Bir Kaya Düşme Alanında LiDAR Sensörlü Akıllı Telefon Kullanarak Tekil Kaya Blok Hacimlerinin Belirlenmesi

Year 2024, , 19 - 42, 26.06.2024

Mehmet Doğruluk , Nurgül Gültekin

https://doi.org/10.24232/jmd.1479304

Abstract

Bir kaya düşmesi bölgesinde düşen blokların hacminin belirlenmesi kaya düşmesi modelleme çalışmaları için önemli bir parametredir. Bu kapsamda yoğun bir araç trafiğinin bulunduğu Ankara Zir Vadisi yamaçlarından düşen 30 adet andezit bloğun hem şerit metre ile boyutları ölçülmüş, hem de lazer tarama özelliği bulunan bir akıllı telefon aracılığıyla fotogrametrik üç boyutlu (3B) modeli oluşturulmuştur. Böylece hem geleneksel, hem de fotogrametrik yöntemle toplanan veriler yardımıyla düşen blokların hacim hesapları gerçekleştirilmiş ve bu iki farklı yöntemle yapılan hesaplar karşılaştırılmıştır. Buna göre; geleneksel yöntemle belirlenen hacim değerleri ile fotogrametrik olarak belirlenen hacimler arasında istatiksel olarak yüksek bir ilişki bulunmaktadır. Arazide şerit metre ile yapılan ölçümler zaman kaybı oluşturmakta, sonuçlar ölçümü alan kişinin hassasiyetine bağlı olarak değişebilmektedir. Ayrıca, düzensiz bir şekle sahip blokların hacmi hesaplanırken şekil düzenli bir geometriye indirgenmekte ve bir yaklaşımda bulunulmaktadır. Akıllı telefonlar ile tek bir ölçümle her bir blok ayırtlanabilmekte ve hacimleri ayrı ayrı hesaplanabilmektedir. Elde edilen bulgular, çalışmada kullanılan fotogrametrik yöntemi uygulama pratikliği açısından ön plana çıkarmaktadır.

Keywords

Kaya düşmesi, Blok hacmi, Akıllı telefon, LiDAR, nokta bulutu

The Determination of Individual Rock Block Volumes Using a Smartphone with LIDAR Sensor for a Rockfall Area

Abstract

Determining the volume of fallen blocks in a rockfall area is a crucial parameter for rockfall modeling studies. Within this scope, the dimensions of 30 andesite blocks that had fallen from the slopes of the Ankara Zir Valley, where there is heavy vehicle traffic, were measured with a tape measure and a photogrammetric three-dimensional (3D) model was generated using a smartphone equipped with laser scanning capabilities. Hence, the fallen blocks’ volume was determined by utilizing data obtained from both conventional and photogrammetric methods, and, a comparison was subsequently made between the calculations derived from these two different approaches. There is a significant statistical correlation between the volume values obtained by the conventional method and those found using photogrammetry. Measurements conducted using tape measures in the field can be time consuming and the results may vary depending on the precision of the individual performing the measurement. Furthermore, while determining the volume of blocks that have an irregular shape, the shape is simplified to a regular geometric form and an approximation is performed. Smartphones enable the differentiation of each block through a single measurement, allowing the independent calculation of their volumes. These results emphasize the effectiveness of the photogrammetric method employed in this study.

Keywords

Rockfall, Block volume, Smartphone, LiDAR, Point cloud

References

• Agliardi, F., Crosta, G. B., & Frattini, P. (2009). Integrating Rockfall Risk Assessment and Countermeasure Design by 3D Modelling Techniques. Nat. Hazards Earth Syst. Sci., 9(4), 1059-1073. https://doi.org/https://doi. org/10.5194/nhess-9-1059-2009
• Ağca, M., Gültekin, N., & Kaya, E. (2020a). İnsansız Hava Aracından Elde Edilen Veriler ile Kaya Düşme Potansiyelinin Değerlendirilmesi: Adam Kayalar Örneği, Mersin. Geomatik, 5(2), 134- 145. https://doi.org/https://doi.org/10.29128/ geomatik.595574
• Ağca, M., Kaya, E., & Yılmaz, H. M. (2020b). Yersel Ve Fotogrametrik Yöntemler Ile Kaya Bloklarının Hacimlerinin Hesaplanması: Selime Örneği, Aksaray. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, 20(3), 465- 471. https://doi.org/https://doi.org/10.35414/ akufemubid.679005
• An, P., Fang, K., Jiang, Q., Zhang, H., & Zhang, Y. (2021). Measurement of Rock Joint Surfaces by Using Smartphone Structure From Motion (SFM) Photogrammetry. Sensors, 21(3), 922. https:// doi.org/https://doi.org/10.3390/s21030922
• Apple. (2023). iPhone 14 Pro Max - Teknik Özellikleri. Retrieved 1 Nisan from https://support.apple. com/tr-tr/111846
• Assali, P., Grussenmeyer, P., Villemin, T., Pollet, N., & Viguier, F. (2014). Surveying and Modeling of Rock Discontinuities by Terrestrial Laser Scanning and Photogrammetry: Semi-Automatic Approaches for Linear Outcrop Inspection. Journal of Structural Geology, 66, 102-114. https://doi.org/https://doi.org/10.1016/j. jsg.2014.05.014
• Battulwar, R., Zare-Naghadehi, M., Emami, E., & Sattarvand, J. (2021). A State-of-The-Art Review of Automated Extraction of Rock Mass Discontinuity Characteristics Using Three- Dimensional Surface Models. Journal of Rock Mechanics and Geotechnical Engineering, 13(4), 920-936. https://doi.org/https://doi. org/10.1016/j.jrmge.2021.01.008
• Bilgin, A. (2014). Türkiye Jeoloji Haritaları Ankara İ-28 Paftası (Publication Number 208) MTA Jeoloji Etütleri Dairesi. Ankara, Türkiye.
• Brach, M., Tracz, W., Krok, G., & Gąsior, J. (2023). Feasibility of Low-Cost LiDAR Scanner Implementation in Forest Sampling Techniques. Forests, 14(4), 706. https://doi.org/https://doi. org/10.3390/f14040706
• Catharia, O., Richard, F., Vignoles, H., Véron, P., Aoussat, A., & Segonds, F. (2023). Smartphone LiDAR Data: A Case Study for Numerisation of Indoor Buildings in Railway Stations. Sensors, 23(4), 1967. https://www.mdpi.com/1424- 8220/23/4/1967
• Chen, N., Kemeny, J., Jiang, Q., & Pan, Z. (2017). Automatic Extraction of Blocks from 3D Point Clouds of Fractured Rock. Computers & Geosciences, 109, 149-161. https://doi.org/ https://doi.org/10.1016/j.cageo.2017.08.013
• Corradetti, A., Seers, T., Mercuri, M., Calligaris, C., Busetti, A., & Zini, L. (2022). Benchmarking Different SfM-MVS Photogrammetric and İos LiDAR Acquisition Methods for the Digital Preservation of a Short-Lived Excavation: A Case Study from an Area of Sinkhole Related Subsidence. Remote Sensing, 14(20), 5187. https://doi.org/https://doi.org/10.3390/ rs14205187
• Çevre, Şehircilik ve İklim Değişikliği Bakanlığı. (2018). Ankara ili, Sincan ilçesi, Zir Vadisi Doğal Sit Alanı “Doğal Sit-Sürdürülebilir Koruma ve Kontrollü Kullanım Alanı» olarak tescil edilmiştir. Retrieved 1 Mayıs from https:// tvk.csb.gov.tr/ankara-ili-sincan-ilcesi-zir-vadisi- dogal-sit-alani-dogal-sit-surdurulebilir-koruma- ve-kontrollu-kullanim-alani-olarak-tescil- edilmistir.-duyuru-366770
• DiFrancesco, P.-M., Bonneau, D. A., & Hutchinson, D. J. (2021). Computational Geometry-Based Surface Reconstruction for Volume Estimation: A Case Study on Magnitude-Frequency Relations for A Lidar-Derived Rockfall Inventory. ISPRS International Journal of Geo-Information, 10(3), 157. https://doi.org/https://doi.org/10.3390/ ijgi10030157
• DJI. (2022). Osmo Mobile SE- Technical Specifications. Retrieved 30 Mart from https:// www.dji.com/global/osmo-mobile-se/specs
• Doğan, S., & Güllü, H. (2021). Multiple Methods for Voxel Modeling And Finite Element Analysis for Man-Made Caves in Soft Rock of Gaziantep. Bulletin of Engineering Geology and the Environment, 81(1), 23. https://doi.org/https:// doi.org/10.1007/s10064-021-02489-8
• Ersoy, O. (2003). Soğumakta Olan Lav Akıntısının Patlamalı Çökmesi Ile Oluşan Blok ve Kül Akışının ve Patlama Zonu Özelliklerinin Incelenmesi: Zir Çayı Lav Akışı Örneği, Kuzeybatı Ankara [Master’s Thesis, Hacettepe Üniversitesi]. Ankara, Türkiye.
• Frattini, P., Crosta, G., Carrara, A., & Agliardi, F. (2008). Assessment of Rockfall Susceptibility by Integrating Statistical and Physically-Based Approaches. Geomorphology, 94(3), 419-437. https://doi.org/https://doi.org/10.1016/j. geomorph.2006.10.037
• Gillihan, R. N. (2021). Accuracy Comparisons of iPhone 12 Pro LiDAR Outputs [Ph.D. Thesis, University of Colorado]. Colorado, USA
• Gopal, L., & Shukor, S. A. A. (2023). Modelling Small Artefact for Preservation – A Case Study of Perlis Heritage. Journal of Physics: Conference Series, 2641(1), 012005. https://doi.org/10.1088/1742-6596/2641/1/012005
• Guzzetti, F., Crosta, G., Detti, R., & Agliardi, F. (2002). STONE: A Computer Program for The Three-Dimensional Simulation of Rock-Falls. Computers & Geosciences, 28(9), 1079-1093. https://doi.org/https://doi.org/10.1016/S0098- 3004(02)00025-0
• Gülci, S., Yurtseven, H., Akay, A. O., & Akgul, M. (2023). Measuring tree diameter using a LiDAR-equipped smartphone: a comparison of smartphone- and caliper-based DBH. Environmental Monitoring and Assessment, 195(6), 678. https://doi.org/10.1007/s10661- 023-11366-8
• Güllü, M., Solmaz, M., Baybura, T., & Turgut, B. (2018). Tehlikeli Kaya Bloklarının Düşürülmesi ve Metrajlarının Lazer Tarayıcı Ile Hesaplanması. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, 18(1), 276-284. https://doi.org/https://doi.org/10.5578/ fmbd.66782
• Gültekin, N. (2023). Ankara Zir Vadisi kaya düşmelerinin üç boyutlu analizlerle değerlendirilmesi. Yerbilimleri, 44(2), 179- 201. https://doi.org/https://doi.org/10.17824/ yerbilimleri.1332884
• Hou, J., Hübner, P., Schmidt, J., & Iwaszczuk, D. (2024). Indoor Mapping with Entertainment Devices: Evaluating the Impact of Different Mapping Strategies for Microsoft HoloLens 2 and Apple iPhone 14 Pro. Sensors, 24(4), 1062. https://doi.org/https://doi.org/10.3390/ s24041062
• Illeditsch, M., & Preh, A. (2024). Determination of meaningful block sizes for rockfall modelling. Natural Hazards, 120(6), 5685-5710. https://doi. org/https://doi.org/10.1007/s11069-024-06432-4
• Ivanovski, I., Nedelkovska, N., Petrov, G., Jovanovski, M., & Nikolovski, T. (2023). Comparison Between Traditional And Contemporary Methods For Data Recording In Structural Geology. Geologica Macedonica, 37(2), 119-133. https://doi.org/10.46763/GEOL23372119i
• Jaklič, A., Erič, M., Mihajlović, I., Stopinšek, Ž., & Solina, F. (2015). Volumetric Models from 3D Point Clouds: The Case Study of Sarcophagi Cargo from a 2nd/3rd Century AD Roman Shipwreck near Sutivan on Island Brač, Croatia. Journal of Archaeological Science, 62, 143- 152. https://doi.org/https://doi.org/10.1016/j. jas.2015.08.007
• Jasińska, A., Pyka, K., Pastucha, E., & Midtiby, H. S. (2023). A Simple Way to Reduce 3D Model Deformation in Smartphone Photogrammetry. Sensors, 23(2), 728. https://doi.org/https://doi. org/10.3390/s23020728
• King, F., Kelly, R., & Fletcher, C. G. (2022). Evaluation of LiDAR-Derived Snow Depth Estimates From the iPhone 12 Pro. IEEE Geoscience and Remote Sensing Letters, 19, 1-5. https://doi.org/https:// doi.org/10.1109/LGRS.2022.3166665
• Koulibaly, A. S., Shahbazi, A., Saeidi, A., Rouleau, A., Quirion, M., & Chesnaux, R. (2023). Advancements in rock block volume calculation by analytical method for geological engineering applications. Environmental Earth Sciences, 82(13), 344. https://doi.org/https://doi. org/10.1007/s12665-023-11027-6
• Łabędź, P., Skabek, K., Ozimek, P., Rola, D., Ozimek, A., & Ostrowska, K. (2022). Accuracy Verification of Surface Models of Architectural Objects from the iPad LiDAR in the Context of Photogrammetry Methods. Sensors, 22(21), 8504. https://www.mdpi.com/1424- 8220/22/21/8504
• Li, B., Wei, J., Wang, L., Ma, B., & Xu, M. (2019). A Comparative Analysis of Two Point Cloud Volume Calculation Methods. International Journal of Remote Sensing, 40(8), 3227-3246. https://doi.org/https://doi.org/10.1080/01431161.2018.1541111
• Luetzenburg, G., Kroon, A., & Bjørk, A. A. (2021). Evaluation of the Apple iPhone 12 Pro LiDAR for an Application in Geosciences. Scientific Reports, 11(1), 22221. https://doi.org/https://doi. org/10.1038/s41598-021-01763-9
• Mikita, T., Balková, M., Bajer, A., Cibulka, M., & Patočka, Z. (2020). Comparison of Different Remote Sensing Methods for 3D Modeling of Small Rock Outcrops. Sensors, 20(6), 1663. https://doi.org/https://doi.org/10.3390/ s20061663
• Miller, S. H., Hashemian, A., Gillihan, R., & Benes, S. (2023). Accuracy and Repeatability of Mobile Phone LiDAR Capture https://doi. org/10.4271/2023-01-0614
• Monsalve, A., Yager, E. M., & Tonina, D. (2023). Evaluating Apple iPhone LiDAR measurements of topography and roughness elements in coarse bedded streams. Journal of Ecohydraulics, 1-11. https://doi.org/https://doi.org/10.1080/24705357.2023.2204087
• Moyano, J., Nieto-Julián, J. E., Fernández-Alconchel, M., Oreni, D., & Estévez-Pardal, R. (2023). Analysis and Precision of Light Detection and Ranging Sensors Integrated in Mobile Phones as a Framework for Registration of Ground Control Points for Unmanned Aerial Vehicles in the Scanning Technique for Building Information Modelling in Archaeological Sites. Drones, 7(7), 477. https://www.mdpi.com/2504-446X/7/7/477
• Nik Azhan Hakim, N., Razali, R., Said, M., Muhamad, M., Abdul Rahim, H., & Mokhtar, M. (2023). Accuracy Assessment on Detail Survey Plan Using iPhone 13 Pro Max LiDAR Sensor. International Journal of Geoinformatics, 19(5). https://doi.org/https://doi.org/10.52939/ijg. v19i5.2665
• Paukkonen, N. (2023). Towards a Mobile 3D Documentation Solution. Video-Based Photogrammetry and iPhone 12 Pro as Fieldwork Documentation Tools. Journal of Computer Applications in Archaeology. https:// doi.org/10.5334/jcaa.135
• Pavelka jr, K., Kuzmanov, P., Pavelka, K., & Rapuca, A. (2023). Different data joining as a basic model for hbim – a case project St. Pataleimon in Skopje. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-5/W2-2023, 85-91. https://doi.org/https://doi.org/10.5194/isprs- archives-XLVIII-5-W2-2023-85-2023
• Pix4D. (2024a). Capture a project - PIX4Dcatch. Retrieved 15 Mart from https://support.pix4d. com/hc/en-us/articles/4409722555025-Capture- a-project-PIX4Dcatch
• Pix4D. (2024b). How to process PIX4Dcatch datasets in PIX4Dmatic. Retrieved 25 Mart from https://support.pix4d.com/hc/en-us/ articles/4414523101073-How-to-process- PIX4Dcatch-datasets-in-PIX4Dmatic
• Pix4D. (2024c). FAQ - PIX4Dcatch. Retrieved 26 Mart from https://support.pix4d.com/ hc/ en- us/ articles/ 360043331092 - FAQ- PIX4Dcatch#benefits
• Pix4D. (2024d). Pix4D Processing options. Retrieved 25 Mart from https://support.pix4d.com/hc/en- us/sections/4407352591889-Processing-options
• Pix4D. (2024e). Volume measurement - PIX4Dsurvey. Retrieved 30 Ocak from https://support.pix4d. com/hc/en-us/articles/4405473285777-Volume- measurement-PIX4Dsurvey
• Rasti, S., Bleakley, C. J., Silvestre, G. C. M., Holden, N. M., Langton, D., & O’Hare, G. M. P. (2021). Crop Growth Stage Estimation Prior to Canopy Closure Using Deep Learning Algorithms. Neural Computing and Applications, 33(5), 1733-1743. https://doi.org/https://doi.org/10.1007/s00521- 020-05064-6
• Riquelme, A., Tomás, R., Cano, M., Pastor, J. L., & Jordá-Bordehore, L. (2021). Extraction of Discontinuity Sets of Rocky Slopes Using
• Iphone-12 Derived 3DPC and Comparison to TLS and SFM Datasets. IOP Conference Series: Earth and Environmental Science, 833(1), 012056. https://doi.org/https://doi. org/10.1088/1755-1315/833/1/012056
• Rutkowski, W., & Lipecki, T. (2023). Use of the iPhone 13 Pro LiDAR Scanner for Inspection and Measurement in the Mineshaft Sinking Process. Remote Sensing, 15(21), 5089. https:// doi.org/https://doi.org/10.3390/rs15215089
• Sarro, R., Riquelme, A., García-Davalillo, J. C., Mateos, R. M., Tomás, R., Pastor, J. L., Cano, M., & 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. https://doi.org/https://doi. org/10.3390/rs10121923
• Scargill, T., Premsankar, G., Chen, J., & Gorlatova, M. (2022, 3-6 May 2022). Here To Stay: A Quantitative Comparison of Virtual Object Stability in Markerless Mobile AR. 2022 2nd International Workshop on Cyber-Physical- Human System Design and Implementation (CPHS)
• Stevenson, S., & Liscio, E. (2024). Assessing iPhone LiDAR & Recon-3D for determining area of origin in bloodstain pattern analysis. Journal of Forensic Sciences, 69(3), 1045-1060. https://doi. org/https://doi.org/10.1111/1556-4029.15476
• Suleymanoglu, B., Tamimi, R., Yilmaz, Y., Soycan, M., & Toth, C. (2023). Road Infrastructure Mapping by Using Iphone 14 Pro: An Accuracy Assessment. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-1-2023, 347-353. https://doi.org/https://doi.org/10.5194/ isprs-archives-XLVIII-M-1-2023-347-2023
• Tamimi, R. (2022). Relative Accuracy Found within Iphone Data Collection. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 303-308. https://doi.org/https://doi.org/10.5194/ isprs-archives-XLIII-B2-2022-303-2022
• Tamimi, R., & Toth, C. (2023a). Performance Assessment of a Mini Mobile Mapping System: Iphone 14 Pro Installed on a e-Scooter. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-3-2023, 307-315. https://doi.org/https://doi.org/10.5194/isprs-archives- XLVIII-M-3-2023-307-2023
• Tamimi, R., & Toth, C. (2023b). Comparison of Iphone 13 Pro’s Camera and Lidar Sensor To UAS Photogrammetric Model of The Great Pyramid of Giza. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-3-2023, 299-306. https://doi.org/https://doi.org/10.5194/isprs- archives-XLVIII-M-3-2023-299-2023
• Tatsumi, S., Yamaguchi, K., & Furuya, N. (2023). ForestScanner: A mobile application for measuring and mapping trees with LiDAR- equipped iPhone and iPad. Methods in Ecology and Evolution, 14(7), 1603-1609. https://doi.org/ https://doi.org/10.1111/2041-210X.13900
• Tavani, S., Billi, A., Corradetti, A., Mercuri, M., Bosman, A., Cuffaro, M., Seers, T., & Carminati, E. (2022). Smartphone assisted fieldwork: Towards the digital transition of geoscience fieldwork using LiDAR-equipped iPhones. Earth- Science Reviews, 227, 103969. https://doi.org/ https://doi.org/10.1016/j.earscirev.2022.103969
• Tazudin, H., Shukor, S. A. A., & Johari, J. (2023). Performance Evaluation of Different Devices and Algorithms for Modelling Small Artefact. Journal of Physics: Conference Series, 2641(1), 012026. https://doi.org/10.1088/1742- 6596/2641/1/012026
• Teppati Losè, L., Spreafico, A., Chiabrando, F., & Giulio Tonolo, F. (2022). Apple LiDAR Sensor for 3D Surveying: Tests and Results in the Cultural Heritage Domain. Remote Sensing, 14(17), 4157. https://doi.org/https://doi. org/10.3390/rs14174157
• Tondo, G. R., Riley, C., & Morgenthal, G. (2023). Characterization of the iPhone LiDAR-Based Sensing System for Vibration Measurement and Modal Analysis. Sensors, 23(18), 7832. https:// doi.org/https://doi.org/10.3390/s23187832
• Topal, T., Akin, M., & Ozden, U. A. (2007). Assessment of Rockfall Hazard Around Afyon Castle, Turkey. Environmental Geology, 53(1), 191-200. https://doi.org/https://doi.org/10.1007/ s00254-006-0633-2
• Torkan, M., Janiszewski, M., Uotinen, L., & Rinne, M. (2023). Method to obtain 3D point clouds of tunnels using smartphone LiDAR and comparison to photogrammetry. IOP Conference Series: Earth and Environmental Science, 1124(1), 012016. https://doi.org/https://doi. org/10.1088/1755-1315/1124/1/012016
• Umili, G., Bonetto, S. M. R., Mosca, P., Vagnon, F., & Ferrero, A. M. (2020). In Situ Block Size Distribution Aimed at the Choice of the Design Block for Rockfall Barriers Design: A Case Study along Gardesana Road. Geosciences, 10(6),223. https://doi.org/https://doi.org/10.3390/ geosciences10060223
• Vacca, G. (2023). 3D Survey with Apple LiDAR Sensor— Test and Assessment for Architectural and Cultural Heritage. Heritage, 6(2), 1476-1501. https://www.mdpi.com/2571-9408/6/2/80
• Walton, G., & Weidner, L. (2023). Accuracy of Rockfall Volume Reconstruction from Point Cloud Data—Evaluating the Influences of Data Quality and Filtering. Remote Sensing, 15(1),165. https://doi.org/https://doi.org/10.3390/ rs15010165
• Wang, Y., Ding, M., Zhang, Q., Zhang, X., & Qu, Z. (2023). Volume calculation methods of irregular stone artifacts based on 3D laser scanning technology. Journal of Asian Architecture and Building Engineering, 22(6), 3386-3402. https:// doi.org/https://doi.org/10.1080/13467581.2023. 2182640
• Winberg, O., Pyörälä, J., Yu, X., Kaartinen, H., Kukko, A., Holopainen, M., Holmgren, J., Lehtomäki, M., & Hyyppä, J. (2023). Branch information extraction from Norway spruce using handheld laser scanning point clouds in Nordic forests. ISPRS Open Journal of Photogrammetry and Remote Sensing, 9, 100040. https://doi.org/ https://doi.org/10.1016/j.ophoto.2023.100040