Mobile low-cost 3D camera maize crop height measurements under field conditions

• Verfasst von: Hämmerle, Martin [VerfasserIn]
• Verfasst von: Höfle, Bernhard [VerfasserIn]
• Titel: Mobile low-cost 3D camera maize crop height measurements under field conditions
• Verf.angabe: Martin Hämmerle, Bernhard Höfle
• Jahr: 2018
• Umfang: 18 S.
• Fussnoten: Published online: 19 October 2017 ; Im Titel die 3 ist tiefgestellt ; Gesehen am 19.08.2019
• Titel Quelle: Enthalten in: Precision agriculture
• Ort Quelle: Dordrecht [u.a.] : Springer Science + Business Media B.V, 1999
• Jahr Quelle: 2018
• Band/Heft Quelle: 19(2018), 4, Seite 630-647
• ISSN Quelle: 1573-1618
• DOI: doi:10.1007/s11119-017-9544-3
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Low-cost 3D camera
• Sach-SW: Maize crop height
• Sach-SW: Mobile field measurements
• Sach-SW: Terrestrial laser scanning
• K10plus-PPN: 1671594703

Abstract

To tackle global challenges such as food supply and renewable energy provision, the improvement of efficiency and productivity in agriculture is of high importance. Site-specific information about crop height plays an important role in reaching these goals. Crop height can be derived with a variety of approaches including the analysis of three-dimensional (3D) geodata. Crop height values derived from 3D geodata of maize (1.88 and 2.35 m average height) captured with a low-cost 3D camera were examined. Data were collected with a unique measurement setup including the mobile mounting of the 3D camera, and data acquisition under field conditions including wind and sunlight. Furthermore, the data were located in a global co-ordinate system with a straightforward approach, which can strongly reduce computational efforts and which can subsequently support near real-time data processing in the field. Based upon a comparison between crop height values derived from 3D geodata captured with the low-cost approach, and high-end terrestrial laser scanning reference data, minimum RMS and standard deviation values of 0.13 m (6.91% of average crop height), and maximum R2 values of 0.79 were achieved. It can be concluded that the crop height measurements derived from data captured with the introduced setup can provide valuable input for tasks such as biomass estimation. Overall, the setup is considered to be a valuable extension for agricultural machines which will provide complementary crop height measurements for various agricultural applications.