干旱区生态环境知识资源中心(Arid): Evaluating the utility of combining high resolution thermal, multispectral and 3D imagery from unmanned aerial vehicles to monitor water stress in vineyards

Arid

DOI	10.1007/s11119-024-10179-0
	Evaluating the utility of combining high resolution thermal, multispectral and 3D imagery from unmanned aerial vehicles to monitor water stress in vineyards
	Burchard-Levine, V.; Guerra, J. G.; Borra-Serrano, I.; Nieto, H.; Mesias-Ruiz, G.; Dorado, J.; de Castro, A. I.; Herrezuelo, M.; Mary, B.; Aguirre, E. P.; Pena, J. M.
通讯作者	Burchard-Levine, V
来源期刊	PRECISION AGRICULTURE
ISSN	1385-2256
EISSN	1573-1618
出版年	2024
英文摘要	Purpose High resolution imagery from unmanned aerial vehicles (UAVs) has been established as an important source of information to perform precise irrigation practices, notably relevant for high value crops often present in semi-arid regions such as vineyards. Many studies have shown the utility of thermal infrared (TIR) sensors to estimate canopy temperature to inform on vine physiological status, while visible-near infrared (VNIR) imagery and 3D point clouds derived from red-green-blue (RGB) photogrammetry have also shown great promise to better monitor within-field canopy traits to support agronomic practices. Indeed, grapevines react to water stress through a series of physiological and growth responses, which may occur at different spatio-temporal scales. As such, this study aimed to evaluate the application of TIR, VNIR and RGB sensors onboard UAVs to track vine water stress over various phenological periods in an experimental vineyard imposed with three different irrigation regimes. Methods A total of twelve UAV overpasses were performed in 2022 and 2023 where in situ physiological proxies, such as stomatal conductance (g(s)), leaf (Psi(leaf)) and stem (Psi(stem)) water potential, and canopy traits, such as LAI, were collected during each UAV overpass. Linear and non-linear models were trained and evaluated against in-situ measurements. Results Results revealed the importance of TIR variables to estimate physiological proxies (g(s), Psi(leaf), Psi(stem)) while VNIR and 3D variables were critical to estimate LAI. Both VNIR and 3D variables were largely uncorrelated to water stress proxies and demonstrated less importance in the trained empirical models. However, models using all three variable types (TIR, VNIR, 3D) were consistently the most effective to track water stress, highlighting the advantage of combining vine characteristics related to physiology, structure and growth to monitor vegetation water status throughout the vine growth period. Conclusion This study highlights the utility of combining such UAV-based variables to establish empirical models that correlated well with field-level water stress proxies, demonstrating large potential to support agronomic practices or even to be ingested in physically-based models to estimate vine water demand and transpiration.
英文关键词	Remote sensing UAVs Irrigation Vineyards Thermal infrared Multispectral 3D imagery
类型	Article ; Early Access
语种	英语
开放获取类型	hybrid
收录类别	SCI-E
WOS记录号	WOS:001295712900001
WOS关键词	LEAF-AREA INDEX ; REFLECTANCE INDEXES ; VEGETATION INDEXES ; CANOPY TEMPERATURE ; VARIABILITY ; GRAPEVINE ; SOIL ; ALGORITHMS ; FLUXES
WOS类目	Agriculture, Multidisciplinary
WOS研究方向	Agriculture
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/405220
推荐引用方式 GB/T 7714	Burchard-Levine, V.,Guerra, J. G.,Borra-Serrano, I.,et al. Evaluating the utility of combining high resolution thermal, multispectral and 3D imagery from unmanned aerial vehicles to monitor water stress in vineyards[J],2024.
APA	Burchard-Levine, V..,Guerra, J. G..,Borra-Serrano, I..,Nieto, H..,Mesias-Ruiz, G..,...&Pena, J. M..(2024).Evaluating the utility of combining high resolution thermal, multispectral and 3D imagery from unmanned aerial vehicles to monitor water stress in vineyards.PRECISION AGRICULTURE.
MLA	Burchard-Levine, V.,et al."Evaluating the utility of combining high resolution thermal, multispectral and 3D imagery from unmanned aerial vehicles to monitor water stress in vineyards".PRECISION AGRICULTURE (2024).