Automatic classification of point clouds obtained with different airborne sensors in UAV

William Benigno Barragán Zaque; Hugo Alexander Rondón Quintana; Wilmar Dario Fernandez

doi:10.1117/12.2533739

27 June 2019 Automatic classification of point clouds obtained with different airborne sensors in UAV

William Benigno Barragán Zaque, Hugo Alexander Rondón Quintana, Wilmar Dario Fernandez

Proceedings Volume 11174, Seventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2019); 1117415 (2019) https://doi.org/10.1117/12.2533739
Event: Seventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2019), 2019, Paphos, Cyprus

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.

Citation Download Citation

William Benigno Barragán Zaque, Hugo Alexander Rondón Quintana, and Wilmar Dario Fernandez "Automatic classification of point clouds obtained with different airborne sensors in UAV", Proc. SPIE 11174, Seventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2019), 1117415 (27 June 2019); https://doi.org/10.1117/12.2533739

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KEYWORDS

Vegetation

Sensors

Data modeling

Buildings

3D modeling

Unmanned aerial vehicles

Cameras

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