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Synergy of remote sensing data collected with low-cost mobile mapping platform for detection and prediction of damages: a park alley case study

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Warianty tytułu
PL
Synergia danych teledetekcyjnych pozyskanych z wykorzystaniem niskobudżetowej mobilnej platformy kartującej do wykrywania i predykcji uszkodzeń na przykładzie alei w parku
Języki publikacji
EN
Abstrakty
EN
Data synergy involves acquiring and combining data from different sensors to achieve better problem analysis and research results. For more comprehensive data analysis, the sensors are not only mounted on one platform. Still, they should also be compatible with software and hardware, e.g. for the same timestamp registration by different sensors. The aim of this article is to propose the synergy between various remote sensing sensors including the ground penetrating radar (GPR), LiDAR (Light Detection and Ranging) sensor and three photogrammetric RGB cameras for damage detection in a pavement in a park alley. The data were acquired with a low-cost platform, in the Pole Mokotowskie Park in Warsaw, Poland. Three drives were made along the same path with the platform, so it was possible to assess the repeatability of the data. Based on the GPR data, orthophotomap, and digital terrain model (DTM) from images, an analysis of the cracks in the pavement was done. The paper proves additive value from the synergy of data collected for the alley also in the form of a common visualization of acquired data. Results presented in the article showed that using mobile mapping platform and technologies describing the situation above and below the ground level enable a more detailed analysis and inspection of the damages in the park alley.
PL
Synergia danych obejmuje pozyskiwanie i łączenie danych z różnych sensorów w celu wykonania lepszej jakości analiz i uzyskania lepszych wyników badań. W celu zapewnienia bardziej kompleksowej analizy danych, oprócz tego, że sensory są montowane na jednej platformie, powinny być one również kompatybilne z oprogramowaniem i sprzętem, np. w celu rejestracji tego samego znacznika czasu przez różne sensory. Celem tego artykułu jest zaproponowanie synergii między różnymi sensorami teledetekcyjnymi, z georadarem (GPR), czujnikiem LiDAR (Light Detection and Ranging) i trzema fotogrametrycznymi kamerami RGB do wykrywania uszkodzeń chodnika w alejce parkowej. Dane zostały pozyskane za pomocą niskokosztowej platformy w parku Pole Mokotowskie w Warszawie. Wykonano trzy przejazdy platformą po tej samej trasie, dzięki czemu możliwa była ocena powtarzalności danych. Na podstawie danych z georadaru, i numerycznego modelu terenu (NMT) ze zdjęć przeprowadzono analizę pęknięć w nawierzchni. W artykule udowodniono wartość dodaną wynikającą z synergii również w postaci wspólnej wizualizacji pozyskanych dla chodnika danych. Wyniki przedstawione w artykule wykazały, że wykorzystanie mobilnej platformy oraz technologii opisujących sytuację nad i pod poziomem gruntu umożliwia bardziej szczegółową analizę i inspekcję uszkodzeń w alejce parkowej.
Rocznik
Strony
619--634
Opis fizyczny
Bibliogr. 31 poz., il., tab.
Twórcy
  • Warsaw University of Technology, Faculty of Geodesy and Cartography, Warsaw, Poland
  • Warsaw University of Technology, Faculty of Geodesy and Cartography, Warsaw, Poland
autor
  • Warsaw University of Technology, Faculty of Geodesy and Cartography, Warsaw, Poland
  • Warsaw University of Technology, Faculty of Geodesy and Cartography, Warsaw, Poland
  • Warsaw University of Technology, Faculty of Civil Engineering, Warsaw, Poland
  • Warsaw University of Technology, Faculty of Geodesy and Cartography, Warsaw, Poland
  • Lviv Politechnic National University, Institute of Geodesy, Lviv, Ukraine
Bibliografia
  • [1] M. Varela-González, M. Solla, J. Martínez-Sánchez, and P. Arias, “A semi-automatic processing and visualisation tool for ground-penetrating radar pavement thickness data”, Automation in Construction, vol. 45, pp. 42-49, 2014, doi: 10.1016/J.AUTCON.2014.05.004.
  • [2] M.E. Torbaghan, W. Li, N. Metje, M. Burrow, D.N. Chapman, and C.D.F. Rogers, “Automated detection of road cracks using ground penetrating radar”, Journal of Applied Geophysics, vol. 179, art. no. 104118, 2020, doi: 10.1016/j.jappgeo.2020.104118.
  • [3] L. Krysiński and J. Sudyka, “GPR abilities in the investigation of the pavement transversal cracks”, Journal of Applied Geophysics, vol. 97, pp. 27-36, 2013, doi: 10.1016/J.JAPPGEO.2013.03.010.
  • [4] D. Merkle, C. Frey, and A. Reiterer, “Fusion of ground penetrating radar and laser scanning for infrastructure mapping”, Journal of Applied Geodesy, vol. 15, no. 1, pp. 31-45, 2021, doi: 10.1515/jag-2020-0004.
  • [5] B. Chetverikov, “Application of radar interferometry and ground-penetrating radar imaging for monitoring historical and cultural lands”, Modern Achievements in Geodetic Science and Industry, vol. 45, no. 1, pp. 153-160, 2023.
  • [6] A.T. Hassan and D. Fritsch, “Integration of laser scanning and photogrammetry in 3D/4D cultural heritage preservation – A Review”, International Journal of Applied Science and Technology, vol. 9, no. 4, p. 76-91, 2019, doi: 10.30845/ijastv9n4p9.
  • [7] A. Plichta and A. Piasecki, “Lidar and ground penetrating radar data in determining road surface conditions and geological characteristics of unstable soils”, Technical Sciences/University of Warmia and Mazury in Olsztyn, vol. 20, no. 2, pp. 111-129, 2017.
  • [8] I. Rodríguez-Santalla, D. Gomez-Ortiz, T. Martín-Crespo, et al., “Study and Evolution of the Dune Field of La Banya Spit in Ebro Delta (Spain) Using LiDAR Data and GPR”, Remote Sensing, vol. 13, no. 4, 2021, doi: 10.3390/rs13040802.
  • [9] R. Filzwieser, V. Ivanišević, G. J. Verhoeven, et al., “Integrating geophysical and photographic data to visualize the quarried structures of the Roman town of Bassianae”, Remote Sensing, vol. 13, no. 12, art. no. 2384, 2021, doi: 10.3390/rs13122384.
  • [10] Y. El Masri and T. Rakha, “A scoping review of non-destructive testing (NDT) techniques in building performance diagnostic inspections”, Construction and Building Materials, vol. 265, art. no. 120542, 2020, doi: 10.1016/j.conbuildmat.2020.120542.
  • [11] S. Cafiso, A. Di Graziano, D. Goulias, M. Mangiameli, and G. Mussumeci, “Bridge monitoring combining laser scanning and ground penetrating radar”, AIP Conference Proceedings, vol. 2116, no. 1, 2019, doi: 10.1063/1.5114287.
  • [12] S. Cafiso, A. Di Graziano, D. Goulias, M. Mangiameli, and G. Mussumeci, “Implementation of GPR and TLS data for the assessment of the bridge slab geometry and reinforcement”, Archives of Civil Engineering, vol. 66, no. 1, pp. 297-308, 2020, doi: 10.24425/ace.2020.131789.
  • [13] D. Merkle, A. Schmitt, and A. Reiterer, “Concept of an autonomous mobile robotic system for bridge inspection”, in Remote Sensing Technologies and Applications in Urban Environments V. SPIE, 2020, pp. 34-49, doi: 10.1117/12.2570633.
  • [14] W. Li, M. Burrow, N. Metje, and G. Ghataora, “Automatic road survey by using vehicle mounted laser for road asset management”, IEEE Access, vol. 8, pp. 94643-94653, 2020, doi: 10.1109/access.2020.2994470.
  • [15] N. Kamp, S. Russ, O. Sass, G. Tiefengraber, and S. Tiefengraber, “A Fusion of GPR-and LiDAR-Data for Surveying and Visualisation of Archaeological Structures-a case example of an archaeological site in Strettweg, District of Murtal, Austria”, in EGU General Assembly Conference Abstracts. 2014.
  • [16] I. Puente, M. Solla, S. Lagüela, and J. Sanjurjo-Pinto, “Reconstructing the Roman Site ‘Aquis Querquennis’ (Bande, Spain) from GPR, T-LiDAR and IRT Data Fusion”, Remote Sensing, vol. 10, no. 3, art. no. 379, 2018, doi: 10.3390/rs10030379.
  • [17] E. Adamopoulos, C. Colombero, C. Comina, et al., “Integrating multiband photogrammetry, scanning, and GPR for built heritage surveys: the façades of Castello del Valentino”, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 8, pp. 1-8, 2021, doi: 10.5194/isprs-annals-VIII-M-1-2021-1-2021.
  • [18] M. Cozzolino, A. Di Meo, and V. Gentile, “The contribution of indirect topographic surveys (photogrammetry and laser scanner) and GPR investigations in the study of the vulnerability of the Abbey of Santa Maria a Mare, Tremiti Islands (Italy)”, Annals of Geophysics, vol. 62, no. 3, 2019, doi: 10.4401/ag-7987.
  • [19] A. Elseicy, A. Alonso-Diaz, M. Solla, M. Rasol, and S. Santos-Assunçao, “Combined use of GPR and other NDTs for road pavement assessment: An overview”, Remote Sensing, vol. 14, no. 17, art. no. 4336, 2022, doi: 10.3390/rs14174336.
  • [20] J. Wolf, S. Discher, L. Masopust, S. Schulz, R. Richter, and J. Döllner, “Combined visual exploration of 2d ground radar and 3d point cloud data for road environments”, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 42, pp. 231-236, 2018, doi: 10.5194/isprs-archives-XLII-4-W10-231-2018.
  • [21] X. Niu, K. Yan, T. Zhang, Q. Zhang, H. Zhang, and J. Liu, “Quality evaluation of the pulse per second (PPS) signals from commercial GNSS receivers”, GPS Solutions, vol. 19, pp. 141-150, 2015, doi: 10.1007/s10291-014-0375-7.
  • [22] L.B. Ciampoli, A. Calvi, A. Di Benedetto, M. Fiani, and V. Gagliardi, “Ground Penetrating Radar (GPR) and Mobile Laser Scanner (MLS) technologies for non-destructive analysis of transport infrastructures”, in Earth Resources and Environmental Remote Sensing/GIS Applications XII. SPIE, 2021, pp. 166-174, doi: 10.1117/12.2599283.
  • [23] R. Di Maio, A. Emolo, A. Frisetti, et al., “Reconstruction of archaeological contexts through the integrated use of airborne LiDAR and geophysical survey: The case study of San Pietro Infine (Caserta, southern Italy)”, Journal of Archaeological Science: Reports, vol. 49, art. no. 104013, 2023, doi: 10.1016/j.jasrep.2023.104013.
  • [24] S. Lagüela, M. Solla, I. Puente, and F.J. Prego, “Joint use of GPR, IRT and TLS techniques for the integral damage detection in paving”, Construction and Building Materials, vol. 174, pp. 749-760, 2018, doi: 10.1016/j.conbuildmat.2018.04.159.
  • [25] Y. Zhou, Q. Hu, J. Zhang, P. Zhao, F. Yu, and M. Ai, “An Ground and Under-Ground Urban Roads Surveying Approach Using Integrated 3d LIDAR and 3D GPR Technology”, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 10, pp. 101-107, 2022, doi: 10.5194/isprs-annals-X-3-W2-2022-101-2022.
  • [26] T. Bicudo and I. Nakakura, “3D Models Integrating GPR and Apple LiDAR to Improve Results Visualization in Engineering and Geotechnical Applications”, in NSG2023 3rd Conference on Geophysics for Infrastructure Planning, Monitoring and BIM. 2023, pp. 1-5, doi: 10.3997/2214-4609.202320080.
  • [27] K. Bakuła, A. Lejzerowicz, M. Pilarska-Mazurek, et al., “Sensor integration and application of low-sized mobile mapping platform equipped with lidar, GPR and photogrammetric sensors”, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 43, p. 2022, doi: 10.5194/isprsarchives-xliii-b1-2022-167-2022.
  • [28] RadarTeam, “RadarTeam, Sweden”.
  • [29] W. Xu, Wei, and F. Zhang, “Fast-lio: A fast, robust lidar-inertial odometry package by tightly-coupled iterated kalman filter”, IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 3317-3324, 2021, doi: 10.1109/LRA.2021.3064227.
  • [30] M. Maślakowski, A. Lejzerowicz, G. Pacanowski, and R. Kuszyk, “The use of non-invasive ERT method to diagnose karst in road engineering in the Lublin Upland (Poland)”, Archives of Civil Engineering, vol. 70, no. 1, pp. 557-571, 2024, doi: 10.24425/ace.2024.148928.
  • [31] T. Godlewski, R. Mieszkowski, and M. Maślakowski, “From legend to discovery – historical and geotechnical conditions related to the discovery of tunnels under The Castle Hill in Szczecin”, Archives of Civil Engineering, vol. 69, no. 1, pp. 453-467, 2023, doi: 10.24425/ace.2023.144183.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-55bd6964-582f-4d74-a2f2-eed5cd5b1fb0
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