SavedAdd your journal

Journals / International Journal of Engineering and Geosciences / 2017 / Cilt: 2 - Sayı: 3

Evaluation of accuracy of DEMs obtained from uav-point clouds for different topographical areas

Alper AKAR
Pages
110–117
Publication Date
2022-10-19
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

After observing with the Shapiro- Wilk test that the data has a normal distribution, it was statistically determined through the parametric ANOVA: Friedman test that there is no difference between the variables.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The main objective of the study was to examine accuracies of DEMs (Digital Elevation Models) with different topographical structures generated by using the Unmanned Aerial Vehicle (UAV) point clouds.
📊
Key Findings & Data:Two different terrains with flat and sloping topographical structures were selected for the study, and DEMs of these terrains were generated using eight interpolation techniques (Kriging, Natural Neighbor, Radial Basis Function Triangulation with Linear interpolation, Nearest Neighbor, Invers Distance to a Power, Local Polynomial and Minimum Curvature).
💡
Conclusion & Impact:After observing with the Shapiro- Wilk test that the data has a normal distribution, it was statistically determined through the parametric ANOVA: Friedman test that there is no difference between the variables.
🔬Design:Survey & Empirical Study
📍Scope:Comprehensive Sample
⚙️Variables:Digital Elevation Model · Unmanned Aerial Vehicles · Kriging

Abstract

The main objective of the study was to examine accuracies of DEMs (Digital Elevation Models) with different topographical structures generated by using the Unmanned Aerial Vehicle (UAV) point clouds. Two different terrains with flat and sloping topographical structures were selected for the study, and DEMs of these terrains were generated using eight interpolation techniques (Kriging, Natural Neighbor, Radial Basis Function Triangulation with Linear interpolation, Nearest Neighbor, Invers Distance to a Power, Local Polynomial and Minimum Curvature). The accuracies of DEMs were tested by calculating the statistic methods with the help of the control points obtained by land surveying techniques. At the end of the study, it was observed that in DEMs prepared for both flat (study area 1) and sloping (study area 2) terrains, Kriging interpolation method yields the best results as study area 1 and 2, respectively. In addition, the results were examined using Shapiro-Wilk and ANOVA: Friedman tests. After observing with the Shapiro- Wilk test that the data has a normal distribution, it was statistically determined through the parametric ANOVA: Friedman test that there is no difference between the variables.

🔖

Cite This Article

AKAR, A. (2022). Evaluation of accuracy of DEMs obtained from uav-point clouds for different topographical areas. International Journal of Engineering and Geosciences, Cilt: 2 - Sayı: 3, 110–117. https://ajindex.com/articles/540755

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (11)

  1. Jain, S.K. and Singh, V.P., 2003. Water Resources Systems Planning and Management.Fist ed. Elsevier, Amsterdam. Honghai, Q.I. and Altinakar, M.S., 2011. A GIS-based decision support system for integrated flood management under uncertainty with two dimensional numerical simulations. Environmental Modelling and Software, 26 (6), 817–821.
  2. Ramlal, B. and Baban, S., 2008. Developing a GIS based integrated approach to flood management in Trinidad. West Indies, Journal of Environmental Management, 88 (4), 1131-1140.
  3. Spark, R.N. and Williams, P.F., 1996. Digital Terrain Models and the visualization of structural geology, Computer Methods in the Geosciences, 15, 421–446.
  4. Januchowski, S.R., Pressey, R.L., Van Der Wal, J. and Edwards, A., 2010. Characterizing errors in digital elevation models and estimating the financial costs of accuracy. International Journal of Geographical Information Science, 24 (9), 1327–1347.
  5. Hohle, J., 2009. DEM generation using a digital large format frame camera. Photogrammetric Engineering and Remote Sensing, 75 (1), 87–93.
  6. Kraus, K., 2007. Photogrammetry - Geometry from Images and Laser Scans, Walter de Gruyter, Goettingen, Germany, p. 459. Vosselman, G. and Maas, H.G., 2010. Airborne and Terrestrial Laser Scanning. CRC: Boca Raton, FL, USA, p. 318. Arun, P.V., 2013. A comparative analysis of different DEM interpolation methods. Geodesy and Cartography, 39 (4), 171-177.
  7. Wilson, J.P., Gallant, J.C., 2000. Secondary Topographic Attribute. in: Wilson, J.P.,Gallant, J.C. (Eds.), Terrain Analysis: Principles and Applications, John Wiley andSons., New York, pp. 87–131.
  8. Uysal, M., Toprak, A.S. and Polat, N., 2015. DEM generation with UAV photogrammetry and accuracy analysis in Sahitler Hill, Measurement, 73, 539-543.
  9. Remondino, F., Barazzetti, L., Nex, F., Scaioni, M. and Sarazzi, D., 2011. UAV Photogrammetry for mapping and 3D modelling current status and future perspectives. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVIII-1- C22, pp. 25-31. Ruzgienė, B., Berteška, T., Gečyte, S., Jakubauskienė, E. and Aksamitauskas, V.Č., 2015. The surface modelling based on UAV photogrammetry and qualitativeestimation. Measurement, 73, 619–627.
  10. Mesas-Carrascosa, F.J., Notario-García, M.D., de Larriva, J.E.M., de la Orden, M.S. and Porras, A.G.F., 2014. Validation of measurements of land plot area using UAV imagery. International Journal of Applied Earth Observation and Geoinformation, 33, 270–279.
  11. Austin, R.