High-resolution UAV-based thermal imaging to estimate the instantaneous and seasonal variability of plant water status within a vineyard

Santesteban, L.G.; Gennaro, Salvatore Filippo Di; Herrero-Langreo, Ana; Jiménez, Carlos Miranda; Royo, J.B.; Matese, Alessandro

doi:10.1016/j.agwat.2016.08.026

Cited by 212 publications

(138 citation statements)

References 44 publications

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“…Another source of uncertainties could be related to the erroneous consideration of CWSI as the entire season water stress index. CWSI measured on a single day did not provide a good estimation of the variations of plant water status [53]. The objective of the work was to evaluate the instantaneous correspondence between water status characterizations through different sensing techniques.…”

Section: Discussionmentioning

confidence: 99%

Estimation of Water Stress in Grapevines Using Proximal and Remote Sensing Methods

et al. 2018

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Abstract:In light of climate change and its impacts on plant physiology, optimizing water usage and improving irrigation practices play a crucial role in crop management. In recent years, new optical remote sensing techniques have become widespread since they allow a non-invasive evaluation of plant water stress dynamics in a timely manner. Unmanned aerial vehicles (UAV) currently represent one of the most advanced platforms for remote sensing applications. In this study, remote and proximal sensing measurements were compared with plant physiological variables, with the aim of testing innovative services and support systems to farmers for optimizing irrigation practices and scheduling. The experiment, conducted in two vineyards located in Sardinia, Italy, consisted of two regulated deficit irrigation (RDI) treatments and two reference treatments maintained under stress and well-watered conditions. Indicators of crop water status (Crop Water Stress Index-CWSI-and linear thermal index) were calculated from UAV images and ground infrared thermal images and then related to physiological measurements. The CWSI values for moderate water deficit (RDI-1) were 0.72, 0.28 and 0.43 for 'Vermentino', 'Cabernet' and 'Cagnulari' respectively, while for severe (RDI-2) water deficit the values were 0.90, 0.34 and 0.51. The highest differences for net photosynthetic rate (Pn) and stomatal conductance (Gs) between RDI-1 and RDI-2 were observed in 'Vermentino'. The highest significant correlations were found between CWSI with Pn (R = −0.80), with Φ PSII (R = −0.49) and with Fv'/Fm' (R = −0.48) on 'Cagnulari', while a unique significant correlation between CWSI and non-photochemical quenching (NPQ) (R = 0.47) was found on 'Vermentino'. Pn, as well as the efficiency of light use by the photosystem II (PSII), declined under stress conditions and when CWSI values increased. Under the experimental water stress conditions, grapevines were able to recover their efficiency during the night, activating a photosynthetic protection mechanism such as thermal energy dissipation (NPQ) to prevent irreversible damage to the photosystem. The results presented here demonstrate that CWSI values derived from remote and proximal sensors could be valuable indicators for the assessment of the spatial variability of crop water status in Mediterranean vineyards.

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Section: Discussionmentioning

confidence: 99%

Estimation of Water Stress in Grapevines Using Proximal and Remote Sensing Methods

et al. 2018

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“…The derived CWSI maps can serve as important inputs for precision irrigation. Time series of thermal images can also be used to determine the variation in water status [97].…”

Section: Vegetation Monitoring and Precision Agriculturementioning

confidence: 99%

On the Use of Unmanned Aerial Systems for Environmental Monitoring

et al. 2018

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Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small-and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air-and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challenges.

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“…Inclusion of a third target not only provides redundancy, but also allows assessment of the quality of fit between recorded and actual temperatures. To retrieve the calibration coefficients, the deployed targets would normally be imaged at the beginning and the end of the survey [44], although additional mid-flight calibrations [43] may be preferred on longer flights or if weather conditions are rapidly changing. Using the empirical line calibration method, Gomez-Candon et al [43] reported R 2 value of 0.768 in linear regression of apple tree canopy temperature measurements from calibrated thermal imagery and from radio-thermometers positioned 1.2 m above top of the tops of the canopies.…”

Section: Discussionmentioning

confidence: 99%

Use of Miniature Thermal Cameras for Detection of Physiological Stress in Conifers

et al. 2017

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Tree growth and survival predominantly depends on edaphic and climatic conditions, thus climate change will inevitably influence forest health and growth. It will affect forests directly, for example, through extended periods of drought, and indirectly, such as by affecting the distribution and abundance of forest pathogens and pests. Developing ways of early detection and monitoring of tree stress is crucial for effective protection of forest stands. Thermography is one of the techniques that can be used for monitoring changes in the physiological state of plants; however, in forestry, it has not been widely tested or utilized. The main challenge rises from the need for high spatial resolution data. Newly emerging technologies, such as unmanned aerial vehicles (UAVs) could aid in provision of the required data. However, their main constraint is the limited payload, requiring the use of miniature sensors. This paper investigates whether a miniature microbolometer thermal camera, designed for a UAV platform, can provide reliable canopy temperature measurements of conifers. Furthermore, it explores whether there is a distinction in whole canopy temperature between the control and the stressed trees, assessing the potential of low-cost thermography for investigating stress in conifers. Two experiments on young larch trees, with induced drought stress, were performed. The plants were imaged in a greenhouse setting, and readings from a set of thermocouples attached to the canopy were used as a method of validation. Following calibration and a basic normalization for background radiation, both the spatial and temporal variation of canopy temperature was well characterized. Very mild stress did not exhibit itself, as the temperature readings for both stressed and control plants were similar. However, with a higher stress level, there was a clear distinction (temperature difference of 1.5 • C) between the plants, showing potential for using low-cost sensors to investigate tree stress.

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High-resolution UAV-based thermal imaging to estimate the instantaneous and seasonal variability of plant water status within a vineyard

Cited by 212 publications

References 44 publications

Estimation of Water Stress in Grapevines Using Proximal and Remote Sensing Methods

Estimation of Water Stress in Grapevines Using Proximal and Remote Sensing Methods

On the Use of Unmanned Aerial Systems for Environmental Monitoring

Use of Miniature Thermal Cameras for Detection of Physiological Stress in Conifers

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