Version 1
: Received: 26 August 2019 / Approved: 27 August 2019 / Online: 27 August 2019 (10:40:49 CEST)
How to cite:
Agüera-Vega, F.; Agüera-Puntas, M.; Mancini, F.; Martínez-Carricondo, P.; Carvajal-Ramírez, F. Effects of Structure from Motion Data Density, Interpolation Method and Grid Size on Micro Topography Digital Terrain Model Accuracy. Preprints2019, 2019080283. https://doi.org/10.20944/preprints201908.0283.v1
Agüera-Vega, F.; Agüera-Puntas, M.; Mancini, F.; Martínez-Carricondo, P.; Carvajal-Ramírez, F. Effects of Structure from Motion Data Density, Interpolation Method and Grid Size on Micro Topography Digital Terrain Model Accuracy. Preprints 2019, 2019080283. https://doi.org/10.20944/preprints201908.0283.v1
Agüera-Vega, F.; Agüera-Puntas, M.; Mancini, F.; Martínez-Carricondo, P.; Carvajal-Ramírez, F. Effects of Structure from Motion Data Density, Interpolation Method and Grid Size on Micro Topography Digital Terrain Model Accuracy. Preprints2019, 2019080283. https://doi.org/10.20944/preprints201908.0283.v1
APA Style
Agüera-Vega, F., Agüera-Puntas, M., Mancini, F., Martínez-Carricondo, P., & Carvajal-Ramírez, F. (2019). Effects of Structure from Motion Data Density, Interpolation Method and Grid Size on Micro Topography Digital Terrain Model Accuracy. Preprints. https://doi.org/10.20944/preprints201908.0283.v1
Chicago/Turabian Style
Agüera-Vega, F., Patricio Martínez-Carricondo and Fernando Carvajal-Ramírez. 2019 "Effects of Structure from Motion Data Density, Interpolation Method and Grid Size on Micro Topography Digital Terrain Model Accuracy" Preprints. https://doi.org/10.20944/preprints201908.0283.v1
Abstract
The objective of this study is to evaluate the effects of the 3D point cloud density derived from unmanned aerial vehicle (UAV) photogrammetry and structure from motion (SfM) and multi-view stereopsis (MVS) techniques, the interpolation method for generating a digital terrain model (DTM), and the resolution (grid size) of the derived DTM on the accuracy of estimated heights in small areas, where a very accurate high spatial resolution is required. A UAV-photogrammetry project was carried out on a bare soil of 13 × 13 m with a rotatory wing UAV at 10 m flight altitude (equivalent ground sample distance = 0.4 cm). The 3D point cloud was derived, and five sample replications representing 1, 2, 3, 4, 5, 10, 15, 20, 30, 40, 50, 60, 70, 80 and 90% of the original cloud were extracted to analyze the effect of cloud density on DTM accuracy. For each of these samples, DTMs were derived using four different interpolation methods (Inverse Distance Weighted (IDW), Multiquadric Radial Basis Function (MRBF), Kriging (KR), and Triangulation with Linear Interpolation (TLI)) and 15 DTM grid size (GS) values (20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0.67, 0.5, and 0.4 cm). Then, 675 DTMs were analyzed. The results showed, for each interpolation method and each density, an optimal GS value (most of the cases equal to 1 cm) for which the Root Mean Square Error (RMSE) is minimum. IDW was the interpolator which yielded best accuracies for all combination of densities and GS. Its RMSE, considering the raw cloud, was 1.054 cm. The RMSE increased 3% when a point cloud with 80% extracted from the raw cloud was used to generate the DTM. When the point cloud included the 40% of the raw cloud, RMSE increased 5%. For densities lower than 15%, RMSE increased exponentially (45% for 1% of raw cloud). The grid size minimizing RMSE for densities of 20% or higher was 1 cm, which represents 2.5 times the ground sample distance of the pictures used for developing the photogrammetry project.
Keywords
UAV-photogrammetry; digital surface model; Structure from Motion; microtopography
Subject
Environmental and Earth Sciences, Environmental Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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