Abstract
Abstract. The objective of this investigation was to study the use of a new type of a low-weight unmanned aerial vehicle (UAV) imaging system in the precision agriculture. The system consists of a novel Fabry-Perot interferometer based hyperspectral camera and a high-resolution small-format consumer camera. The sensors provide stereoscopic imagery in a 2D frame-format and they both weigh less than 500 g. A processing chain was developed for the production of high density point clouds and hyperspectral reflectance image mosaics (reflectance signatures), which are used as inputs in the agricultural application. We demonstrate the use of this new technology in the biomass estimation process, which is based on support vector regression machine. It was concluded that the central factors influencing on the accuracy of the estimation process were the quality of the image data, the quality of the image processing and digital surface model generation, and the performance of the regressor. In the wider perspective, our investigation showed that very low-weight, low-cost, hyperspectral, stereoscopic and spectrodirectional 3D UAV-remote sensing is now possible. This cutting edge technology is powerful and cost efficient in time-critical, repetitive and locally operated remote sensing applications.
Highlights
The unmanned aerial vehicle (UAV) based remote sensing with low-weight imaging systems offers low-cost and flexible tools for the agricultural applications
We investigated the use of a new type of a UAV imaging system in agricultural applications
The system consists of a novel Fabry-Perot interferometer based hyperspectral camera (Saari et al, 2011) and a high-resolution small format camera Panasonic Lumix GF1
Summary
The unmanned aerial vehicle (UAV) based remote sensing with low-weight imaging systems offers low-cost and flexible tools for the agricultural applications. Based on the precise measurements of energy emission and reflection from the vegetation, a wide range of variables that affect the crops can be monitored, such as soil moisture, surface temperature, photosynthetic activity, and weed or pest infestations. This information is of increasing importance to ensure the cost-efficiency of the agricultural production, for the harvest forecasts and from the wider perspectives of the climate change mitigation and adaptation, and the environmental sustainability. The UAV imaging service providers collect and process the images of the crop fields of farmers. In Finland, the optimization of fertilizers and pesticides are expected to be the first operational applications of the technology; the time window for the UAV data collection is two weeks and the maximum allowable processing time is one week
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