Assessment of Unmanned Aerial Vehicles Imagery for Quantitative Monitoring of Wheat Crop in Small Plots
Autor: | Philippe Burger, Bruno Roux, Guillaume Jubelin, Sylvain Labbé, Frédéric Baret, Camille Lelong |
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Přispěvatelé: | Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Institut National de la Recherche Agronomique (INRA), NEV@NTROPIS CAYENNE, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), AVION JAUNE MONTPELLIER, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre national du machinisme agricole, du génie rural, des eaux et forêts (CEMAGREF), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS) |
Rok vydání: | 2008 |
Předmět: |
Engineering
010504 meteorology & atmospheric sciences Multispectral image 0211 other engineering and technologies F62 - Physiologie végétale - Croissance et développement 02 engineering and technology lcsh:Chemical technology 01 natural sciences Biochemistry Analytical Chemistry lcsh:TP1-1185 Instrumentation imagery multispectral precision farming uav 2. Zero hunger Expérimentation Vignetting Indice de surface foliaire Vegetation Spectral bands Métrologie Atomic and Molecular Physics and Optics Relevé aérien [SDE]Environmental Sciences Développement biologique Méthodologie Télédétection Triticum aestivum Article Normalized Difference Vegetation Index Imagery Multispectral Precision Farming UAV Mesure Electrical and Electronic Engineering Leaf area index 021101 geological & geomatics engineering 0105 earth and related environmental sciences Remote sensing Métabolisme de l'azote business.industry Glider Autre (Sciences de l'ingénieur) Precision agriculture U30 - Méthodes de recherche business |
Zdroj: | Sensors; Volume 8; Issue 5; Pages: 3557-3585 Sensors Sensors, MDPI, 2008, 8 (5), pp.3557-3585. ⟨10.3390/s8053557⟩ Sensors 5 (8), 3557-3585. (2008) Sensors, Vol 8, Iss 5, Pp 3557-3585 (2008) Sensors (Basel, Switzerland) |
ISSN: | 1424-8220 |
DOI: | 10.3390/s8053557 |
Popis: | International audience; This paper outlines how light Unmanned Aerial Vehicles (UAV) can be used in remote sensing for precision farming. It focuses on the combination of simple digital photographic cameras with spectral filters, designed to provide multispectral images in the visible and near-infrared domains. In 2005, these instruments were fitted to powered glider and parachute, and flown at six dates staggered over the crop season. We monitored ten varieties of wheat, grown in trial micro-plots in the South-West of France. For each date, we acquired multiple views in four spectral bands corresponding to blue, green, red, and near-infrared. We then performed accurate corrections of image vignetting, geometric distortions, and radiometric bidirectional effects. Afterwards, we derived for each experimental micro-plot several vegetation indexes relevant for vegetation analyses. Finally, we sought relationships between these indexes and field-measured biophysical parameters, both generic and date-specific. Therefore, we established a robust and stable generic relationship between, in one hand, leaf area index and NDVI and, in the other hand, nitrogen uptake and GNDVI. Due to a high amount of noise in the data, it was not possible to obtain a more accurate model for each date independently. A validation protocol showed that we could expect a precision level of 15% in the biophysical parameters estimation while using these relationships. |
Databáze: | OpenAIRE |
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