ORIGINAL ARTICLE
Monitoring mass movements using Network-RTK measurement technique and producing potential rockfall scenarios in a paleo-landslide area
1
Department of Geomatics Engineering, Faculty of Engineering, Karadeniz Technical University, 61080, Trabzon, Turkey
2
Department of Geomatics Engineering, Faculty of Engineering, Artvin Çoruh University, 08100, Artvin, Turkey
Submission date: 2023-02-08
Acceptance date: 2023-05-25
Online publication date: 2023-06-29
Publication date: 2023-06-01
Reports on Geodesy and Geoinformatics 2023;115:9-17
KEYWORDS
ABSTRACT
Mass movements resulting from landslides cause significant losses in terms of lives and property. Periodic observations of these movements using geodetic measurement techniques help to prevent these losses. Network-RTK measurement technique produces real-time location with centimeter accuracy, based on phase observations using a network of reference stations. In this study, the paleo-landslide area in the Işıklar location of Trabzon province, Esiroğlu district, Turkey, was chosen as the application area. This study aims to measure the application area between 2019 and 2021, using the Network-RTK technique to determine the mass movements. Additionally, there is a rock block in an area with a steep slope. The possible movement of this rock block is a threat to infrastructure facilities, residential areas, agricultural areas, and life safety if the mass movement continues. Within this scope, the potential movement scenarios of the block were produced using RocPro3D software and UAV photogrammetry. Scenarios following an ongoing mass movements in the region triggering another mass movement are discussed. In the light of the results obtained, mass movements in the vertical direction of up to 28 cm were detected in the area where the rock block is located in the last 2 years. The periodic continuation of mass movements in the study area, declared a disaster-prone area, confirms the importance of the rock block in the region. In another phase of the study, possible movement scenarios of the rock block were examined using a rockfall analysis. In this context, with the help of an unmanned aerial vehicle, a digital elevation model and orthophoto map of the region where the rock block is likely to move was produced and a base map to be used in rockfall analysis was obtained. As a result of the rockfall analysis, maps showing the speed, energy, spread, possible impacts, and stopping points were produced. With the examination of these maps, it has been determined that residential areas, agricultural areas, and infrastructure facilities in the study area may be significantly damaged.
REFERENCES (25)
1.
Abidin, H. Z., Andreas, H., Gamal, M., Surono, S., and Hendrasto, M. (2004). Studying landslide displacements in Megamendung (Indonesia) using GPS survey method. Journal of Engineering and Technological Sciences, 36(2):109–123, doi:10.5614/itbj.eng.sci.2004.36.2.2.
2.
AFAD (2016). Geological survey report (in Turkish). Macka, Esiroglu, Isiklar area, Trabzon.
3.
Akin, M., Dinçer, İ., Ok, A. Ö., Orhan, A., Akin, M. K., and Topal, T. (2021). Assessment of the effectiveness of a rock-fall ditch through 3-D probabilistic rockfall simulations and automated image processing. Engineering Geology, 283:106001, doi:10.1016/j.enggeo.2021.106001.
4.
Bayrak, T. (2003). Creating a dynamic deformation and a dynamic motion surface model for landslides (in Turkish). PhD thesis, Karadeniz Technical University, Institute of Science and Technology, Trabzon.
5.
Ergünay, O. (2009). Disaster management: general principles, definitions, concepts (in Turkish). General Directorate of Disaster Affairs, Ankara.
6.
Geo-matching (2023). The principles and performance of cors, network rtk and vrs. ComNav Technology. Last accessed January 2023.
7.
Gili, J. A., Corominas, J., and Rius, J. (2000). Using Global Positioning System techniques in landslide monitoring. Engineering geology, 55(3):167–192, doi:10.1016/S0013-7952(99)00127-1.
8.
İnal, C., Gündüz, A. M., and Bülbül, S. (2014). Comparison of classical RTK and NETWORK-RTK methods (in Turkish). Selcuk University Journal of Engineering, Science & Technology, 2(2):19–29, doi:10.15317/Scitech.201426890.
9.
Kahveci, M. (2009). Kinematic GNSS and RTK CORS Networks (in Turkish). Zerpa Tourism Publishing Ltd. Sti., Ankara.
10.
Kalkan, Y., Alkan, R., Yanalak, M., Tari, E., and Erden, T. (2003). Landslide monitoring study with geotechnical and geodetic methods in the area of Altaş Ambarlı port facilities (in Turkish). Technical report.
11.
Koçyiğit (2019). Evaluation of rockfalls affecting Göre (Nevşehir) and its surroundings (in Turkish). Master’s thesis, Nevşehir Hacı Bektaş Veli University.
12.
Leyva, S., Cruz-Pérez, N., Rodríguez-Martín, J., Miklin, L., and Santamarta, J. C. (2022). Rockfall and rainfall correlation in the Anaga nature reserve in Tenerife (Canary Islands, Spain). Rock Mechanics and Rock Engineering, 55(4):2173–2181, doi:10.1007/s00603-021-02762-y.
13.
Li, L. and Lan, H. (2015). Probabilistic modeling of rockfall trajectories: a review. Bulletin of Engineering Geology and the Environment, 74:1163–1176, doi:10.1007/s10064-015-0718-9.
14.
Li, W., Liu, Y., Yang, L., and Chen, Y. (2020). Deformation characteristics and exploratory data analysis of rainfall-induced rotational landslide: A case study of the Zhutoushan landslide in Nanjing, China. Natural Hazards and Earth System Sciences Discussions, pages 1–11, doi:10.5194/nhess-2020-175.
15.
Ozturk, M. Z., Utlu, M., and Şimşek, M. (2022). UAV based 3D modeling analysis in determining and preventing rockfall hazard: a case study from Murtaza Village (Nigde, Turkey). Bulletin for Earth Sciences, 43(2):174–188.
17.
Pektaş, F. (2010). Kinematic Positioning Based on Real Time National and Local Fixed GNSS Networks (in Turkish). PhD thesis, YTU Institute of Science and Technology, Istanbul. RocPro3D (2014). RocPro3D software. http://www.rocpro3d.com/rocpro....
18.
Saleh, B. and Al-Bayari, O. (2007). Geodetic monitoring of a landslide using conventional surveys and GPS techniques. Survey Review, 39(305):252–260, doi:10.1179/175227007X197165.
19.
Samardžić-Petrović, M., Popović, J., Ðurić, U., Abolmasov, B., Pejić, M., and Marjanović, M. (2020). Permanent GNSS monitoring of landslide Umka. In XIV International Conference On Contemporary Theory And Practice In Construction XIV Stepgrad XIV Proceedings, 2020. University of Banja Luka Faculty of Architecture, Civil Engineering and Geode, doi:10.7251/STP2014091S.
20.
Sarro, R., Riquelme, A., García-Davalillo, J. C., Mateos, R. M., Tomás, R., Pastor, J. L., Cano, M., and Herrera, G. (2018). Rockfall simulation based on UAV photogrammetry data obtained during an emergency declaration: Application at a cultural heritage site. Remote sensing, 10(12):1923, doi:10.3390/rs10121923.
21.
Şener, E. (2019). Geographical information systems-based 3D modeling of possible rockfalls using unmanned aerial vehicles: Example of Kasımlar village (Isparta-Turkey) (in Turkish). Journal of Suleyman Demirel University Institute of Science and Technology, 23(2):419–426, doi:10.19113/sdufenbed.501482.
22.
Squarzoni, C., Delacourt, C., and Allemand, P. (2005). Differential single-frequency GPS monitoring of the La Valette landslide (French Alps). Engineering Geology, 79(3-4):215–229, doi:10.1016/j.enggeo.2005.01.015.
23.
Tiwari, A., Narayan, A., Devara, M., Dwivedi, R., and Dikshit, O. (2018). Multi-sensor geodetic approach for landslide detection and monitoring. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 4:287–292, doi:10.5194/isprs-annals-IV-5-287-2018.
24.
Wang, G. (2011). GPS landslide monitoring: single base vs. network solutions—a case study based on the Puerto Rico and Virgin Islands permanent GPS network. Journal of Geodetic Science, 1(3):191–203, doi:10.2478/v10156-010-0022-3.
25.
Yuceses, O., Erenoglu, R., and Erenoglu, O. (2016). GPS/GNSS Verileriyle Heyelanlarin CBS Ortaminda Uç Boyutlu Modellenmesi ve Analizi. In 6. Uzaktan Algilama-CBS Sempozyumu (UZAL-CBS 2016), 5-7 Ekim, Adana.
| eISSN: | 2391-8152 |
| ISSN: | 2391-8365 |
© 2006-2024 Journal hosting platform by Bentus
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
