Skip to main content

Advertisement

Log in

UAV-based investigation of earthquake-induced deformation and landscape changes: a case study of the February 6, 2023 Earthquakes in Hatay, Türkiye

  • Research
  • Published:
Earth Science Informatics Aims and scope Submit manuscript

Abstract

This study uses Unmanned Aerial Vehicles (UAVs) to investigate earthquake-induced deformation in Turkey’s Hatay region after significant earthquakes in February 2023. The study employs UAV photogrammetry to get high-resolution 3D modeling and aerial imagery to analyze surface deformations and fractures in the bedrock. Results show extensive fractures and fragmentation, with 7 cracks ranging from 24.11 to 497.69 m in length. Two subsidence areas are identified, measuring 23,060.8 m² and 13,954.2 m² respectively, with elevation changes of up to 20 m. Profile analysis within the subsidence area reveals the extent of physical deformations. The accuracy and precision of the photogrammetric products are validated with a Root Mean Square Error (RMSE) of 4.6 cm, indicating high accuracy. The 3 Dimensional (3D) models and observed fractures provide insights into the spatial patterns and magnitudes of surface deformations. This study demonstrates the effectiveness of UAV-based data in analyzing earthquake-induced deformations and landscape changes, offering a foundation for future research.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  • Achille C, Adami A, Chiarini S, Cremonesi S, Fassi F, Fregonese L, Taffurelli L (2015) UAV-based photogrammetry and integrated technologies for architectural applications—methodological strategies for the after-quake survey of vertical structures in Mantua (Italy). Sensors 15(7):15520–15539. https://doi.org/10.3390/s150715520

    Article  Google Scholar 

  • Agisoft (2023) https://www.agisoft.com/forum/index.php?topic=7310.0 (Accessed August 2023)

  • Akca S, Polat N (2022) Semantic segmentation and quantification of trees in an orchard using UAV orthophoto. Earth Sci Inf 15(4):2265–2274. https://doi.org/10.1007/s12145-022-00871-y

    Article  Google Scholar 

  • Barnston A (1992) Correspondence among the correlation [root mean square error] and Heidke Verifcation measures. Refinement of the Heidke Score

  • Bayrakdar C, Halis O, Canpolat E, Döker MF, Keserci F (2023) 6 Şubat 2023 Kahramanmaraş-Ekinözü depremi (mw 7.6) ile ilişkili Çardak Fayı yüzey kırığının tektonik jeomorfolojisi. Türk Coğrafya Dergisi 837–22 (in Turkish). https://doi.org/10.17211/tcd.1281680

  • Bemis SP, Micklethwaite S, Turner D, James MR, Akciz S, Thiele ST, Bangash HA (2014) Ground-based and UAV-Based photogrammetry: a multi-scale, high-resolution mapping tool for structural geology and paleoseismology. J Struct Geol 69:163–178. https://doi.org/10.1016/j.jsg.2014.10.007

    Article  Google Scholar 

  • Cook KL (2017) An evaluation of the effectiveness of low-cost UAVs and structure from motion for geomorphic change detection. Geomorphology 278:195–208. https://doi.org/10.1016/j.geomorph.2016.11.009

    Article  Google Scholar 

  • Ding J, Zhang J, Zhan Z, Tang X, Wang X (2022) A Precision efficient method for collapsed building detection in post-earthquake UAV images based on the Improved NMS Algorithm and faster R-CNN. Remote Sens 14(3):663

    Article  Google Scholar 

  • Dominici D, Alicandro M, Massimi V (2017) UAV photogrammetry in the post-earthquake scenario: case studies in L’Aquila. Geomatics, Natural Hazards and Risk, 8(1), 87–103

  • Duarte D, Nex F, Kerle N, Vosselman G (2017) Towards a more efficient detection of Earthquake induced facade damages using oblique UAV imagery. Int Archives Photogrammetry Remote Sens Spat Inform Sci 42:93–100

    Article  Google Scholar 

  • Duffy JP, Cunliffe AM, DeBell L, Sandbrook C, Wich SA, Shutler JD, … and, Anderson K (2018) Location, location, location: considerations when using lightweight drones in challenging environments. Remote Sens Ecol Conserv 4(1):7–19. https://doi.org/10.1002/rse2.58

    Article  Google Scholar 

  • Esteban CH, Schmitt F (2004) Silhouette and stereo fusion for 3D object modeling. Comput Vis Image Underst 96(3):367–392

    Article  Google Scholar 

  • Eyübagil EE, Yaşar ŞŞ, Çakanşimşek EB, Duman H, Solak Hİ, Özkan A, … and, Özener H (2023) 6 Şubat 2023 Sofalaca-Şehitkamil Gaziantep (Mw: 7.7) ve Ekinözü Kahramanmaraş (Mw: 7.6) Depremlerinin GNSS Gözlemlerine Bağlı Öncül Sonuçları. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 23(1):160–176 (in Turkish). 10.35414/ akufemubid.1251601

    Article  Google Scholar 

  • França Pereir F, Sussel Gonçalves Mendes T, Jorge Coelho Simões S, Roberto Magalhães de Andrade M, Luiz Lopes Reiss M, Fortes Cavalcante Renk J, Correia da Silva Santos T (2023) Comparison of LiDAR-and UAV-derived data for landslide susceptibility mapping using Random Forest algorithm. Landslides 20(3):579–600. https://doi.org/10.1007/s10346-022-02001-7

    Article  Google Scholar 

  • Graber A, Santi P (2023) UAV-photogrammetry rockfall monitoring of natural slopes in Glenwood Canyon, CO, USA: background activity and post-wildfire impacts. Landslides 20(2):229–248. https://doi.org/10.1007/s10346-022-01974-9

    Article  Google Scholar 

  • Hsieh CS, Hsiao DH, Lin DY (2023) Contour Mission Flight Planning of UAV for Photogrammetric in Hillside areas. Appl Sci 13(13):7666. https://doi.org/10.3390/app13137666

    Article  Google Scholar 

  • Hu S, Qiu H, Pei Y, Cui Y, Xie W, Wang X, … and, Cao M (2019) Digital terrain analysis of a landslide on the loess tableland using high-resolution topography data. Landslides 16:617–632. https://doi.org/10.1007/s10346-018-1103-0

    Article  Google Scholar 

  • Işık E, Avcil F, Büyüksaraç A, İzol R, Arslan MH, Aksoylu C, … and, Ulutaş H (2023) Structural damages in masonry buildings in Adıyaman during the Kahramanmaraş (Turkiye) Earthquakes (mw 7.7 and mw 7.6) on 06 February 2023. Eng Fail Anal 107405. https://doi.org/10.1016/j.engfailanal.2023.107405

  • İTÜ, İstanbul T, Üniversitesi (2023) 6 February 2023: 04.17 mw 7.8 Kahramanmaraş and 13.24 mw 7.7 Kahramanmaraş Earthquakes: preliminary investigation report. Istanbul Technical University.(in Turkish

  • James MR, Robson S, Smith MW (2017) 3-D uncertainty‐based topographic change detection with structure‐from‐motion photogrammetry: precision maps for ground control and directly georeferenced surveys. Earth Surf Proc Land 42(12):1769–1788. https://doi.org/10.1002/esp.4125

    Article  Google Scholar 

  • Karakas G, Nefeslioglu HA, 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(6):2193–2209. https://doi.org/10.1007/s10346-021-01660-2

    Article  Google Scholar 

  • Kim S, Irizarry J, Costa DB (2020) Field test-based UAS operational procedures and considerations for construction safety management: a qualitative exploratory study. Int J Civil Eng 18:919–933. https://doi.org/10.1007/s40999-020-00512-9

    Article  Google Scholar 

  • Kim H, Hyun CU, Park HD, Cha J (2023) Image mapping accuracy evaluation using UAV with Standalone, Differential (RTK), and PPP GNSS Positioning techniques in an Abandoned Mine Site. Sensors 23(13):5858. https://doi.org/10.3390/s23135858

    Article  Google Scholar 

  • Kocaman İ (2023) The effect of the Kahramanmaraş Earthquakes (mw 7.7 and mw 7.6) on historical masonry mosques and minarets. Eng Fail Anal 149:107225. https://doi.org/10.1016/j.engfailanal.2023.107225

    Article  Google Scholar 

  • Kovanič Ľ, Štroner M, Blistan P, Urban R, Boczek R (2023) Combined ground-based and UAS SfM-MVS approach for determination of geometric parameters of the large-scale industrial facility–case study. Measurement 216:112994. https://doi.org/10.1016/j.measurement.2023.112994

    Article  Google Scholar 

  • Kumar K, Kumar N (2023) Region coverage-aware path planning for unmanned aerial vehicles: a systematic review. Phys Communication 102073. https://doi.org/10.1016/j.phycom.2023.102073

  • Levine NM, Spencer BF Jr (2022) Post-earthquake building evaluation using UAVs: a BIM-based digital twin framework. Sensors 22(3):873

    Article  Google Scholar 

  • Liu X, Zhu W, Lian X, Xu X (2023) Monitoring mining surface subsidence with multi-temporal three-dimensional unmanned aerial vehicle point cloud. Remote Sens 15(2):374. https://doi.org/10.3390/rs15020374

    Article  Google Scholar 

  • Loh R, Bian Y, Roe T (2009) UAVs in civil airspace: safety requirements. IEEE Aerosp Electron Syst Mag 24(1):5–17

    Article  Google Scholar 

  • Lucieer A, Turner D, King DH, Robinson SA (2014) Using an unmanned aerial vehicle (UAV) to capture micro-topography of Antarctic Moss beds. Int J Appl Earth Obs Geoinf 27:53–62

    Google Scholar 

  • Ma S, Xu C, Shao X, Zhang P, Liang X, Tian Y (2019) Geometric and kinematic features of a landslide in Mabian Sichuan, China, derived from UAV photography. Landslides 16:373–381. https://doi.org/10.1007/s10346-018-1104-z

    Article  Google Scholar 

  • Mazzanti P, Caporossi P, Brunetti A, Mohammadi FI, Bozzano F (2021) Short-term geomorphological evolution of the Poggio Baldi landslide upper scarp via 3D change detection. Landslides 18(7):2367–2381. https://doi.org/10.1007/s10346-021-01647-z

    Article  Google Scholar 

  • Mckenzie DP (1970) Plate tectonics of the Mediterranean region. Nature 226(5242):239–243

    Article  Google Scholar 

  • Meng X, Shang N, Zhang X, Li C, Zhao K, Qiu X, Weeks E (2017) Photogrammetric UAV mapping of terrain under dense coastal vegetation: an object-oriented classification ensemble algorithm for classification and terrain correction. Remote Sens 9(11):1187

    Article  Google Scholar 

  • Narin OG, Abdikan S (2023) Multi-temporal analysis of inland water level change using ICESat-2 ATL-13 data in lakes and dams. Environ Sci Pollut Res 30(6):15364–15376. https://doi.org/10.1007/s11356-022-23172-9

    Article  Google Scholar 

  • Nedjati A, Vizvari B, Izbirak G (2016) Post-earthquake response by small UAV helicopters. Nat Hazards 80:1669–1688

    Article  Google Scholar 

  • Özer M (2023) Education policy actions by the Ministry of National Education after the historical Earthquake Disaster on February 6, 2023 in Türkiye. Bartın Univ J Fac Educ 12(2):1–14

    Google Scholar 

  • Polat N (2023) An investigation of Ancient Water Collection and Storage systems Near the Karahantepe Neolithic Site using UAV and GIS. Environ Archaeol 1–13. https://doi.org/10.1080/14614103.2023.2216530

  • Polat N, Uysal M (2018) An experimental analysis of digital elevation models generated with Lidar Data and UAV photogrammetry. J Indian Soc Remote Sens 46(7):1135–1142. https://doi.org/10.1007/s12524-018-0760-8(0123456789(),-volV)(0123456789(),-volV)

    Article  Google Scholar 

  • Polat N, Uysal M, Toprak AS (2015) An investigation of DEM generation process based on LiDAR data filtering, decimation, and interpolation methods for an urban area. Measurement 75:50–56

    Article  Google Scholar 

  • Raghunatha A, Thollander P, Barthel S (2023) Addressing the emergence of drones–A policy development framework for regional drone transportation systems. Transp Res Interdisciplinary Perspect 18:100795. https://doi.org/10.1016/j.trip.2023.100795

    Article  Google Scholar 

  • Salunke S, Ramsankaran R, Ghosh S, Milani G, Halani B, Cundari GA, … and, Gangurde N (2023), May Global Vipassana Pagoda: Exterior Geometry Envelope Extraction Using UAV Photogrammetry. In 2023 IEEE International Workshop on Metrology for Living Environment (MetroLivEnv) (pp. 225–229). IEEE. https://doi.org/10.1109/MetroLivEnv56897.2023.10164027

  • Şengör AM, C, Görür N, Şaroğlu F (1985) “Strike-Slip Faulting and Related Basin Formation in Zones of Tectonic Escape: Turkey as a Case Study”, Strike-Slip Deformation, Basin Formation, and Sedimentation, (Ed.) Kevin T. Biddle, Nicholas Christie-Blick

  • Singh CH, Rai A, Mishra V, Kushwaha SKP (2023), January and Jain K. Quality Assessment of UAV Data using Multiple RTK Reference Stations. In 2023 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing (Vol. 1, pp. 1–4). IEEE. https://doi.org/10.1109/MIGARS57353.2023.10064555

  • Smith MW, Carrivick JL, Quincey DJ (2016) Structure from motion photogrammetry in physical geography. Prog Phys Geogr 40(2):247–275. https://doi.org/10.1177/0309133315615805

    Article  Google Scholar 

  • Snavely N, Seitz SM, Szeliski R (2008) Modeling the world from internet photo collections. Int J Comput Vision 80:189–210

    Article  Google Scholar 

  • Sudra P, Demarchi L, Wierzbicki G, Chormański J (2023) A comparative Assessment of Multi-source Generation of Digital Elevation Models for Fluvial landscapes characterization and monitoring. Remote Sens 15(7):1949. https://doi.org/10.3390/rs15071949

    Article  Google Scholar 

  • USGS, The U.S. Geological Survey (2023) https://www.usgs.gov/faqs/why-are-we-having-so-many-earthquakes-has-naturally-occurring-earthquake-activity-been#:~:text=According%20to%20long%2Dterm%20records,earthquake%20magnitude%208.0%20or%20greater. (Accessed August 2023)

  • Uysal M, Toprak AS, Polat N (2015) DEM generation with UAV Photogrammetry and accuracy analysis in Sahitler hill. Measurement 73:539–543. https://doi.org/10.1016/j.measurement.2015.06.010

    Article  Google Scholar 

  • World Health Organization-WHO (2022) Earthquakes. https://www.who.int/health-topics/earthquakes#tab=tab_1

  • Yilmaz M, Uysal M (2017) Comparing uniform and random data reduction methods for DTM accuracy. Int J Eng Geosci 2(1):9–16

    Article  Google Scholar 

  • Zeybek M, Biçici S (2022) Investigation of landslide-based road surface deformation in mountainous areas with single period UAV data. Geocarto Int 37(27):18638–18664. https://doi.org/10.1080/10106049.2022.2142969

    Article  Google Scholar 

  • Zeybek M, Taşkaya S, Elkhrachy I, Tarolli P (2023) Improving the spatial accuracy of UAV platforms using direct georeferencing methods: an application for Steep Slopes. Remote Sens 15(10):2700. https://doi.org/10.3390/rs15102700

    Article  Google Scholar 

Download references

Funding

This research received no external funding.

Author information

Authors and Affiliations

Authors

Contributions

N.P. carried out all the data processing, analysis and writing works of the study.

Corresponding author

Correspondence to Nizar Polat.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

Communicated by H. Babaie.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Polat, N. UAV-based investigation of earthquake-induced deformation and landscape changes: a case study of the February 6, 2023 Earthquakes in Hatay, Türkiye. Earth Sci Inform 16, 3765–3777 (2023). https://doi.org/10.1007/s12145-023-01128-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12145-023-01128-y

Keywords

Navigation