Unmanned aerial vehicle-based field phenotyping of crop biomass using growth traits retrieved from PROSAIL model

2021 ◽  
Vol 187 ◽  
pp. 106304
Author(s):  
Liang Wan ◽  
Jiafei Zhang ◽  
Xiaoya Dong ◽  
Xiaoyue Du ◽  
Jiangpeng Zhu ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Growth Traits ◽  
Field Phenotyping ◽  
Aerial Vehicle ◽  
Crop Biomass

scholarly journals Assessment of Multi-Image Unmanned Aerial Vehicle Based High-Throughput Field Phenotyping of Canopy Temperature

2020 ◽  
Vol 11 ◽  
Author(s):  
Gregor Perich ◽  
Andreas Hund ◽  
Jonas Anderegg ◽  
Lukas Roth ◽  
Martin P. Boer ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
High Throughput ◽  
Canopy Temperature ◽  
Field Phenotyping ◽  
Aerial Vehicle

scholarly journals High-throughput field phenotyping in dry bean using small unmanned aerial vehicle based multispectral imagery

2018 ◽  
Vol 151 ◽  
pp. 84-92 ◽  
Author(s):  
Sindhuja Sankaran ◽  
Jianfeng Zhou ◽  
Lav R. Khot ◽  
Jennifer J. Trapp ◽  
Eninka Mndolwa ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
High Throughput ◽  
Multispectral Imagery ◽  
Dry Bean ◽  
Field Phenotyping ◽  
Aerial Vehicle

scholarly journals Easy MPE: Extraction of Quality Microplot Images for UAV-Based High-Throughput Field Phenotyping

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Léa Tresch ◽  
Yue Mu ◽  
Atsushi Itoh ◽  
Akito Kaga ◽  
Kazunori Taguchi ◽  
...  
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Unmanned Aerial Vehicle ◽  
High Throughput ◽  
Field Conditions ◽  
Processing Step ◽  
Field Phenotyping ◽  
Binary Segmentation ◽  
Aerial Vehicle ◽  
Uav Images

Microplot extraction (PE) is a necessary image processing step in unmanned aerial vehicle- (UAV-) based research on breeding fields. At present, it is manually using ArcGIS, QGIS, or other GIS-based software, but achieving the desired accuracy is time-consuming. We therefore developed an intuitive, easy-to-use semiautomatic program for MPE called Easy MPE to enable researchers and others to access reliable plot data UAV images of whole fields under variable field conditions. The program uses four major steps: (1) binary segmentation, (2) microplot extraction, (3) production of ∗.shp files to enable further file manipulation, and (4) projection of individual microplots generated from the orthomosaic back onto the raw aerial UAV images to preserve the image quality. Crop rows were successfully identified in all trial fields. The performance of the proposed method was evaluated by calculating the intersection-over-union (IOU) ratio between microplots determined manually and by Easy MPE: the average IOU (±SD) of all trials was 91% (±3).

scholarly journals Unmanned aerial vehicle–based assessment of cover crop biomass and nitrogen uptake variability

2019 ◽  
Vol 74 (4) ◽  
pp. 350-359 ◽  
Author(s):  
M. Yuan ◽  
J.C. Burjel ◽  
J. Isermann ◽  
N.J. Goeser ◽  
C.M. Pittelkow
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Nitrogen Uptake ◽  
Cover Crop ◽  
Aerial Vehicle ◽  
Crop Biomass

scholarly journals Easy MPE: Extraction of quality microplot images for UAV-based high-throughput field phenotyping

2019 ◽  
Author(s):  
Léa Tresch ◽  
Yue Mu ◽  
Atsushi Itoh ◽  
Akito Kaga ◽  
Kazunori Taguchi ◽  
...  
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Unmanned Aerial Vehicle ◽  
High Throughput ◽  
Automatic Program ◽  
Processing Step ◽  
Field Phenotyping ◽  
Binary Segmentation ◽  
Aerial Vehicle ◽  
Uav Images

AbstractMicroplot extraction (MPE) is a necessary image-processing step in unmanned aerial vehicle (UAV)-based research on breeding fields. At present, it is manually using ArcGIS, QGIS or other GIS-based software, but achieving the desired accuracy is time-consuming. We therefore developed an intuitive, easy-to-use semi-automatic program for MPE called Easy MPE to enable researchers and others to access reliable plot data UAV images of whole fields under variable field conditions. The program uses four major steps: (1). Binary segmentation, (2). Microplot extraction, (3). Production of *.shp files to enable further file manipulation, and (4). Projection of individual microplots generated from the orthomosaic back onto the raw aerial UAV images to preserve the image quality. Crop rows were successfully identified in all trial fields. The performance of proposed method was evaluated by calculating the intersection-over-union (IOU) ratio between microplots determined manually and by Easy MPE: The average IOU (±SD) of all trials was 91% (±3).

Study on Fault Diagnosis of Planetary Gearbox in Unmanned Aerial Vehicle Using Multi sensor Data

2020 ◽  
Vol 20 (4) ◽  
pp. 332-342
Author(s):  
Hyung Jun Park ◽  
Seong Hee Cho ◽  
Kyung-Hwan Jang ◽  
Jin-Woon Seol ◽  
Byung-Gi Kwon ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Unmanned Aerial Vehicle ◽  
Sensor Data ◽  
Planetary Gearbox ◽  
Aerial Vehicle

Results of Spatial Structure of Atmosphere Radiation in a Spectral Range (1.5–2) µm Research

2018 ◽  
pp. 7-13
Author(s):  
Anton M. Mishchenko ◽  
Sergei S. Rachkovsky ◽  
Vladimir A. Smolin ◽  
Igor V . Yakimenko
Keyword(s):  
Spatial Structure ◽  
Unmanned Aerial Vehicle ◽  
Wavelength Range ◽  
Spectral Range ◽  
Near Ir ◽  
Optoelectronic Systems ◽  
Aerial Vehicle

Results of experimental studying radiation spatial structure of atmosphere background nonuniformities and of an unmanned aerial vehicle being the detection object are presented. The question on a possibility of its detection using optoelectronic systems against the background of a cloudy field in the near IR wavelength range is also considered.

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