High-Resolution UAV RGB Imagery Dataset for Precision Agriculture and 3D Photogrammetric Reconstruction Captured over a Pistachio Orchard ( Pistacia vera L.) in Spain

Sergio Vélez (), Rubén Vacas, Hugo Martín, David Ruano-Rosa and Sara Álvarez
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Sergio Vélez: Information Technology Group, Wageningen University and Research, 6708 PB Wageningen, The Netherlands
Rubén Vacas: Instituto Tecnológico Agrario de Castilla y León (ITACyL), Unidad de Cultivos Leñosos y Hortícolas, 47071 Valladolid, Spain
Hugo Martín: Instituto Tecnológico Agrario de Castilla y León (ITACyL), Unidad de Cultivos Leñosos y Hortícolas, 47071 Valladolid, Spain
David Ruano-Rosa: Instituto Tecnológico Agrario de Castilla y León (ITACyL), Unidad de Cultivos Leñosos y Hortícolas, 47071 Valladolid, Spain
Sara Álvarez: Instituto Tecnológico Agrario de Castilla y León (ITACyL), Unidad de Cultivos Leñosos y Hortícolas, 47071 Valladolid, Spain

Data, 2022, vol. 7, issue 11, 1-11

Abstract: A total of 248 UAV RGB images were taken in the summer of 2021 over a representative pistachio orchard in Spain (X: 341450.3, Y: 4589731.8; ETRS89/UTM zone 30N). It is a 2.03 ha plot, planted in 2016 with Pistacia vera L. cv. Kerman grafted on UCB rootstock, with a NE–SW orientation and a 7 × 6 m triangular planting pattern. The ground was kept free of any weeds that could affect image processing. The photos (provided in JPG format) were taken using a UAV DJI Phantom Advance quadcopter in two flight missions: one planned to take nadir images (β = 0°), and another to take oblique images (β = 30°), both at 55 metres above the ground. The aerial platform incorporates a DJI FC6310 RGB camera with a 20 megapixel sensor, a horizontal field of view of 84° and a mechanical shutter. In addition, GCPs (ground control points) were collected. Finally, a high-quality 3D photogrammetric reconstruction process was carried out to generate a 3D point cloud (provided in LAS, LAZ, OBJ and PLY formats), a DEM (digital elevation model) and an orthomosaic (both in TIF format). The interest in using remote sensing in precision agriculture is growing, but the availability of reliable, ready-to-work, downloadable datasets is limited. Therefore, this dataset could be useful for precision agriculture researchers interested in photogrammetric reconstruction who want to evaluate models for orthomosaic and 3D point cloud generation from UAV missions with changing flight parameters, such as camera angle.

Keywords: leaf area; drone; dense cloud; aerial; LAI; 3D point cloud; unmanned aerial vehicle; structure from motion; canopy; crown volume (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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