Processing and Assessment of Spectrometric, Stereoscopic Imagery Collected Using a Lightweight UAV Spectral Camera for Precision Agriculture

By Eija Honkavaara, Heikki Saari, Jere Kaivosoja, Ilkka Pölönen, Teemu Hakala, Paula Litkey, Jussi Mäkynen, Liisa Pesonen. Remote Sensing, 2013

491 citations recorded by the source corpus.

Imaging using lightweight, unmanned airborne vehicles (UAVs) is one of the most rapidly developing fields in remote sensing technology. The new, tunable, Fabry-Perot interferometer-based (FPI) spectral camera, which weighs less than 700 g, makes it possible to collect spectrometric image blocks with stereoscopic overlaps using light-weight UAV platforms. This new technology is highly relevant, because it opens up new possibilities for measuring and monitoring the environment, which is becoming increasingly important for many environmental challenges. Our objectives were to investigate the processing and use of this new type of image data in precision agriculture. We developed the entire processing chain from raw images up to georeferenced reflectance images, digital surface models and biomass estimates. The processing integrates photogrammetric and quantitative remote sensing approaches. We carried out an empirical assessment using FPI spectral imagery collected at an agricultural wheat test site in the summer of 2012. Poor weather conditions during the campaign complicated the data processing, but this is one of the challenges that are faced in operational applications. The

Subfields: Ecology, Environmental Engineering, Plant Science

View Paper: https://www.semanticscholar.org/paper/e08a5b2a63ebc6106b91c2fa6d0e6c11208b1404

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Citations in the corpus

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Unmanned Aircraft System (UAS) Technology and Applications in Agriculture (2019, background): “In a few studies, biomass yields of grasses were estimated using point clouds and crop height models (CHMs) [14,38], though, the majority of studies primarily used some form of vegetation index to make predictions [6,7,23,39,40].”