Turkish Contributions to the World Landslide Literature on the 100th Anniversary of the Republic of Türkiye

Öz

The main purpose of the present study is to celebrate the 100th anniversary of the Republic of Türkiye by investigating the contribution of researchers from Türkiye to the world literature on landslides. Landslides are a significant and common natural hazard in terms of both loss of life and property. Within the scope of the analysis, Web of Science records with the keywords”landslide*” and the address “Turkey or Türkiye or Turkiye” were used. Among the query results obtained, only articles and reviews were considered. As a result, 721 records were obtained and analyzed. The earliest publication addressing Türkiye was dated 1989. Although international publications on landslides in Türkiye started late, many articles addressing Türkiye have since been published in important journals such as Engineering Geology, Landslides, Environmental Earth Sciences, Computers & Geosciences, and Natural Hazard. While a limited number of articles were published in the 1990s, there was a significant increase in the number of articles in the 2000s, at one point reaching 66 in 2020. These articles were cited on average 33.73 times, a very high number, indicating the success of researchers from Türkiye. Indeed, the total citations of the 10 most cited articles range from 630-339, which is extraordinarily high. On the other hand, 12.6% of articles from Türkiye were not cited at all. As a result, considering both the quality and quantity of the articles and the number of citations, it is understood that landslide-related publications from Türkiye have had a significant impact on the international literature.

Anahtar Kelimeler

• Landslide
• bibliometry
• Türkiye
• article
• Web of Science

Türkiye Cumhuriyeti’nin 100. Yılında Türkiye Adresli Yayınların Dünya Heyelan Literatürüne Katkısı

Öz

Bu çalışmanın temel amacı, Türkiye Cumhuriyeti’nin 100. Yılında Türkiye açısından neden olduğu can ve mal kayıpları açısından önemli ve yaygın bir doğal tehlike olan heyelanlar konusunda Türkiye adresli araştırmaların Dünya literatürüne katkısı incelenmesidir. İnceleme kapsamında Web of Science kayıtları kullanılmış, adres olarak “Turkey veya Türkiye veya Türkiye”, bütün alanlarda ise “landslide*” anahtar kelimeleri kullanılmıştır. Elde edilen sorgu sonuçlarından sadece makale ve derleme çalışmaları dikkate alınmıştır. Sonuçta 721 adet kayıt elde edilmiş ve bu kayıtlar incelenmiştir. Türkiye adresli ilk yayın 1989 tarihlidir. Türkiye’de heyelan konulu uluslararası yayınlar geç başlamasına rağmen, alanının önemli dergileri olan Engineering Geology, Landslides, Environmental Earth Sciences, Computers & Geosciences ve Natural Hazard gibi dergilerde Türkiye adresli çok sayıda makale yayınlanmıştır. 1990’larda sınırlı sayıda makale yayınlanmışken, 2000’li yıllarda makale sayısında ciddi artış olmuş, 2020 yılında 66 sayısına ulaşmıştır. Makalelerin ortalama atıfı 33.73 gibi oldukça yüksek bir sayıya ulaşmış, Türkiye adresli araştırmacılar önemli bir başarı göstermiştir. Bununla birlikte, en çok atıf alan 10 makalenin toplam atıfı 630-339 arasında olup, olağanüstü yüksektir. Buna karşın, Türkiye adresli makalelerin %12.6’sı hiç atıf almamıştır. Sonuçta, makalelerin gerek nitelik ve niceliği gerekse atıf sayısı dikkate alındığında, Türkiye adresli heyelanla ilişkili yayınların uluslararası literatürde önemli bir etkiye sahip olduğu anlaşılmaktadır.

Anahtar Kelimeler

• heyelan
• bibliyometri
• Türkiye
• makale
• Web of Science

Kaynakça

1. Akgun, A. (2012). A comparison of landslide susceptibility maps produced by logistic regression, multi-criteria decision, and likelihood ratio methods: a case study at Izmir, Turkey. Landslides, 9 (1), 93-106, 10.1007/s10346-011-0283-7
2. Akın, M. (2013). Slope Stability Problems and Back Analysis in Heavily Jointed Rock Mass: A Case Study from Manisa, Turkey. Rock Mechanics and Rock Engineering, 46 (2), 359-371, 10.1007/ s00603-012-0262-x
3. Aksoy, C.O., Kose, H., Onargan, T., Koca, Y., & Heasley, K. (2004). Estimation of limit angle using laminated displacement discontinuity analysis in the Soma coal field, Western Turkey. International Journal of Rock Mechanics and Mining Sciences, 41 (4), 547-556, 10.1016/j. ijrmms.2003.01.002
4. Alcantara-Ayala, I. (2002). Geomorphology, natural hazards, vulnerability and prevention of natural disasters in developing countries. Geomorphology, 47, 107–124
5. Alimohammadlou, Y., Najafi, A., Gokceoglu, C. (2014). Estimation of rainfall-induced landslides using ANN and fuzzy clustering methods: A case study in Saeen Slope, Azerbaijan province, Iran. Catena, 120, 149-162, 10.1016/j. catena.2014.04.009
6. Bukhari, M.H., da Silva, P.F., Pilz, J., Istanbulluoglu, E., Görüm, T., Lee, J., Karamehic-Muratovic, A., Urmi, T., Soltani, A., Wilopo, W., Qureshi, J.A., Zekan, S., Koonisetty, K.S., Sheishenaly, U., Khan, L., Espinoza, J., Mendoza, E.P., & Haque, U., (2023). Community perceptions of landslide risk and susceptibility: a multi-country study. Landslides, 20, 1321–1334, DOI 10.1007/ s10346-023-02027-5
7. Demir G. (2019). GIS-based landslide susceptibility mapping for a part of the North Anatolian Fault Zone between Resadiye and Koyulhisar (Turkey). Catena, 183, 104211, 10.1016/j. catena.2019.104211
8. Demir, O., Inan, H.I., Biyik, C., &Uzun, B. (2015). Land management for erosion prevention: A case study for a Turkish nature reserve. 47, 394-400, 10.1016/j.landusepol.2015.01.036

9. Derin, L., & Ercanoğlu, M., (1998). Heyelan Duyarlılığı, Tehlikesi ve Riski ile İlgili Çalışmalarda Türkiye ve Avrupa Birliği Ülkelerinin Karşılaştırılması. Afet ve Risk Dergisi, 1(1), 26-38
10. Duman, T.Y. (2009). The largest landslide dam in Turkey: Tortum landslide. Engineering Geology, 104 (1-2), 66-79, https://doi.org/10.1016/j. enggeo.2008.08.006
11. Duman, T.Y., & Çan, T. (2023). Characteristics of landslides and assessment of deep-seated landslide susceptibility in Northern Turkey. Med. Geosc. Rev. 5, 131–157, https://doi.org/10.1007/ s42990-023-00105-3
12. Duman, T.Y., Çan, T., Emre, Ö., Keçer, M., Doğan, A., Ateş, Ş., & Durmaz, S. (2005a). Landslide inventory of northwestern Anatolia, Turkey. Engineering Geology, 77(1-2), 99-114, https:// doi.org/10.1016/j.enggeo.2004.08.005
13. Duman, T.Y., Can, T., Ulusay, R., Keçer, M., Emre, O., Ateş, S., & Gedik, I. (2005b). A geohazard reconnaissance study based on geoscientific information for development needs of the western region of Istanbul (Turkey). Environ Geol 48, 871–888 (2005). https://doi.org/10.1007/ s00254-005-0026-y
14. Eker, R., & Aydin, A. (2021). Long-term retrospective investigation of a large, deep-seated, and slow- moving landslide using InSAR time series, historical aerial photographs, and UAV data: The case of Devrek landslide (NW Turkey). Catena, 196, 104895, 10.1016/j.catena.2020.104895
15. Ercanoglu, M., & Gokceoglu, C., (2002). Assessment of landslide susceptibility for a landslide-prone area (north of Yenice, NW Turkey) by fuzzy approach. Environmental Geology, 41 (6), 720-730, 10.1007/s00254-001-0454-2
16. Erten, E., & Rossi, C., (2019). The worsening impacts of land reclamation assessed with Sentinel-1: The Rize (Turkey) test case. International Journal of Applied Earth Observation and Geoinformation,74, 57-64, 10.1016/j. jag.2018.08.007
17. Ekmekcioglu, O., & Koc, K. (2022). Explainable step- wise binary classification for the susceptibility assessment of geo-hydrological hazards. Catena, 216, 106379, 10.1016/j.catena.2022.106379
18. Froude, M. J., & Petley, D. N. (2018). Global fatal landslide occurrence from 2004 to 2016, Nat. Hazards Earth Syst. Sci., 18, 2161–2181, https:// doi.org/10.5194/nhess-18-2161-2018
19. Hastaoglu, K.O., Gul, Y., Poyraz, F., & Kara, B.C. (2019). Monitoring 3D areal displacements by a new methodology and software using UAV photogrammetry. International Journal of Applied Earth Observation and Geoinformation, 83, 101916, 10.1016/j.jag.2019.101916
20. Haque, U., Blum, P., Da Silva, P. F., Andersen, P., Pilz, J., Chalov, S. R., & Keellings, D., (2016). Fatal landslides in Europe. Landslides, 13, 1545-1554.
21. Gokceoglu, C. (2023). 6 February 2023 Kahramanmaraş – Türkiye Earthquakes: A general overwiev. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-1-2023, 417–424, https://doi.org/10.5194/isprs-archives- XLVIII-M-1-2023-417-2023
22. Gökçeoğlu, C., & Ercanoğlu, M. (2001). Heyelan duyarlılık haritalarının hazırlanmasında kullanılan parametrelere ilişkin belirsizlikler. Yerbilimleri, 23, 189-206
23. Gökçeoğlu, C., & Sezer, E. (2009). A statistical assessment on international landslide literature (1945–2008). Landslides, 6, 345–351, DOI 10.1007/s10346-009-0166-3
24. Gokceoglu, C., Okay, A.I., & Sezer, E. (2008). International earth science literature from Turkey 1970–2005: Trends and possible causes. Scientometrics, 74 (3), 409–423, DOI: 10.1007/ s11192-007-1813-x
25. Görüm, T. (2019). Tectonic, topographic and rock- type influences on large landslides at the northern margin of the Anatolian Plateau. Landslides, 16, 333–346, DOI 10.1007/s10346-018-1097-7
26. Görüm, T., & Fidan, S. (2021). Spatiotemporal variations of fatal landslides in Turkey. Landslides, 18, 1691–1705, DOI 10.1007/ s10346-020-01580-7
27. Görüm, T., Tanyas, H., Karabacak, F., Yilmaz, A., Girgin, S., Allstadt, K.E., Süzen, M.L., & Burgi, P. (2023). Preliminary documentation of coseismic ground failure triggered by the February 6, 2023 Turkiye earthquake sequence. Engineering Geology, 327, 107315, DOI 10.1016/j.enggeo.2023.107315
28. Grater, R.K. (1945). Landslide in Zion Canyon, Zion National Park, Utah. The Journal of Geology, 53 (2), 116-124, https://doi.org/10.1086/625254
29. Juang, C.H., Carranza-Torres, C., Crosta, G., Dong, J.-J., Gokceoglu, C., Jibson, R.W., Shakoor, A., Tang, H., van Asch, T.J.W., & Wasowski, J. (2016). Engineering geology — A fifty year perspective. Engineering Geology, 201, 67–70, http://dx.doi.org/10.1016/j.enggeo.2015.12.020
30. Jones, D.K.C., Lee, E.M., Hearn, G.J., & Genc, S. (1989). The Catak landslide disaster, Trabzon Province, Turkey. Terra Nova, 1 (1), 84-90, https://doi.org/10.1111/j.1365-3121.1989. tb00331.x
31. Keles, F., & Nefeslioglu, H.A. (2021). Infinite slope stability model and steady-state hydrology-based shallow landslide susceptibility evaluations: The Guneysu catchment area (Rize, Turkey). Catena, 200, 105161, 10.1016/j.catena.2021.105161
32. Karakas, G., Nefeslioglu, H.A., Kocaman, S., Buyukdemircioglu, M., Yurur, T., & Gokceoglu, C. (2021). Derivation of earthquake- induced landslide distribution using aerial photogrammetry: the January 24, 2020, Elazig (Turkey) earthquake. Landslides 18, 2193–2209, https://doi.org/10.1007/s10346-021-01660-2
33. Kavzoğlu, T., Sahin, E.K., & Colkesen, I. (2014). Landslide susceptibility mapping using GIS- based multi-criteria decision analysis, support vector machines, and logistic regression. Landslides, 11 (3), 425-439, 10.1007/s10346-013-0391-7
34. Kocaman, S., & Gokceoglu, C. (2019). A CitSci app for landslide data collection. Landslides, 16, 611–615, https://doi.org/10.1007/s10346-018-1101-2
35. Kocaman, S., Tavus, B., Nefeslioglu, H.A., Karakas, G., & Gokceoglu, C. (2020). Evaluation of Floods and Landslides Triggered by a Meteorological Catastrophe (Ordu, Turkey, August 2018) Using Optical and Radar Data. Geofluids, 2020, Article ID 8830661,| https:// doi.org/10.1155/2020/8830661
36. Korup, O., Görüm, T., & Hayakawa, Y. (2012). Without power? Landslide inventories in the face of climate change. Earth Surf. Process. Landforms, 37,92–99, DOI: 10.1002/esp.2248
37. Kumsar, H., Aydan, O., Tano, H., Celik, S.B., & Ulusay, R. (2016). An Integrated Geomechanical Investigation, Multi-Parameter Monitoring and Analyses of Babadag-Gundogdu Creep- like Landslide. Rock Mechanics and Rock Engineering, 49 (6), 2277-2299, 10.1007/ s00603-015-0826-7
38. Lima, P., Steger, S., Glade, T., Murillo-García, & F.G. (2022). Literature review and bibliometric analysis on data-driven assessment of landslide susceptibility. Journal of Mountain Science, 19(6). https://doi.org/10.1007/s11629-021-7254- 9
39. Liu, P., Li, Z., Hoey, T., Kincal, C., Zhang, J., Zeng, Q., & Muller, J.-P., (2013). Using advanced InSAR time series techniques to monitor landslide movements in Badong of the Three Gorges region, China. International Journal of Applied Earth Observation and Geoinformation, 21, 253-264, 10.1016/j.jag.2011.10.010
40. Nefeslioglu, H.A., & Görüm, T. (2020). The use of landslide hazard maps to determine mitigation priorities in a dam reservoir and its protection area. Land Use Policy, 91, 104363, 10.1016/j. landusepol.2019.104363
41. Nefeslioglu, H.A., Duman, T.Y., & Durmaz, S. (2008). Landslide susceptibility mapping for a part of tectonic Kelkit Valley (Eastern Black Sea region of Turkey). Geomorphology, 94 (3–4), 401-418, https://doi.org/10.1016/j.geomorph.2006.10.036
42. Nefeslioglu, H.A., Gokceoglu, C., & Sonmez, H., (2008). An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility. Engineering Geology, 97 (3-4), 171-191, 10.1016/j.enggeo.2008.01.004
43. Nefeslioglu, H.A., San, B.T., Gokceoglu, C., & Duman, T.Y. (2012). An assessment on the use of Terra ASTER L3A data in landslide susceptibility mapping. International Journal of Applied Earth Observation and Geoinformation, 14 (1), 40-60, 10.1016/j.jag.2011.08.005
44. Osmanoglu, B., Sunar, F., Wdowinski, S., & Cabral- Cano, E. (2016). Time series analysis of InSAR data: Methods and trends. ISPRS Journal of Phottogrammetry and Remote Sensing, 115, 90-102, 10.1016/j.isprsjprs.2015.10.003
45. Petley, D. (2012). Global patterns of loss of life from landslides. Geology, 40 (10), 927–930, doi:10.1130/G33217.1
46. Pourghasemi, H.R., Pradhan, B., & Gokceoglu, C., (2012). Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran. Natural Hazards, 63 (2), 965-996, 10.1007/ s11069-012-0217-2
47. Pradhan, B., Sezer, E.A., Gokceoglu, C., & Buchroithner, M. F. (2010). Landslide Susceptibility Mapping by Neuro-Fuzzy Approach in a Landslide-Prone Area (Cameron Highlands, Malaysia). IEEE Transactions on Geoscience and Remote Sensing, 48 (12), 4164-4177, 10.1109/TGRS.2010.2050328
48. San, B.T. (2014). An evaluation of SVM using polygon-based random sampling in landslide susceptibility mapping: The Candir catchment area (western Antalya, Turkey). International Journal of Applied Earth Observation and Geoinformation, 26, 399-412, 10.1016/j. jag.2013.09.010
49. Sezer, E.A., Pradhan, B., & Gokceoglu, C. (2011). Manifestation of an adaptive neuro-fuzzy model on landslide susceptibility mapping: Klang valley, Malaysia. Expert Systems with Applications, 38 (7), 8208-8219, 10.1016/j. eswa.2010.12.167
50. Yalcin, 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, 10.1016/j.catena.2007.01.003
51. Yalcin, A., Reis, S., Aydinoglu, A. C., & Yomralioglu, T., (2011). A GIS-based comparative study of frequency ratio, analytical hierarchy process, bivariate statistics and logistics regression methods for landslide susceptibility. Catena, 85 (3), 274-287, 10.1016/j.catena.2011.01.014
52. Yeşilnacar, E., & Topal, T., (2005). Landslide susceptibility mapping: A comparison of logistic regression and neural networks methods in a medium scale study, Hendek region (Turkey). Engineering Geology, 79 (3-4), 251-266, 10.1016/j.enggeo.2005.02.002
53. Yılmaz, I. (2009). Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat-Turkey). Computers & Geosciences, 35 (6), 1125-1138, 10.1016/j.cageo.2008.08.007
54. Yılmaz, I. (2010). Comparison of landslide susceptibility mapping methodologies for Koyulhisar, Turkey: conditional probability, logistic regression, artificial neural networks, and support vector machine. Environmental Earth Sciences, 61 (4), 821-836, 10.1007/s12665-009-0394-9
55. Zennaro, F., Furlan, E., Simeoni, C., Torresan, S., Aslan, S., Critto, A., & Marcomini, A. (2021). Exploring machine learning potential for climate change risk assessment. Earth-Science Reviews, 220, 103752, 10.1016/j.earscirev.2021.103752