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Sirvi Autor "Lajunen, A." järgi

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  • Pisipilt
    Kirje
    Application of UAV multispectral imaging for determining the characteristics of maize vegetation
    (Estonian University of Life Sciences, 2023) Änäkkälä, M.; Lehtilä, A.; Mäkelä, P.S.A.; Lajunen, A.
    Interest in forage maize (Zea mays L.) cultivation for livestock feed has grown in northern conditions. In addition, it is important to develop methods and tools to monitor crop development and other characteristics of the crop. For these purposes UAVs are very efficient and versatile tools. UAVs can be equipped with a variety of sensors like lidar or different types of cameras. Several studies have been conducted where data collected by UAVs are used to estimate different crop properties like yield and biomass. In this research, a forage maize field experiment was studied to examine how well the aerial multispectral data correlated with the different properties of the vegetation. The field test site is located in Helsinki, Finland. A multispectral camera (MicaSense Rededge 3) was used to take images from five spectral bands (Red, Green, Blue, Rededge and NIR). All the images were processed with Pix4D software to generate orthomosaic images. Several vegetation indices were calculated from the five spectral bands. During the growing season, crop height, chlorophyll content, leaf area index (LAI), fresh and dry matter biomass were measured from the vegetation. From the five spectral bands, Rededge had the highest correlation with fresh biomass (R2 = 0.273). The highest correlation for a vegetation index was found between NDRE and chlorophyll content (R2 = 0.809). A multiple linear regression (MLR) model using selected spectral bands and vegetation indices as inputs showed high correlations with the field measurements.
  • Pisipilt
    Kirje
    Development of a custom-built RTK-GNSS positioning system for agricultural operations
    (Estonian University of Life Sciences, 2023) Lajunen, A.; Pietarinen, J.
    The objective of this research is to assess positioning accuracy of a custom-built RTK (Real Time Kinematic) base station. Setting up a RTK base station with open-source tools is rather straightforward process requiring only few components and basic programming skills. The base station and receiver unit were developed by using a SparkFun GPS-RTK2 Board with U-Blox ZED-F9P module. The board was paired with U-blox Multi band GNSS (Global Navigation Satellite System) antenna. The board can use GNSS satellite signals from Galileo, BeiDou, Glonass and GPS systems. The positioning accuracy was evaluated in a fixed position and during operations in agricultural fields. The RTK correction signal was used in connection with soil scanning measurements in different crop fields of the Viikki Research Farm of the University of Helsinki. For accuracy assessment, comparative measurements were carried out with a commercial network RTK (NRTK) correction signal. The vertical and horizontal accuracy of the positioning signal were evaluated based on the accuracy variables calculated by the receiver. The vertical accuracy was also evaluated by mapping the scanned trajectories on the height map which was obtained from NSL (National Land Survey of Finland) open map data service. The custom-built RTK positioning system accuracy was considered generally precise enough for autonomous field work, but the reliability of the observed accuracy should be confirmed with more extensive measurements. The commercial NRTK signal accuracy was considered very good and reliable also for the vertical direction.