Accurate estimates of land surface energy fluxes and irrigation requirements from UAV-based thermal and multispectral sensors

Peng, Junxiang; Nieto, H.; Andersen, Mathias Neumann; Kørup, Kirsten; Larsen, Ryan Godsk; Morel, Julien; Parsons, David; Zhou, Zhenjiang; Manevski, Kiril

doi:10.1016/j.isprsjprs.2023.03.009

Cited by 21 publications

(4 citation statements)

References 74 publications

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“…In the paper [23], thermal, multispectral, and RGB images obtained from UAVs are used to calculate various parameters related to plant growth and water consumption. Specifically, the study claims to assess the actual canopy Transpiration (Tr), soil Evaporation (E), and EvapoTranspiration (ET) of potato plants grown under different irrigation treatments on sandy soil.…”

Section: Related Workmentioning

confidence: 99%

“…The traditional method of estimating Tr and E using the Two-Source Energy Balance model-Priestley-Taylor equation (TSEB-PT) with satellite-derived Land Surface Temperature (LST) has limitations in accuracy, especially at high spatialtemporal resolutions. The paper in [23] proposes an energy-flux-modeling framework based on the TSEB-PT, leveraging high-resolution thermal and multispectral data collected by UAVs. The research, conducted during drought conditions in 2018 and 2019, recorded diurnal variations of the LST in agricultural fields.…”

Section: Related Workmentioning

confidence: 99%

“…The Normalized Difference Vegetation Index (NDVI) is a widely recognized and extensively employed vegetation metric derived from the NIR to red (R) reflectance [20,21]. This index has long held a prominent position as the standard methodology in RS for the comprehensive assessment of plant health, leaf area index, biomass quantification, plant productivity, and fractional vegetation cover in the agricultural industry [19,22,23].…”

Section: Introductionmentioning

confidence: 99%

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The Uncertainty Assessment by the Monte Carlo Analysis of NDVI Measurements Based on Multispectral UAV Imagery

Khalesi,

Ahmed,

Daponte

et al. 2024

Sensors

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This paper proposes a workflow to assess the uncertainty of the Normalized Difference Vegetation Index (NDVI), a critical index used in precision agriculture to determine plant health. From a metrological perspective, it is crucial to evaluate the quality of vegetation indices, which are usually obtained by processing multispectral images for measuring vegetation, soil, and environmental parameters. For this reason, it is important to assess how the NVDI measurement is affected by the camera characteristics, light environmental conditions, as well as atmospheric and seasonal/weather conditions. The proposed study investigates the impact of atmospheric conditions on solar irradiation and vegetation reflection captured by a multispectral UAV camera in the red and near-infrared bands and the variation of the nominal wavelengths of the camera in these bands. Specifically, the study examines the influence of atmospheric conditions in three scenarios: dry–clear, humid–hazy, and a combination of both. Furthermore, this investigation takes into account solar irradiance variability and the signal-to-noise ratio (SNR) of the camera. Through Monte Carlo simulations, a sensitivity analysis is carried out against each of the above-mentioned uncertainty sources and their combination. The obtained results demonstrate that the main contributors to the NVDI uncertainty are the atmospheric conditions, the nominal wavelength tolerance of the camera, and the variability of the NDVI values within the considered leaf conditions (dry and fresh).

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Uncertainty Assessment by the Monte Carlo Analysis of NDVI Measurements Based on Multispectral UAV Imagery

Khalesi,

Ahmed,

Daponte

et al. 2024

Sensors

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“…With the emergence of unmanned aerial vehicles (UAVs), studies [10][11][12][13][14][15] are being conducted to determine the physicochemical parameters of soil using oblique irradiation of the Earth's surface in order to create conditions for the occurrence of the total (pseudo-total) refraction effect [6,16]. The advantage of this approach is that it allows for estimating the soil parameters directly in the root zone of plants.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Accuracy of the Remote Determination of the Brewster Angle When Measuring Physicochemical Parameters of Soil

Linets,

Bazhenov,

Malygin

et al. 2023

AgriEngineering

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In precision farming technology, the moisture of the soil, its granulometric composition, specific conductivity and a number of other physical and chemical parameters are determined using remote radar sensing. The most important parameters are those measured in the area of the plant root system located well below the “air-surface” boundary. In order to create conditions for the penetration of electromagnetic waves through the “air-surface” interface with a minimum reflection coefficient, the irradiation of the Earth’s surface is carried out obliquely with an angle of incidence close to the Brewster angle. The reflection coefficient, and, consequently, the Brewster angle, depend on the complex dielectric permittivity of the surface soil layer and are not known a priori. To determine the Brewster angle, the usual method is to search for the minimum amplitude of the vertically polarized signal reflected from the surface. Another approach is when the first derivative of the dependence of the modulus of the complex amplitude of a vertically polarized interference wave, taken with respect to the angle of incidence, is set equal to zero. In turn, in real dielectrics such as agricultural soils, the amplitude of the vertically polarized signal reflected from the surface is directly proportional to the reflection coefficient and does not have a pronounced minimum, which reduces the accuracy of the measurements. Based on the solution of the Helmholtz wave equation for a three-layered structure of the propagation medium (air, upper fertile soil layer, soil layer below the groundwater level), a model of the process of forming an interference wave under oblique irradiation of a planar layered dielectric with losses has been developed. Using the developed model, factors influencing the accuracy of determining the Brewster angle have been identified. For the first time, it is proposed to use the phase shift between the oscillations of the interference waves with vertical and horizontal polarization to measure the Brewster angle. A comparative assessment of the accuracy of determining the Brewster angle using known amplitude methods and the proposed phase method has been carried out. The adequacy of the method was experimentally confirmed. Recommendations have been developed for the practical application of the phase method of finding the Brewster angle for assessing the dielectric permittivity of soil and its moisture content.

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Evaluating the performance of the TSEB model for sorghum evapotranspiration estimation using time series UAV imagery

Tunca

2023

Irrig Sci

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Accurate estimates of land surface energy fluxes and irrigation requirements from UAV-based thermal and multispectral sensors

Cited by 21 publications

References 74 publications

The Uncertainty Assessment by the Monte Carlo Analysis of NDVI Measurements Based on Multispectral UAV Imagery

The Uncertainty Assessment by the Monte Carlo Analysis of NDVI Measurements Based on Multispectral UAV Imagery

Evaluation of the Accuracy of the Remote Determination of the Brewster Angle When Measuring Physicochemical Parameters of Soil

Evaluating the performance of the TSEB model for sorghum evapotranspiration estimation using time series UAV imagery

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