Abstract
Abstract. Remote sensing with lightweight optical sensors is becoming a powerful tool to solve many problems in agriculture. Achieving the level of spatial and spectral resolutions required for this type of detection at an acceptable cost-benefit ratio has motivated the development of new sensors which must be lightweight to be carried by mobile robots either aerial or terrestrial. One new type of multiple head cameras has been developed by Agrowing, an Israeli company developing technology for digital agriculture. The aim of this paper is to analyse the geometric features of an Agrowing dual head camera trough calibration experiments. The sensor was calibrated following two options, depending on the cropping technique used to produce the 4 spectral bands. Different calibration techniques were also used and very accurate results were achieved. Experiments with data collected with a UAV also confirmed the results achieved with close range calibration.
Highlights
Proximal remote sensing is emerging as a powerful technique for precision agriculture, especially for detection of crop diseases and quality of plant nutrition (Nansen, 2016) (Murray et al, 2019)
Achieving the level of spatial and spectral resolutions required for this type of detection is challenging
The first set of analysis was performed in the values of the estimated inner orientation parameters (IOPs) and estimated standard deviations with the automatically cropped images processed by single camera calibration (Configuration A in Table 3, results in Table 4 and Table 5)
Summary
Proximal remote sensing is emerging as a powerful technique for precision agriculture, especially for detection of crop diseases and quality of plant nutrition (Nansen, 2016) (Murray et al, 2019). Unmanned Aerial Vehicles (UAV) or Mobile Mapping Systems are recognized as suitable platforms to carry lightweight sensors with detection capabilities, like multispectral or hyperspectral cameras. There are many models of lightweight multispectral cameras, with some differences in geometry, weight and costs (Nebiker et al, 2016). Multispectral, light-weight and low-cost systems usually combine multiple cameras to acquire different spectral bands. Cameras such as MCA_Tetracam, MAIA, MicaSense and Parrot Sequoia have become common alternatives in the UAV applications. There are some drawbacks when using multiple cameras to acquire multispectral images, such as the triggering synchronization, the relative calibration and bands registration and relative exposures. One new type of multiple head cameras has been developed by Agrowing, an Israeli company developing technology for digital agriculture
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