Research Article
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Automatic Building Vectorization from Photogrammetric Point Clouds for GIS-based Spatial Analysis

Year 2024, Volume: 11 Issue: 4, 10 - 16, 25.12.2024

Abstract

Photogrammetry has played an important role in creating visually interesting three-dimensional (3D) models thanks to unmanned aerial vehicle (UAV) images in recent years. Photogrammetry and GIS are widely used together to produce and analyze 3D models. This study successfully produced 3D models of buildings using photogrammetry and transferred them to GIS for analysis. UAVs were utilized to capture images, which were then processed to generate a dense point cloud. The point cloud was classified using rule-based classification. Buildings were vectorized and textured, and the resulting models were analyzed in ArcGIS Pro software. The study achieved a high accuracy in the classification process and automatic vectorization. The use of UAVs expedited data collection and improved data quality, while the detailed analysis of the point enabled precise analysis for many applications such as urban planning and land management. The integration of building models into GIS facilitated more accurate and efficient work processes.

References

  • Ahmad, A., Rabiu, L. (2011, March). Generation of three dimensional model of building using photogrammetric technique. In 2011 IEEE 7th International Colloquium on Signal Processing and its Applications (pp. 225-231). IEEE.
  • Aljumaily, H., Laefer, D. F., Cuadra, D., Velasco, M. (2023). Point cloud voxel classification of aerial urban LiDAR using voxel attributes and random forest approach. International Journal of Applied Earth Observation and Geoinformation, 118, 103208.
  • Atik, M. E., Duran, Z., Seker, D. Z. (2021). Machine learning-based supervised classification of point clouds using multiscale geometric features. ISPRS International Journal of Geo-Information, 10(3), 187.
  • Atik, M. E., Duran, Z., Seker, D. Z. (2024). Explainable Artificial Intelligence for Machine Learning-Based Photogrammetric Point Cloud Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
  • Büyüksalih, İ., Alkan, M., Gazioğlu, C. G. (2019). Design for 3D city model management using remote sensing and GIS: A case study for the Golden Horn in İstanbul, Turkey. Sigma Journal of Engineering andNatural Sciences, 37(4), 1450-1466.
  • Chen, L., Zhao, S., Han, W., Li, Y. (2012). Building detection in an urban area using lidar data and QuickBird imagery. International Journal ofRemote Sensing, 33(16), 5135-5148.
  • Chen, M., Feng, A., McAlinden, R., Soibelman, L. (2020). Photogrammetric point cloud segmentation and object information extraction for creating virtual environments and simulations. Journal of Management in Engineering, 36(2), 04019046.
  • Duran, Z., Ozcan, K., Atik, M. E. Classification of photogrammetric and airborne LiDAR point clouds using machine learning algorithms. Drones 2021, 5,104.
  • Haithcoat, T. L., Song, W., Hipple, J. D. (2022, November). Building footprint extraction and 3-D reconstruction from LIDAR data. In IEEE/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas (Cat. No. 01EX482) (pp. 74-78). IEEE.
  • Huang, J., Stoter, J., Peters, R., Nan, L. (2022). City3D: Large-scale building reconstruction from airborne LiDAR point clouds. Remote Sensing, 14(9), 2254.
  • Kang, T. (2023). Scan to BIM mapping process description for building representation in 3D GIS. Applied Sciences, 13(17), 9986.
  • Karsli, B., Yilmazturk, F., Bahadir, M., Karsli, F., Ozdemir, E. (2024). Automatic building footprint extraction from photogrammetric and LiDAR point clouds using a novel Improved-Octree approach. Journal ofBuilding Engineering, 82, 108281.
  • Leick, A. (2004). GPS Satellite Surveying (3rd ed.). Wiley.
  • Limandal, Y. P. (2019). Dijital Hava Görüntülerinden Üretilen Nokta Bulutu İle Yarı Otomatik Bina Detayı Çıkarımı (Yüksek Lisans Tezi, Karadeniz Teknik Üniversitesi Fen Bilimleri Enstitüsü Harita Mühendisliği Ana Bilim Dalı).
  • Lu, S., Li, H., Li, C. (2019). A review of the applications of 3D LiDAR and 3D point cloud processing in urban environment. ISPRS International Journal of Geo-Information, 8(3), 116.
  • Nys, G. A., Billen, R., Poux, F. (2020). Automatic 3d buildings compact reconstruction from LiDAR point clouds. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 43, 473-478.
  • Park, Y., Guldmann, J. M. (2019). Creating 3D city models with building footprints and LIDAR point cloud classification: A machine learning approach. Computers, environment and urban systems, 75, 7689.
  • Pellerin Le Bas, X., Froideval, L., Mouko, A., Conessa, C., Benoit, L., Perez, L. (2024). A New Open-Source Software to Help Design Models for Automatic 3D Point Cloud Classification in Coastal Studies. Remote Sensing, 16(16), 2891.
  • Sharma, M., Garg, R. D. (2023). Building footprint extraction from aerial photogrammetric point cloud data using its geometric features. Journal ofBuilding Engineering, 76, 107387.
  • Sirmacek, B., Gulec, O. (2017). Hierarchical approach for automatic detection and segmentation of buildings in complex urban areas using airborne LiDAR data and aerial imagery. ISPRS International Journal of Geo-Information, 6(1), 16.
  • Smith, J., Johnson, A. B., Williams, C. D. (2021). Integration of Terrestrial Laser Scanning and RealTime Kinematic GNSS for Structural Monitoring of Bridges. Sensors, 21(4), 1234-1256. doi:10.3390/s21041234
  • Wang, D., Loo, J. F. C., Chen, J., Yam, Y., Chen, S. C., He, H., ... Ho, H. P. (2019). Recent advances in surface plasmon resonance imaging sensors. Sensors, 19(6), 1266.
  • Westoby, M. J., Brasington, J., Glasser, N. F., Hambrey, M. J., Reynolds, J. M. (2012). ‘Structure-from-Motion’photogrammetry: A low-cost, effective tool for geoscience applications. Geomorphology, 179, 300-314.
  • Widyaningrum, E., Gorte, B., Lindenbergh, R. (2019). Automatic building outline extraction from ALS point clouds by ordered points aided hough transform. Remote Sensing, 11(14), 1727.
  • Yanalak, M. (2002). Interpolation with Direction And Inverse Distance Weighted Average. Map Journal, 127(5). Yildirim, D., Büyüksalih, G., Şahin, A. D. (2021). Rooftop photovoltaic potential in Istanbul: Calculations based on LiDAR data, measurements and verifications. Applied Energy, 304, 117743.
  • Zhang, S., Han, F., Bogus, S. M. (2020, November). Building Footprint and Height Information Extraction from Airborne LiDAR and Aerial Imagery. In Construction Research Congress 2020: Computer Applications (pp. 326-335). Reston, VA: American Society of Civil Engineers.
Year 2024, Volume: 11 Issue: 4, 10 - 16, 25.12.2024

Abstract

References

  • Ahmad, A., Rabiu, L. (2011, March). Generation of three dimensional model of building using photogrammetric technique. In 2011 IEEE 7th International Colloquium on Signal Processing and its Applications (pp. 225-231). IEEE.
  • Aljumaily, H., Laefer, D. F., Cuadra, D., Velasco, M. (2023). Point cloud voxel classification of aerial urban LiDAR using voxel attributes and random forest approach. International Journal of Applied Earth Observation and Geoinformation, 118, 103208.
  • Atik, M. E., Duran, Z., Seker, D. Z. (2021). Machine learning-based supervised classification of point clouds using multiscale geometric features. ISPRS International Journal of Geo-Information, 10(3), 187.
  • Atik, M. E., Duran, Z., Seker, D. Z. (2024). Explainable Artificial Intelligence for Machine Learning-Based Photogrammetric Point Cloud Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
  • Büyüksalih, İ., Alkan, M., Gazioğlu, C. G. (2019). Design for 3D city model management using remote sensing and GIS: A case study for the Golden Horn in İstanbul, Turkey. Sigma Journal of Engineering andNatural Sciences, 37(4), 1450-1466.
  • Chen, L., Zhao, S., Han, W., Li, Y. (2012). Building detection in an urban area using lidar data and QuickBird imagery. International Journal ofRemote Sensing, 33(16), 5135-5148.
  • Chen, M., Feng, A., McAlinden, R., Soibelman, L. (2020). Photogrammetric point cloud segmentation and object information extraction for creating virtual environments and simulations. Journal of Management in Engineering, 36(2), 04019046.
  • Duran, Z., Ozcan, K., Atik, M. E. Classification of photogrammetric and airborne LiDAR point clouds using machine learning algorithms. Drones 2021, 5,104.
  • Haithcoat, T. L., Song, W., Hipple, J. D. (2022, November). Building footprint extraction and 3-D reconstruction from LIDAR data. In IEEE/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas (Cat. No. 01EX482) (pp. 74-78). IEEE.
  • Huang, J., Stoter, J., Peters, R., Nan, L. (2022). City3D: Large-scale building reconstruction from airborne LiDAR point clouds. Remote Sensing, 14(9), 2254.
  • Kang, T. (2023). Scan to BIM mapping process description for building representation in 3D GIS. Applied Sciences, 13(17), 9986.
  • Karsli, B., Yilmazturk, F., Bahadir, M., Karsli, F., Ozdemir, E. (2024). Automatic building footprint extraction from photogrammetric and LiDAR point clouds using a novel Improved-Octree approach. Journal ofBuilding Engineering, 82, 108281.
  • Leick, A. (2004). GPS Satellite Surveying (3rd ed.). Wiley.
  • Limandal, Y. P. (2019). Dijital Hava Görüntülerinden Üretilen Nokta Bulutu İle Yarı Otomatik Bina Detayı Çıkarımı (Yüksek Lisans Tezi, Karadeniz Teknik Üniversitesi Fen Bilimleri Enstitüsü Harita Mühendisliği Ana Bilim Dalı).
  • Lu, S., Li, H., Li, C. (2019). A review of the applications of 3D LiDAR and 3D point cloud processing in urban environment. ISPRS International Journal of Geo-Information, 8(3), 116.
  • Nys, G. A., Billen, R., Poux, F. (2020). Automatic 3d buildings compact reconstruction from LiDAR point clouds. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 43, 473-478.
  • Park, Y., Guldmann, J. M. (2019). Creating 3D city models with building footprints and LIDAR point cloud classification: A machine learning approach. Computers, environment and urban systems, 75, 7689.
  • Pellerin Le Bas, X., Froideval, L., Mouko, A., Conessa, C., Benoit, L., Perez, L. (2024). A New Open-Source Software to Help Design Models for Automatic 3D Point Cloud Classification in Coastal Studies. Remote Sensing, 16(16), 2891.
  • Sharma, M., Garg, R. D. (2023). Building footprint extraction from aerial photogrammetric point cloud data using its geometric features. Journal ofBuilding Engineering, 76, 107387.
  • Sirmacek, B., Gulec, O. (2017). Hierarchical approach for automatic detection and segmentation of buildings in complex urban areas using airborne LiDAR data and aerial imagery. ISPRS International Journal of Geo-Information, 6(1), 16.
  • Smith, J., Johnson, A. B., Williams, C. D. (2021). Integration of Terrestrial Laser Scanning and RealTime Kinematic GNSS for Structural Monitoring of Bridges. Sensors, 21(4), 1234-1256. doi:10.3390/s21041234
  • Wang, D., Loo, J. F. C., Chen, J., Yam, Y., Chen, S. C., He, H., ... Ho, H. P. (2019). Recent advances in surface plasmon resonance imaging sensors. Sensors, 19(6), 1266.
  • Westoby, M. J., Brasington, J., Glasser, N. F., Hambrey, M. J., Reynolds, J. M. (2012). ‘Structure-from-Motion’photogrammetry: A low-cost, effective tool for geoscience applications. Geomorphology, 179, 300-314.
  • Widyaningrum, E., Gorte, B., Lindenbergh, R. (2019). Automatic building outline extraction from ALS point clouds by ordered points aided hough transform. Remote Sensing, 11(14), 1727.
  • Yanalak, M. (2002). Interpolation with Direction And Inverse Distance Weighted Average. Map Journal, 127(5). Yildirim, D., Büyüksalih, G., Şahin, A. D. (2021). Rooftop photovoltaic potential in Istanbul: Calculations based on LiDAR data, measurements and verifications. Applied Energy, 304, 117743.
  • Zhang, S., Han, F., Bogus, S. M. (2020, November). Building Footprint and Height Information Extraction from Airborne LiDAR and Aerial Imagery. In Construction Research Congress 2020: Computer Applications (pp. 326-335). Reston, VA: American Society of Civil Engineers.
There are 26 citations in total.

Details

Primary Language English
Subjects Photogrammetry and Remote Sensing
Journal Section Research Articles
Authors

Tolga Bozkurt 0009-0003-8257-1244

Muhammed Enes Atik 0000-0003-2273-7751

Zaide Duran 0000-0002-1608-0119

Publication Date December 25, 2024
Submission Date June 22, 2024
Acceptance Date December 6, 2024
Published in Issue Year 2024 Volume: 11 Issue: 4

Cite

APA Bozkurt, T., Atik, M. E., & Duran, Z. (2024). Automatic Building Vectorization from Photogrammetric Point Clouds for GIS-based Spatial Analysis. International Journal of Environment and Geoinformatics, 11(4), 10-16.