Estimation of olive evapotranspiration using multispectral and thermal sensors placed aboard an unmanned aerial vehicle

Ortega-Farías, Samuel; Ortega-Salazar, Samuel; Poblete, Tomas; Poblete-Echeverría, Carlos; Zúñiga, María del Carmén; Sepulveda-Reyes, D.; Kiliç, Ayşe; Allen, Richard G.

doi:10.17660/actahortic.2017.1150.1

Cited by 6 publications

(4 citation statements)

References 22 publications

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“…UASs are being increasingly utilised to acquire multi-spectral and thermal imagery to compute ET at an unprecedented spatial resolution [270,271]. Using high-resolution images, filtering the shadowed-pixel is possible, which showed significant improvement in the estimation of ET in grapevine [101].…”

Section: Evapotranspirationmentioning

confidence: 99%

“…Using high-resolution images, filtering the shadowed-pixel is possible, which showed significant improvement in the estimation of ET in grapevine [101]. Using high-resolution thermal and/or multispectral imagery, ET has been derived for horticultural crops, such as grapevines [270] and olives [271]. The seasonal monitoring of ET c at high spatial and temporal resolutions is of high importance for precision irrigation of horticultural crops in the future [259].…”

Section: Evapotranspirationmentioning

confidence: 99%

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A Review of Current and Potential Applications of Remote Sensing to Study the Water Status of Horticultural Crops

Gautam

Pagay

2020

Agronomy

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With increasingly advanced remote sensing systems, more accurate retrievals of crop water status are being made at the individual crop level to aid in precision irrigation. This paper summarises the use of remote sensing for the estimation of water status in horticultural crops. The remote measurements of the water potential, soil moisture, evapotranspiration, canopy 3D structure, and vigour for water status estimation are presented in this comprehensive review. These parameters directly or indirectly provide estimates of crop water status, which is critically important for irrigation management in farms. The review is organised into four main sections: (i) remote sensing platforms; (ii) the remote sensor suite; (iii) techniques adopted for horticultural applications and indicators of water status; and, (iv) case studies of the use of remote sensing in horticultural crops. Finally, the authors' view is presented with regard to future prospects and research gaps in the estimation of the crop water status for precision irrigation.

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Section: Evapotranspirationmentioning

confidence: 99%

Section: Evapotranspirationmentioning

confidence: 99%

A Review of Current and Potential Applications of Remote Sensing to Study the Water Status of Horticultural Crops

Gautam

Pagay

2020

Agronomy

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“…precision agriculture applications (Berni et al 2009; Brosy et al 2017; Zhang and Kovacs 2012; Candiago et al 2015; Reineman et al 2013; Link, Senner, and Claupein 2013; Lelong et al 2008; Turner et al 2014; Stefano et al 2017; Vázquez-Tarrío et al 2017). However, studies using UAS-based TIR sensors to map LST and subsequently derive surface turbulent heat fluxes are still rare (Hoffmann et al 2016b; Ortega-Farías et al 2017; Ortega-Farías et al 2016; Brenner et al 2017). In view of the ease of use of UAS and the flexibility in mission planning and operation, simple approaches that facilitate operational ET monitoring in near real time would perfectly complete the asset of UAS.…”

Section: Introductionmentioning

confidence: 99%

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

Brenner

Zeeman

Bernhardt

et al. 2018

International Journal of Remote Sensing

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Spatially distributed high-resolution data of land surface temperature (LST) and evapotranspiration (ET) are important information for crop water management and other applications in the agricultural sector. While satellite data can provide LST high-resolution data of 100 m, the current development of unmanned aerial systems (UAS) and affordable low-weight thermal cameras allows LST and subsequent ET to be derived at resolutions down to centimetre scale.In this study, UAS-based images in the thermal infrared (TIR) and visible spectral range were collected over a managed temperate grassland in July 2016 at the Terrestrial Environmental Observatories Networks TERENO preAlpine observatory site at Fendt, Germany. The UAS set-up included a lightweight thermal camera (Optris Pi Lightweight) and a regular digital camera (Sony α 6000) that allowed for the acquisition of thermal and optical images with a ground resolution of 5 cm and 1 cm, respectively. Three TIR-based ET models of different complexity were applied and the resulting ET estimates were compared to the Eddy covariance (EC) observations of turbulent energy fluxes and also to the evaporative fraction. While the Deriving Atmosphere Turbulent Transport Useful To Dummies Using Temperature (DATTUTDUT) model and the Triangle Method belong to the group of simpler contextual models, the Two-Source Energy Balance (TSEB) model incorporates a more physically based formulation of the surface energy balance. In addition to the comparison of UAS-based estimates of latent heat fluxes to EC observations, the effect of the spatial resolution of the model imagery input on the modelled results was analysed by running the models with imagery from the native resolution of the acquired images to resolutions that were aggregated up to 30 m.The results show that both contextual models are sensitive to the input image resolution and that the agreement with the EC observations improves with increasing image resolution. The TSEB model assumes that LST pixels represent a mixed signal of the soil and canopy components, thus an image resolution coarse enough to ensure this assumption should be chosen. However, with the exception of the native image resolution of 5 cm, we found no effect of image resolution on the spatially weighted mean TSEB estimates.For the studied grassland, the comparison of model estimates with EC observations indicates that all three models are able to reproduce observed energy fluxes with comparable accuracy with mean absolute errors of ET between 20 and 40 W m−2. The TSEB model showed larger deviations from the reference observations under cloudy conditions with rapid fluctuations of LST within the 30 min averaging period for EC. The two contextual models yielded similar results for most of the flights. The good performance of the DATTUTDUT model, which had the lowest input requirements of the three models, is especially promising in view of the application of UAS for routine near-real-time ET monitoring.

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“…A linear regression model between Kc and the Normalized Difference Vegetation Index (NDVI) demonstrated the ability to estimate tree-level ET with a coefficient of determination (R 2 ) of 0.91 and mean absolute error (MAE) of 0.39 mm per day. Ortega-Farías et al [38] investigated ET in olive orchard based on multispectral and thermal sensors on a UAV, along with the remote sensing energy balance (RSEB) algorithm. The results indicated a 13% overestimation of ET by RSEB compared to the eddy covariance (EC) method, with a root mean square error (RMSE) and average absolute error of 0.43 mm per day.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Evaporation and Drought Stress of Pistachio Plant Using UAV Multispectral Images and a Surface Energy Balance Approach

Khormizi,

Malamiri,

Ferreira

2024

Horticulturae

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Water scarcity is a critical abiotic stress factor for plants in arid and semi-arid regions, impacting crop development and production yield and quality. Monitoring water stress at finer scales (e.g., farm and plant), requires multispectral imagery with thermal capabilities at centimeter resolution. This study investigates drought stress in pistachio trees in a farm located in Yazd province, Iran, by using Unmanned Aerial Vehicle (UAV) images to quantify evapotranspiration and assess drought stress in individual trees. Images were captured on 10 July 2022, using a Matrix 300 UAV with a MicaSense Altum multispectral sensor. By employing the Surface Energy Balance Algorithm for Land (SEBAL), actual field evapotranspiration was accurately calculated (10 cm spatial resolution). Maps of the optimum crop coefficient (Kc) were developed from the Normalized Difference Vegetation Index (NDVI) based on standard evapotranspiration using the Food and Agriculture Organization (FAO) 56 methodology. The comparison between actual and standard evapotranspiration allowed us to identify drought-stressed trees. Results showed an average and maximum daily evaporation of 4.3 and 8.0 mm/day, respectively, in pistachio trees. The real crop coefficient (Kc) for pistachio was 0.66, contrasting with the FAO 56 standard of 1.17 due to the stress factor (Ks). A significant correlation was found between Kc and NDVI (R2 = 0.67, p < 0.01). The regression model produced a crop coefficient map, valuable to support precise irrigation management and drought prevention, considering the heterogeneity at the farm scale.

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Estimation of olive evapotranspiration using multispectral and thermal sensors placed aboard an unmanned aerial vehicle

Cited by 6 publications

References 22 publications

A Review of Current and Potential Applications of Remote Sensing to Study the Water Status of Horticultural Crops

A Review of Current and Potential Applications of Remote Sensing to Study the Water Status of Horticultural Crops

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

Estimation of Evaporation and Drought Stress of Pistachio Plant Using UAV Multispectral Images and a Surface Energy Balance Approach

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