0000000000668565
AUTHOR
Heikki Salo
HYPERSPECTRAL REFLECTANCE SIGNATURES AND POINT CLOUDS FOR PRECISION AGRICULTURE BY LIGHT WEIGHT UAV IMAGING SYSTEM
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, w…
Image analysis with environmental applications
Kaukokartoitusmenetelmiä käytetään tarkkuusmaataloudessa ja metsien inventoinnissa. Pro gradu -tutkielma keskittyy parantamaan analysointiprosessia kasvillisuusmäärien arvioimiseksi esikäsitellyistä ilmakuvista ja digitaalisesta korkeusmallista. Tutkielmassa esitellään evolutiivinen optimointimenetelmä viljapellon biomassojen estimoimiseksi ja tutkitaan biomassaestimaattien tekoa eri menetelmin radiometrisesti korjatuista spektrikaistoista. Tutkielmassa pohditaan myös vaihtoehtoja puulajeittaisten tilavuuksien estimoimiseksi metsistä. Remote sensing methodologies are employed in the fields of precision agriculture and forest industry. This thesis focuses on enhancing analysation process for…
Regressiomenetelmiä viljapellon biomassan estimointiin ortokuvista ja digitaalisesta korkeusmallista
Tutkielmassa esitellään käyttötarkoitus biomassan estimoinnille ja vertaillaan kolmea regressiomenetelmää, lineaarista regressiota, k:n lähimmän naapurin menetelmää sekä tukivektoriregressiota. Tutkielmassa esitellään myös aineisto ja aineistoon suoritetut muunnokset.
A case study of a precision fertilizer application task generation for wheat based on classified hyperspectral data from UAV combined with farm history data
Different remote sensing methods for detecting variations in agricultural fields have been studied in last two decades. There are already existing systems for planning and applying e.g. nitrogen fertilizers to the cereal crop fields. However, there are disadvantages such as high costs, adaptability, reliability, resolution aspects and final products dissemination. With an unmanned aerial vehicle (UAV) based airborne methods, data collection can be performed cost-efficiently with desired spatial and temporal resolutions, below clouds and under diverse weather conditions. A new Fabry-Perot interferometer based hyperspectral imaging technology implemented in an UAV has been introduced. In this…
Biomass estimator for NIR image with a few additional spectral band images taken from light UAS
A novel way to produce biomass estimation will offer possibilities for precision farming. Fertilizer prediction maps can be made based on accurate biomass estimation generated by a novel biomass estimator. By using this knowledge, a variable rate amount of fertilizers can be applied during the growing season. The innovation consists of light UAS, a high spatial resolution camera, and VTT's novel spectral camera. A few properly selected spectral wavelengths with NIR images and point clouds extracted by automatic image matching have been used in the estimation. The spectral wavelengths were chosen from green, red, and NIR channels.