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B2FIND
Dataset . 2020
Data sources: B2FIND
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PANGAEA
Dataset . 2020
License: CC BY
Data sources: PANGAEA
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UAV-based multispectral data in legume-grass mixtures

Authors: orcid bw Grüner, Esther;
Grüner, Esther
ORCID
Derived by OpenAIRE algorithms or harvested from 3rd party repositories

Grüner, Esther in OpenAIRE
Wachendorf, Michael; orcid bw Astor, Thomas;
Astor, Thomas
ORCID
Derived by OpenAIRE algorithms or harvested from 3rd party repositories

Astor, Thomas in OpenAIRE

UAV-based multispectral data in legume-grass mixtures

Abstract

Multispectral data from two legume-grass mixtures (clover- and lucerne-grass) were collected in the year 2018 for aboveground biomass and nitrogen fixation (NFix) estimation. In addition to the mixtures, pure stands of legumes and of grasses of the two mixtures were sown in order to represent variable conditions in practical farming (0-100% legumes). All six treatments were cultivated in four replicates and harvested three times within the year (plot size: 1.5 x 12 m). Destructive biomass samples for fresh (FM) and dry matter (DM) and NFix determination were taken three times at harvest. To cover the entire vegetation season, sub-sampling for DM and FM was done five times between the harvests. Flight missions were carried out one day before each of the eight sampling dates. A multispectral sensor (Parrot Sequoia, MicaSense Inc, Seattle, USA) with four spectral bands (green, red, red edge, near infrared) was mounted on a low-cost unmanned aerial vehicle (UAV; DJI Phantom 3, Advanced, Shenzhen, China). Eight black and white ground control points (GCPs) were distributed in the pathways. Coordinates of the plot corners and GCPs were measured by a Leica real time kinematic global navigation satellite system (Leica RTK GNSS). Orthomosaics were created by the overlapping images with a photogrammetric processing software (Agisoft PhotoScan Professional, Agisoft LLC, St. Petersburg, Russia). The orthomosaics were georeferenced using the coordinates of the GCPs. The mean reflectance value of the four bands was extracted by zonal statistics in QGIS (Quantum Geografic Infromation System) using the four plot corners of each plot as boundaries. Furthermore, eight texture features of every band were calculated, provided by the processing tool HaralickTextureExtraction of the Orfeo Toolbox library (OTB) in QGIS.

Keywords

Latitude, additional, Longitude, additional, UAV, fresh mass, DJI Phantom 3, Sample comment, Crop, Parrot Sequoia, DJI Phantom 3, Agisoft PhotoScan, HaralickTextureExtraction in QGIS, Near infrared band, dry mass, Leica RTK GNSS, remote sensing, Red edge band, Nitrogen fixation, Weighted, DATE TIME, biomass estimation, Biomass, dry mass, Biomass, Red edge band texture, Agisoft PhotoScan, Biomass, fresh mass, Green band texture, Difference method according to Stülpnagel 1982, Latitude, Event label, Near infrared band texture, Difference method: according to Stülpnagel (1982), DATE/TIME, Red band, Plot, Red band texture, Longitude, nitrogen fixation, Parrot Sequoia, Earth System Research, texture features, grassland, Green band

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