EVALUATION OF PHOTOGRAMMETRIC PRODUCTS OF A KARST UNIT OBTAINED WITH A DRONE

Gonzalo Neftaly Gijón-Yescas, Héctor Estrada-Medina, Yameli Guadalupe Aguilar, Rubén Arturo Medina-Esquivel, Jorge Iván Euán-Ávila

Abstract


Background. The rapid technological development of drones has been used in different disciplines as a new tool for the collection of geospatial data. Depending on the application of geospatial data, users may not require high absolute precision and therefore the measurement error within the model (relative precision) may be more important. Objective. To determine the root mean square error and the relative precision of the orthomosaics and digital elevation models at different heights generated with the SfM photogrammetric technique and a drone, over a sinkhole located in the Cenote Ring in the state of Yucatán. Methodology. Aerial images were acquired with a DJI Phantom 4 drone over a sinkhole at two heights, 80 and 100 m. Subsequently, the aerial images were processed obtaining digital elevation models (DEM) and orthomosaic with which the root mean squared error (RMSE) of the UTM coordinates (x, y) and elevations (z) was calculated. Finally, the relative precision was calculated by comparing the measurements in the field with those obtained in the DEMs and orthomosaics. Results. Flights at 100 m altitude showed the least variation in coordinates and elevations compared to flights at 80 m. The highest relative precision was recorded at 100 m high in the orthomosaics and ranged from 0.03 to 0.36 m with an average value of 0.22 m. Implications. With these results we can affirm that it is possible to carry out studies without control points in applications where a consistent and centimeter precision is not required. Conclusion. The 100 m high flights had the lowest RMSE and the highest relative accuracy.

Keywords


Relative precision; root mean squared error; digital elevation models; orthomosaic

Full Text:

PDF


URN: http://www.revista.ccba.uady.mx/urn:ISSN:1870-0462-tsaes.v24i1.36130



Copyright (c) 2021 Yameli Guadalupe Aguilar, Gonzalo Neftaly Gijón-Yescas, Héctor Estrada-Medina, Rubén Arturo Medina-Esquivel, Jorge Iván Euán-Ávila

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.