title: Configuration and specifications of an Unmanned Aerial Vehicle (UAV) for early site specific weed management.
abstract: A new aerial platform has risen recently for image acquisition, the Unmanned Aerial Vehicle (UAV). This article describes the technical specifications and configuration of a UAV used to capture remote images for early season site- specific weed management (ESSWM). Image spatial and spectral properties required for weed seedling discrimination were also evaluated. Two different sensors, a still visible camera and a six-band multispectral camera, and three flight altitudes (30, 60 and 100 m) were tested over a naturally infested sunflower field. The main phases of the UAV workflow were the following: 1) mission planning, 2) UAV flight and image acquisition, and 3) image pre-processing. Three different aspects were needed to plan the route: flight area, camera specifications and UAV tasks. The pre-processing phase included the correct alignment of the six bands of the multispectral imagery and the orthorectification and mosaicking of the individual images captured in each flight. The image pixel size, area covered by each image and flight timing were very sensitive to flight altitude. At a lower altitude, the UAV captured images of finer spatial resolution, although the number of images needed to cover the whole field may be a limiting factor due to the energy required for a greater flight length and computational requirements for the further mosaicking process. Spectral differences between weeds, crop and bare soil were significant in the vegetation indices studied (Excess Green Index, Normalised Green-Red Difference Index and Normalised Difference Vegetation Index), mainly at a 30 m altitude. However, greater spectral separability was obtained between vegetation and bare soil with the index NDVI. These results suggest that an agreement among spectral and spatial resolutions is needed to optimise the flight mission according to every agronomical objective as affected by the size of the smaller object to be discriminated (weed plants or weed patches).
authors.affiliation: Department of Crop Protection, Institute for Sustainable Agriculture (IAS) Spanish National Research Council (CSIC), Córdoba, Spain. jtorres@ias.csic.es
authors.forename: Jorge
authors.initials: J
authors.lastname: Torres-Sánchez
authors.forename: Francisca
authors.initials: F
authors.lastname: López-Granados
authors.forename: Ana Isabel
authors.initials: AI
authors.lastname: De Castro
authors.forename: José Manuel
authors.initials: JM
authors.lastname: Peña-Barragán
mesh_terms: D000401:Aircraft; D000531:Altitude; D010781:Photography; D012371:Robotics; D058728:Weed Control / Q000295:instrumentation* / Q000379:methods*