Evaluating UAV-Based Remote Sensing for Hay Yield Estimation.

Remote Sensing Technology / methods Biomass Unmanned Aerial Devices Crops, Agricultural / growth & development
UAV hay yield-monitoring system multispectral image precision agriculture remote-sensing technology

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
17 Aug 2024
Historique:
received: 29 06 2024
revised: 09 08 2024
accepted: 14 08 2024
medline: 1 9 2024
pubmed: 31 8 2024
entrez: 29 8 2024
Statut: epublish

Résumé

(1) Background: Yield-monitoring systems are widely used in grain crops but are less advanced for hay and forage. Current commercial systems are generally limited to weighing individual bales, limiting the spatial resolution of maps of hay yield. This study evaluated an Uncrewed Aerial Vehicle (UAV)-based imaging system to estimate hay yield. (2) Methods: Data were collected from three 0.4 ha plots and a 35 ha hay field of red clover and timothy grass in September 2020. A multispectral camera on the UAV captured images at 30 m (20 mm pixel

Identifiants

DOI: 10.3390/s24165326 PMID: 39205020
pubmed: 39205020
pii: s24165326
doi: 10.3390/s24165326
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Agricultural Research Service
ID : 5070-12000-001-004S

Auteurs

Kyuho Lee (K)

Department of Chemical and Biomedical Engineering, University of Missouri, Columbia, MO 65211, USA.
Department of Smart Agricultural System, Graduate School, Chungnam National University, Daejeon 34134, Republic of Korea.
Department of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Republic of Korea.
ORCID: 0000-0002-3186-8975

Kenneth A Sudduth (KA)

USDA-ARS Cropping Systems and Water Quality Research Unit, Columbia, MO 65211, USA.
ORCID: 0000-0002-2558-0668

Jianfeng Zhou (J)

Division of Plant Science and Technology, University of Missouri, Columbia, MO 65211, USA.
ORCID: 0000-0002-7127-1428

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Classifications MeSH

questionsmedicales.fr › Sciences de l'information › Sources d'information › Moyens de communication › Télécommunications › Télémétrie › Technologie de télédétection › Evaluating UAV-Based Remote Sensing for Hay...
questionsmedicales.fr › Environnement et santé publique › Environnement › Écosystème › Biomasse › Evaluating UAV-Based Remote Sensing for Hay...
questionsmedicales.fr › Technologie, industrie et agriculture › Transports › Aviation › Véhicules de transport aérien › Dispositifs aériens sans pilote › Evaluating UAV-Based Remote Sensing for Hay...
questionsmedicales.fr › Aliments et boissons › Aliments › Produits agricoles › Evaluating UAV-Based Remote Sensing for Hay...