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Ingeniería agrícola y biosistemas
On-line version ISSN 2007-4026Print version ISSN 2007-3925
Abstract
JIMENEZ-JIMENEZ, Sergio Iván et al. Quantification of the error of digital terrain models derived from images acquired with UAV. Ing. agric. biosist. [online]. 2017, vol.9, n.2, pp.85-100. Epub Aug 28, 2020. ISSN 2007-4026. https://doi.org/10.5154/r.inagbi.2017.03.007.
Introduction:
Topographic surveys based on traditional methods (total stations and GPS) enable representing in detail the characteristics of the terrestrial surface, but they mean a high cost in terms of resources and time. With the use of unmanned aerial vehicles (UAVs) it is possible to obtain digital terrain models (DTMs) with high spatial resolution, but they require field validation to obtain high-accuracy topographic products.
Objective:
To estimate the precision of DTMs generated from high-resolution images acquired with a UAV by means of the geolocation of 23 terrestrial points (11 control and 12 verification ones) obtained in the field with a GPS-RTK (Global Positioning System - Real Time Kinematic).
Materials and methods:
For the generation of each DTM, a photogrammetric restitution process with a different number of Ground Control Points (GCPs) was used: 4, 5, 6, 8, 9, 10 and 11. To evaluate the precision of the DTMs, four statistical parameters were used.
Results and discussion:
The DTM processed with four points had a root-mean-square error (RMSE) > 3 m, and those of 9, 10 and 11 had an RMSE < 7 cm. The georeferenced DTM with 11 GCPs represented the topography of the site with better accuracy. The largest RMSE was 5.9 cm, which is less than three times the spatial resolution of the orthomosaic (2 cm·pixel-1).
Conclusions:
At least five terrestrial GCPs are well distributed throughout the study area for every 15 ha of surveyed area; in addition, it is necessary to add one point for each additional 3 ha to obtain a minimum accuracy of 6 cm on the Z axis and 7 cm on the plane (X, Y, Z).
Keywords : photogrammetry; high resolution topography; Ground Control Points; point clouds; flight plan; drone.