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Sensors 2017, 17(12), 2703;

Designing and Testing a UAV Mapping System for Agricultural Field Surveying

Department of Engineering, Aarhus University, Finlandsgade 22, 8200 Aarhus N, Denmark
Department of Agroecology, Aarhus University, Forsøgsvej 1, 4200 Slagelse, Denmark
Author to whom correspondence should be addressed.
Received: 30 September 2017 / Revised: 9 November 2017 / Accepted: 13 November 2017 / Published: 23 November 2017
(This article belongs to the Special Issue UAV or Drones for Remote Sensing Applications)
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A Light Detection and Ranging (LiDAR) sensor mounted on an Unmanned Aerial Vehicle (UAV) can map the overflown environment in point clouds. Mapped canopy heights allow for the estimation of crop biomass in agriculture. The work presented in this paper contributes to sensory UAV setup design for mapping and textual analysis of agricultural fields. LiDAR data are combined with data from Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) sensors to conduct environment mapping for point clouds. The proposed method facilitates LiDAR recordings in an experimental winter wheat field. Crop height estimates ranging from 0.35–0.58 m are correlated to the applied nitrogen treatments of 0–300 kg N ha . The LiDAR point clouds are recorded, mapped, and analysed using the functionalities of the Robot Operating System (ROS) and the Point Cloud Library (PCL). Crop volume estimation is based on a voxel grid with a spatial resolution of 0.04 × 0.04 × 0.001 m. Two different flight patterns are evaluated at an altitude of 6 m to determine the impacts of the mapped LiDAR measurements on crop volume estimations.
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Keywords: aerial robotics; canopy estimation; crop monitoring; point cloud; winter wheat mapping aerial robotics; canopy estimation; crop monitoring; point cloud; winter wheat mapping

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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 (CC BY 4.0).

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Christiansen, M.P.; Laursen, M.S.; Jørgensen, R.N.; Skovsen, S.; Gislum, R. Designing and Testing a UAV Mapping System for Agricultural Field Surveying. Sensors 2017, 17, 2703.

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