UAVs challenge to assess water stress for sustainable agriculture

Gago, Jorge; Douthe, Cyril; Coopman, Rafael E.; Gallego, Pedro Pablo Ferrer; Ribas‐Carbó, Miquel; Flexas, Jaume; Escalona, José M.; Medrano, H.

doi:10.1016/j.agwat.2015.01.020

Cited by 438 publications

(292 citation statements)

References 53 publications

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“…2018, 10, 641 9 of 28 Vegetation state can be evaluated and quantified through different vegetation indices from images acquired in the visible, red edge, and near-infrared spectral bands. Depending on their formulation, these can display a strong correlation with soil coverage and Leaf and Green Area Index (LAI and GAI), Crop Nitrogen Uptake (QN), chlorophyll content, water stress detection, canopy structure, photosynthesis, yield, and/or growing conditions [67][68][69]. As such, these vegetation indices may be exploited to monitor biophysical parameters.…”

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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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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“…[52,53,70,77,78], to facilitate its applicability in interpreting photosynthetic activity and in the large-scale monitoring of carbon uptake. Increasingly used unmanned aerial vehicles (UAVs) with various optical sensors provide an exciting opportunity to monitor multiple optical signals (e.g., PRI and WI) with high spatiotemporal resolution [79]. MODIS (Moderate Resolution Imaging Spectroradiometer) aboard the Terra and Aqua satellites provides the possibility of retrieving PRI or CCI (chlorophyll/carotenoid index, [41]) both in the morning and at midday, which can be further applied to test the diurnal changes of PRI or CCI and the utility of assessing carbon budget under ongoing and future climate change at larger spatial and longer temporal scales.…”

Section: Conclusion and Final Remarksmentioning

confidence: 99%

Photochemical Reflectance Index (PRI) for Detecting Responses of Diurnal and Seasonal Photosynthetic Activity to Experimental Drought and Warming in a Mediterranean Shrubland

et al. 2017

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Climatic warming and drying are having profound impacts on terrestrial carbon cycling by altering plant physiological traits and photosynthetic processes, particularly for species in the semi-arid Mediterranean ecosystems. More effective methods of remote sensing are needed to accurately assess the physiological responses and seasonal photosynthetic activities of evergreen species to climate change. We evaluated the stand reflectance in parallel to the diurnal and seasonal changes in gas exchange, fluorescence and water contents of leaves and soil for a Mediterranean evergreen shrub, Erica multiflora, submitted to long-term experimental warming and drought. We also calculated a differential photochemical reflectance index (∆PRI, morning PRI subtracted from midday PRI) to assess the diurnal responses of photosynthesis (∆A) to warming and drought. The results indicated that the PRI, but not the normalized difference vegetation index (NDVI), was able to assess the seasonal changes of photosynthesis. Changes in water index (WI) were consistent with seasonal foliar water content (WC). In the warming treatment, ∆A value was higher than control in winter but ∆Yield was significantly lower in both summer and autumn, demonstrating the positive effect of the warming on the photosynthesis in winter and the negative effect in summer and autumn, i.e., increased photosynthetic midday depression in summer and autumn, when temperatures were much higher than in winter. Drought treatment increased the midday depression of photosynthesis in summer. Importantly, ∆PRI was significantly correlated with ∆A both under warming and drought, indicating the applicability of ∆PRI for tracking the midday depression of photosynthetic processes. Using PRI and ∆PRI to monitor the variability in photosynthesis could provide a simple method to remotely sense photosynthetic seasonality and midday depression in response to ongoing and future environmental stresses.

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“…UAS have become a viable and cost-effective alternative to manned airborne or satellite remote sensing for precision agriculture, given their ability to collect high spatial resolution data at critical times during the growing season [1,[24][25][26][27]. Moreover, UAS aerial photography allows overlapping imagery to be collected, which is widely used for three-dimensional (3D) image reconstruction and facilitates change analysis [11,[28][29][30][31].…”

Section: Introductionmentioning

confidence: 99%

Poppy Crop Height and Capsule Volume Estimation from a Single UAS Flight

et al. 2017

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Abstract:The objective of this study was to estimate poppy plant height and capsule volume with remote sensing using an Unmanned Aircraft System (UAS). Data were obtained from field measurements and UAS flights over two poppy crops at Cambridge and Cressy in Tasmania. Imagery acquired from the UAS was used to produce dense point clouds using structure from motion (SfM) and multi-view stereopsis (MVS) techniques. Dense point clouds were used to generate a digital surface model (DSM) and orthophoto mosaic. An RGB index was derived from the orthophoto to extract the bare ground spaces. This bare ground space mask was used to filter the points on the ground, and a digital terrain model (DTM) was interpolated from these points. Plant height values were estimated by subtracting the DSM and DTM to generate a Crop Height Model (CHM). UAS-derived plant height (PH) and field measured PH in Cambridge were strongly correlated with R 2 values ranging from 0.93 to 0.97 for Transect 1 and Transect 2, respectively, while at Cressy results from a single flight provided R 2 of 0.97. Therefore, the proposed method can be considered an important step towards crop surface model (CSM) generation from a single UAS flight in situations where a bare ground DTM is unavailable. High correlations were found between UAS-derived PH and poppy capsule volume (CV) at capsule formation stage (R 2 0.74), with relative error of 19.62%. Results illustrate that plant height can be reliably estimated for poppy crops based on a single UAS flight and can be used to predict opium capsule volume at capsule formation stage.

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UAVs challenge to assess water stress for sustainable agriculture

Cited by 438 publications

References 53 publications

On the Use of Unmanned Aerial Systems for Environmental Monitoring

On the Use of Unmanned Aerial Systems for Environmental Monitoring

Photochemical Reflectance Index (PRI) for Detecting Responses of Diurnal and Seasonal Photosynthetic Activity to Experimental Drought and Warming in a Mediterranean Shrubland

Poppy Crop Height and Capsule Volume Estimation from a Single UAS Flight

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