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The assessment of elevation data consistency : A case study using the ALS and georeference database in the City of Kraków

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The integration of geodetic and photogrammetric data has become a new tool that has expanded the existing measurement capabilities, as well as it found its application outside the geodetic sector. As a result, over the past decades, the process of topographic data acquisition has caused cartographic industry to move from classical surveying methods to passive and active detection methods. The introduction of remote sensing technology has not only improved the speed of data acquisition but has also provided elevation data for areas that are difficult to access and survey. The aim of the work is to analyse consistency of elevation data from the Georeference Database of Topographic Objects (Pol. Baza danych obiektów topograficznych - BDOT500) with data from airborne laser scanning (ALS) for selected 15 research areas located in the City of Kraków. The main findings reveal discrepancies between elevation data sources, potentially affecting the accuracy of various applications, such as flood risk assessment, urban planning, and environmental management. The research gap identified in the study might stem from the lack of comprehensive investigations into the consistency and accuracy of elevation data across different databases and technologies in urban areas. This gap highlights the need for a thorough examination of the reliability of various data sources and methods of urban planning, disaster management, and environmental analysis. The integration of diverse databases and technologies, like ALS and geodetic measurements, in various applications introduces potential discrepancies that can significantly impact decision-making and outcomes.
Wydawca
Rocznik
Tom
Strony
135--144
Opis fizyczny
Bibliogr. 31 poz., rys., tab., wykr.
Twórcy
  • University of Agriculture in Krakow, Faculty of Environmental Engineering and Land Surveying, al. Adama Mickiewicza 21, 31-120 Kraków, Poland
  • University of Agriculture in Krakow, Faculty of Environmental Engineering and Land Surveying, al. Adama Mickiewicza 21, 31-120 Kraków, Poland
  • Slovak University of Agriculture in Nitra, Faculty of Horticulture and Landscape Engineering, Department of Landscape Planning and Ground Consolidation, 949 76 Nitra, Slovak Republic
  • University of Agriculture in Krakow, Faculty of Environmental Engineering and Land Surveying, al. Adama Mickiewicza 21, 31-120 Kraków, Poland
Bibliografia
  • Ackermann, F. (1999) “Airborne laser scanning – present status and future expectations,” ISPRS Journal of Photogrammetry and Remote Sensing, 54, pp. 64–67. Available at: https://doi.org/10.1016/S0924-2716(99)00009-X.
  • Ali-Sisto, D. et al. (2020) “A method for vertical adjustment of digital aerial photogrammetry data by using a high-quality digital terrain model,” International Journal of Applied Earth Observation and Geoinformation, 84, 101954. Available at: https://doi.org/10.1016/j.jag.2019.101954.
  • Bac-Bronowicz, J. et al. (2015) “Harmonizacja modeli pojęciowych BDOT10k i BDOT500 w kontekście wymiany danych [Harmonization of conceptual models of the reference databases BDOT10k and BDOT500 considering data exchange],” Polskie Towarzystwo Informacji Przestrzennej Roczniki Geomatyki, 13, 4(70), pp. 295–305. Available at: http://rg.ptip.org.pl/index.php/rg/article/view/RG2015-4-Bac-Bronowicz-inni (Accessed: June 10, 2023).
  • Bartmiński, P., Siłuch, M. and Kociuba, W. (2023) “The effectiveness of a UAV-based LIDAR survey to develop digital terrain models and topographic texture analyses,” Sensors, 23(14), 6415. Available at: https://doi.org/10.3390/s23146415.
  • Baszkiewicz, K. et al. (2014) “Wykorzystanie danych z lotniczego skanowania laserowego w zarządzaniu zagrożeniem powodziowym [The use of LIDAR data in the flood emergency management],” Logistyka, 5, pp. 68–84.
  • Cãţeanu, M. and Ciubotaru, A. (2020) “Accuracy of ground surface interpolation from airborne laser scanning (ALS) data in dense forest cover,” ISPRS International Journal of Geo-Information, 9(4), 224. Available at: https://doi.org/10.3390/ijgi9040224.
  • Doskocz, A. (2016) “The current state of the creation and modernization of national geodetic and cartographic resources in Poland,” Open Geosciences, 8(1). Available at: ttps://doi.org/10.1515/geo2016-0059.
  • Doskocz, A. and Lewandowicz, E. (2022) “Modyfikacja i integracja danych przestrzennych pozyskanych z różnych źródeł w celu wykonywania analiz przestrzennych oraz opracowywania modeli 3D budynków [Modification and integration of spatial data obtained from various sources in order to perform spatial analyses and develop 3D models of buildings]," Builder, 5(298), pp. 30–35. Available at: https://doi.org/10.5604/01.3001.0015.8331.
  • Estornell, J. et al. (2011) “Analysis of the factors affecting LiDAR DTM accuracy in a steep shrub area,” International Journal of Digital Earth, 4(6), pp. 522–538. Available at: https://doi.org/10.1080/17538947.2010.533201.
  • Forkuo, E.K. (2008) “Digital terrain modeling in a GIS environment,” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37, B2, Beijing, pp. 1023–1030.
  • Hyyppä, J. et al. (2000) “Elevation accuracy of laser scanning derived digital terrain and target models in forest environment,” in Proceedings of EARSeL-SIG-Workshop LIDAR. Dresden/FRG, June 14–17, 2000. Strasbourg: European Association of Remote Sensing Laboratories (EARSel), pp. 139–147.
  • Hyyppä, J. et al. (2005) “Using individual tree crown approach for forest volume extraction with aerial images and laser point clouds,” ISPRS WG III/3, III/4, V/3 Workshop “Laser scanning 2005”, pp. 144–149. Enschede, the Netherlands, September 12–14, 2005.
  • Inglot, A. and Kozioł, K. (2016) “The importance of contextual topology in the process of harmonization of the spatial databases on example BDOT500,” Baltic Geodetic Congress (Geomatics). Gdansk University of Technology, 2–4 June 2016 Poland. Available at: https://doi.org/10.1109/BGC.Geomatics.2016.52.
  • Kurczyński, Z. and Bakula, K. (2013) “Generowanie referencyjnego numerycznego modelu terenu o zasięgu krajowym w oparciu o lotnicze skanowanie laserowe w projekcie ISOK [Generation of countrywide reference digital terrain model from airborne laser scannig in ISOK project],” Archiwum Fotogrametrii, Kartografii i Teledetekcji, wydanie specjalne: Monografia „Geodezyjne Technologie Pomiarowe”, pp. 59–68.
  • Lê, H.-A. et al. (2022) “Learning digital terrain models from point clouds: ALS2DTM dataset and rasterization-based gan,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, pp. 4980–4989. Available at: https://doi.org/10.1109/jstars.2022.3182030.
  • Liang, F. et al. (2020) “A novel skyline context descriptor for rapid localization of terrestrial laser scans to airborne laser scanning point clouds,” ISPRS Journal of Photogrammetry and Remote Sensing, 165, pp. 120–132. Available at: https://doi.org/10.1016/j.isprsjprs.2020.04.018.
  • Maciąg, K., Leń, P. and Maciąg, M. (2022) “Badanie lokalnej zgodności ogólnodostępnych danych LiDAR z danymi bazy BDOT500 z zastosowaniem technik GIS [Analysis of the local agreement between the LiDAR data and the BDOT500 database using the GIS techniques],” Przegląd Geodezyjny, 94(2), pp. 13–16. Available at: https://doi.org/10.15199/50.2022.2.2.
  • Mikrut, S. and Głowienka E. (eds.) (2015) Fotogrametria i skaning laserowy w modelowaniu 3D [Photogrammetry and the laser scanning in the 3D modelling]. Rzeszów: Wyższa Szkoła Inżynieryjno-Ekonomiczna z siedzibą w Rzeszowie.
  • Morsdorf, F. et al. (2003) “The potential of high resolution airborne laser scanning for deriving geometric properties of single trees,” in EGS – AGU – EUG Joint Assembly. Nice, France, 06–11 April 2003. Munich: European Geophysical Society.
  • Nurunnabi, A. et al. (2021) “An efficient deep learning approach for ground point filtering in aerial laser scanning point clouds,” International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 43, pp. 31–38. Available at: https://doi.org/10.5194/isprs-archives-XLIII-B1-2021-31-2021.
  • Okolie, Ch.J. and Smit, J.L. (2022) “A systematic review and meta-analysis of Digital Elevation Model (DEM) fusion: Pre-processing, methods and applications,” ISPRS Journal of Photogrammetry and Remote Sensing, 188, pp. 1–29. Available at: https://doi.org/10.1016/j.isprsjprs.2022.03.016.
  • Ouzahar, F. et al. (2018) “The contribution of remote sensing in hydraulics and hydrology, analysis and evaluation of digital terrain model for flood risk mapping,” Journal of Water and Land Development, 39, pp. 17–26. Available at: https://doi.org/10.2478/jwld-2018-0055.
  • Pitkänen, J., Maltamo, M. and Hyyppä, J. (2004) “Adaptive methods for individual tree detection on airborne laser based canopy height model,” International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 36, 8/W2, pp. 187–191. Available at: https://www.isprs.org/proceedings/xxxvi/8-w2/PITKAENEN.pdf (Accessed: June 05, 2023).
  • Polidori, L. and Hage, M.E. (2022) “Digital Elevation Model quality assessment methods: A critical review,” Remote Sensing, 12(21), 3522. Available at: https://doi.org/10.3390/rs12213522.
  • Sefercik, U.G. et al. (2016) “Point-based and model-based geolocation analysis of airborne laser scanning data,” Optical Engineering, 56 (1), 013101. Available at: https://doi.org/10.1117/1.oe.56.1.013101.
  • Shan, J. and Toth, C.K. (2009) Topographic laser ranging and scanning: Principles and processing. Portland: CRC Taylor & Francis. Available at: https://doi.org/10.1201/9781420051438.
  • Ślusarski, M. (2015) “BDOT500 database of physical topographic objects basic qualitative analysis,” Geomatics, Landmanagement and Landscape, 1, pp. 69–75. Available at: https://doi.org/10.15576/GLL/2015.1.69.
  • Ślusarski, M. (2017) “Metody i modele oceny jakości danych przestrzennych [Methods and models of spatial data quality assessment],” Zeszyty Naukowe Uniwersytetu Rolniczego im. Hugona Kołłątaja w Krakowie, 537. Rozprawy, 414. Kraków: Wydawnictwo Uniwersytetu Rolniczego w Krakowie.
  • Song, J.H., Han, S.H. and Kim, Y.I. (2002) “Assessing the possibility of land-cover classification using LiDAR intensity data,” International Archives of Photogrammetry and Remote Sensing, 34, 3B, pp. 259–262. Available at: https://citeseerx.ist.psu.edu/viewdoc/download?rep=rep1&type=pdf&doi=10.1.1.222.4122 (Accessed: June 10, 2023).
  • Weinacker, H. et al. (2004) “Development of filtering, segmentation and modelling modules for LiDAR and multispectral data as a fundament of an automatic forest inventory system,” International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 36, 8/W2.
  • Wojak, S., Strużyński, A. and Wyrębek, M. (2023) “Analiza zmian parametrów hydraulicznych w rzece nizinnej przy zastosowaniu modelowania numerycznego [Analysis of changes in hydraulic parameters in lowland river using numerical modelling],” Acta Scientiarum Polonorum, Formatio Circumiectus, 22(1), pp. 3–17. Available at: https://doi.org/10.15576/ASP.FC/2023.22.1.3.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6997ea07-2553-4935-b81a-b6c118de0f76
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