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Automatic classification of point clouds obtained with different airborne sensors in UAV
Author(s): William Benigno Barragán Zaque; Hugo Alexander Rondón Quintana; Wilmar Dario Fernandez
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Paper Abstract

One of the main objectives when compiling information from drones, is the generation of digital terrain models - DTM, which are what ultimately allow the creation of cartographic products reliably, efficiently, accurately, economically and quickly. In the present work, information obtained in Colombia is used in 3 types of terrain, with different varying conditions and characteristics. The data is taken with 2 different sensors, located in 2 fixed-wing drones (X8 skywalker with Sony Alpha camera a6000 24MP and UAVER Avian P with Sony RX1R II 42 MP). Information processing was performed and point clouds were obtained about the same area for executing a comparative iterative analysis, and obtaining the optimal parameters of: iteration angle, slope and distance of terrain iteration. A semiautomatic classification of point clouds was used, with 4 different treatments proposed by the authors, called classification MACROS and different DTM was generated. To analyze the behavior of the point clouds and check the accuracy, a control of dimensions in the field was made, the land was divided into 12 plots and the difference in elevation was calculated with a cloud of checkpoints, obtained manually. Finally, a completely randomized block experiment model is designed, created and tested.

Paper Details

Date Published: 27 June 2019
PDF: 14 pages
Proc. SPIE 11174, Seventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2019), 1117415 (27 June 2019); doi: 10.1117/12.2533739
Show Author Affiliations
William Benigno Barragán Zaque, Univ. Distrital Francisco José de Caldas (Colombia)
Hugo Alexander Rondón Quintana, Univ. Distrital Francisco José de Caldas (Colombia)
Wilmar Dario Fernandez, Univ. Distrital Francisco José de Caldas (Colombia)


Published in SPIE Proceedings Vol. 11174:
Seventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2019)
Kyriacos Themistocleous; Giorgos Papadavid; Silas Michaelides; Vincent Ambrosia; Diofantos G. Hadjimitsis, Editor(s)

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