of Iran. JSeismol Earthq Eng., 8, pp. 1–11.
[122] Ruff M., Czurda K., 2008. Landslide susceptibility analysis with a heuristic approach in the Eastern Alps (Vorarlberg, Austria). Geomorphology, 94, pp. 314-324.
[123] Ercanoğlu M., 2005. Landslide susceptibility assessment of SE Bartin (West Black Sea region, Turkey) by artificial neural networks. Natural Hazards Earth System Science, pp. 979–992.
[124] Roodposhti M.S., Rahimi S., Beglou M.J., 2014. PROMETHEE II and fuzzy AHP: an enhanced GIS-based landslide susceptibility mapping. Nat. Hazards, 73, pp. 77–95.
[125] Sadr M.P., Abbas M., Bashir S.S., 2014. Landslide susceptibility mapping of Komroud sub-basin using fuzzy logic approach. Geodyn Res Int Bull., 2, pp. 14–27.
[126] Ilia, Tsangaratos P., 2016. Applying weight of evidence method and sensitivity analysis to produce a landslide susceptibility map. Landslides, pp. 379–397.
[127] Kayastha P., Dhital M.R. De Smedt F., 2012. Landslide susceptibility mapping using the weight of evidence method in the Tinau watershed, Nepal. Natural Hazards, 63.
[128] Rajakumar P., Sanjeevi S., Jayaseelan S., Isakkipandian G., Edwin M., Balaji P., Ehanthalingam G., 2007. Landslide susceptibility mapping in a hilly terrain using remote sensing and GIS. Journal of the Indian Society of Remote Sensing, 35, pp. 31–42.
[129] Daneshvar M.R.M., 2014. Landslide susceptibility zonation using analytical hierarchy process and GIS for the Bojnurd region, northeast of Iran. Landslides, 11, pp. 1079–1091.
[130] Çoruk Ö, Kavak A., 2020. Causes of Bursa Yıldırım district Mollaarap landslide and its improvement studiesl. Pamukkale Univ Muh Bilim Dergisi, 26, pp. 1408–1412.
[131] Taşoğlu İ.K., Keskin Çıtıroğlu H., Mekik Ç., 2016. GIS-based landslide susceptibility assessment: A case study in Kelemen Valley (Yenice—Karabuk, NW Turkey). Environmental Earth Sciences, 75, pp. 1295.
[132] Ercanoğlu M., Gökceoğlu C., Van Asch Th. W.J., 2004. Landslide susceptibility zoning north of Yenice [NW Turkey] by multivariate statistical techniques. Natural Hazards, 32, pp. 1–23.
[133] Yusof N.M., Pradhan B., 2014. Landslide susceptibility mapping along PLUS expressways in Malaysia using probabilistic based model in GIS. 7th IGRSM International Remote Sensing & GIS Conference and Exhibition.
[134] Guo D., Hamada M., He C., Wang Y., Zou Y., 2014. An empirical model for landslide travel distance prediction in Wenchuan earthquake area. Landslides, 11, pp. 281-291.
[135] Dai F.C., Lee C.F., 2001. Terrain-based mapping of landslide susceptibility using a geographical information system: A case study. Can. Geotech. J., pp. 911–923.
[136] Mossa S., Capolongo D., Pennetta L., Wasowski J., 2005. A GIS-based assessment of landsliding in the Daunia Apennines, Southern Italy, in Proceedings of the conference Mass movementhazard in various environments. Polish Geological Institute special papers, 20, pp. 86–91.
[137] Komac M., 2012. Regional landslide susceptibility model using the Monte Carlo approach - The case of Slovenia. Geological Quarterly, 56, pp. 41-54.
[138] Ekinci D., 2005. Karadeniz Ereğlisi'nin Zemin Hareketleri Duyarlılık Sahalarının Sınıflandırılması ve Yüksek Riskli Yerleşmelerin Zemin Stabilite Analizi. İstanbul Üniversitesi Edebiyat Fakültesi Coğrafya Bölümü Coğrafya Dergisi, 13, pp. 121-137.
[139] Rozos D., Bathrellos G.D., Skilodimou H.D., 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. Environ Earth Sci., pp. 49–63.
[140] Sujatha R., Rajamanickam G.V., Pichaimani K., 2012. Landslide susceptibility analysis using Probabilistic Certainty Factor Approach: A case study on Tevankarai stream watershed, India. Journal of Earth System Science, 121, pp. 5.
[141] Sujatha R., Rajamanickam G.V., Pichaimani K., 2012. Landslide susceptibility analysis using Probabilistic Certainty Factor Approach: A case study on Tevankarai stream watershed, India., Journal of Earth System Science, 121, pp. 5.
[142] Poudel D.D., Midmore D.J., West L.T., 1999. Erosion and productivity of vegetable systems on sloping volcanic ash-derived Philippine soils. Soil Sci.Soc. Am. J., 63, pp. 1366–1376.
[143] Yalçın A., Reis S., Aydınoğlu A.C., Yomralıoğlu T.A., 2011. GIS-based comparative study of frequency ratio, analytical hierarchy process, bivariate statistics and logistics regression methods for landslide susceptibility mapping in Trabzon, NE Turkey. Catena, 85, pp. 274-287.
[144] Shit P.K. Bhunia G.S., Maiti R., 2016. Potential landslide susceptibility mapping using weighted overlay model [WOM], Modeling. Earth Systems and Environment, 2, pp. 21.
[145] Korup O., Strom A.L., Weidinger J.T., 2006. Fluvial response to large rock-slope failures-examples from the Himalayas, the Tien Shan, and the New Zealand Southern Alps. Geomorphology, 78, pp. 3–21.
[146] Tang C., Zhu J., Qi X., Ding J., 2011. Landslides induced by the Wenchuan earthquake and the subsequent strong rainfall event: A case study in the Beichuan area of China. Eng Geol., 122, pp. 22–33.
[147] Gandhi M.S., 2016. Distribution of Heavy Minerals and its Provenance Studies of Mahabalipuram Beach, South East Coast of Chennai, Tamil Nadu. Acta Pharmaceutica Sciencia, 7, pp. 1-28.
[148] Matebie M., Netra P.B.R.Y., 2015. Effect of landslide factor combinations on the prediction accuracy of landslide susceptibility maps in the Blue Nile Gorge of Central Ethiopia. Geoenvironmental Disasters, 2.
[149] Saha A.K., Gupt R.P., Arora M.K., 2002. GIS-based landslide hazard zonation in the Bhagirathi [Ganga] valley, Himalaya. Int J Remote Sens, 23, pp. 357–369.
[150] Pham B.T., Tien Bui D., Indra P., Dholakia M., 2015. Landslide susceptibility assessment at a part of Uttarakhand Himalaya, India using GIS-based statistical approach of frequency ratio method. Int J Eng Res Technol., 4, pp. 338–344.
[151] Larsen M.C., Parks J.E., 1997. How wide is a road? The association of roads and mass-wasting in a forested montane environment. Earth Surface Processes and Landforms, 22, pp. 835-848.
[152] Champati ray P.K., 2004. GIS based landslide modelling, In: Nagarajan R [ed], Landslide disaster: Assessment and monitoring. Anmol Publications, New Delhi, pp. 81–96.
[153] Bhatt B., Awasthi K., Heyojoo B., Silwal T., Kafle G., 2013. Using geographic ınformation system and analytical hierarchy process in landslide hazard zonation. Applied Ecology and Environmental Sciences, 1, pp. 14-22.
[154] Ahmed B., Rubel Y.A., 2013. Understanding the issues involved in urban landslide vulnerability in Chittagong metropolitan area, Bangladesh. Association of American Geographers (AAG), Washington DC, Book Section. DOI: 10.13140/RG.2.1.4624.8003/1.
[155] Shaban A., Khawlie M., Bou Kheir R., Abdallah C., 2001. Assessment of road instability along a typicalmountainous road using GIS and aerial photos, Lebanon, Eastern Mediterranean. Bulletin of Engineering Geology and Environment, 60, pp. 93-101.
[156] Vahidnia M.H., Ale Sheykh A.A., Ali Mohammadi A., Hosseinali F., 2009. Landslide hazard zonation using quantitative methods in GIS. International Journal of Civil Engineering, 7, pp. 176-189.
[157] Saha A.K., Gupta R.P., Sarkar I., Arora M.K., Csaplovics E., 2005. An approach for GIS-based statistical landslide susceptibility zonation—with a case study in the Himalayas. Landslides, 2, pp. 61–69.
[158] Pareek N., Sharma M.L., Arora M.K., 2010. Impact of seismic factors on landslide susceptibility zonation: a case study in part of Indian Himalayas. Landslides, 7, pp. 191–201.
[159] Khanlari G.R., Abdi Y., Babazadeh R., 2014. Landslide hazards zonation using GIS in Khoramabad, Iran. Journal of Geotechnical Geology, Winter, 9, pp. 343-352.
[160] Akıncı H., Özalp-Yavuz A., Özalp M., Temuçin-Kılıçer S., Kılıçoğlu C., Everan E., 2014. Production of landslide susceptibility maps using bayesian probability theorem. 5. Remote Sensing-GIS Symposium [Uzal-GIS], 14-17 Oct., İstanbul.
[161] Uromeihy A., Mahdavifar M.R., 2000. Landslide hazard zonation of the Khorshrostam area, Iran. Bulletin of Engineering Geology and the Environment, 58, pp. 207–213.
[162] Akgün A., Türk N., 2010. Landslide susceptibility mapping for Ayvalik [Western Turkey] and its vicinity by multicriteria decision analysis. Environmental Earth Sciences, 61, pp. 595–611.
[163] He S., Li D., Wu Luo Y., 2011. Study on the rainfall and aftershock threshold for debris flow of post-earthquak. J. Mountain Sci., pp. 750–756.
[164] Erener A., Lacasse S., 2007. Landslide susceptibility mapping using GIS. TMMOB Chamber of Survey and Cadastre Engineers National Geographic Information Systems Congress, KTU, Turkey.
[165] Yalçın A., Bulut F., 2007. Landslide susceptibility mapping using GIS and digital photogrametric techniques; a case study from Ardeşen [NETurkey]. Natural Hazard, 41, pp. 201-226.
[166] Yalçın A., 2008. GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen [Turkey]: Comparisons of results and confirmations. Catena, 72 (1) 1, 12.
[167] Chen S.C., Chang C.C., Chan H.C., Huang L.M., Lin L.L., 2013. Modeling typhoon event-induced landslides using GIS-based logistic regression: A case study of Alishan Forestry Railway, Taiwan. Math. Prob. Eng. URL: https://www.hindawi.com/journals/mpe/2013/72830.