Assessing Crop Water Stress Index of Citrus Using In-Situ Measurements, Landsat, and Sentinel-2 Data
04 Mar 2021-International Journal of Remote Sensing (Taylor & Francis)-Vol. 42, Iss: 5, pp 1893-1916
TL;DR: With the advent of optical sensors, thermal-based indicators can be retrieved at multiscale levels from handheld devices to satellite platforms, providing a low-cost method to mirror plant water as mentioned in this paper.
Abstract: With the advent of optical sensors, thermal-based indicators can be retrieved at multiscale levels from handheld devices to satellite platforms, providing a low-cost method to mirror plant water st...
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TL;DR: In this paper, the water requirement of mature orange trees (Citrus sinensis (L) Osbeck, cv Tarocco Ippolito) by identifying standard evapotranspiration rate and crop coefficients (single and dual) was investigated.
14 citations
TL;DR: A self-organizing map (SOM) based model to predict the CWSI using microclimatic variables, namely air temperature, canopy temperature and relative humidity, indicated that the presence of zero CWSI values in a significant proportion in the dataset impacted the model prediction performance at low CWSI.
11 citations
TL;DR: In this paper , the authors evaluated the utility of optical and thermal infrared UAV imagery, in combination with a random forest machine-learning algorithm, to estimate the maize foliar temperature and stomatal conductance as indicators of potential crop water stress and moisture content over the entire phenological cycle.
Abstract: Climatic variability and extreme weather events impact agricultural production, especially in sub-Saharan smallholder cropping systems, which are commonly rainfed. Hence, the development of early warning systems regarding moisture availability can facilitate planning, mitigate losses and optimise yields through moisture augmentation. Precision agricultural practices, facilitated by unmanned aerial vehicles (UAVs) with very high-resolution cameras, are useful for monitoring farm-scale dynamics at near-real-time and have become an important agricultural management tool. Considering these developments, we evaluated the utility of optical and thermal infrared UAV imagery, in combination with a random forest machine-learning algorithm, to estimate the maize foliar temperature and stomatal conductance as indicators of potential crop water stress and moisture content over the entire phenological cycle. The results illustrated that the thermal infrared waveband was the most influential variable during vegetative growth stages, whereas the red-edge and near-infrared derived vegetation indices were fundamental during the reproductive growth stages for both temperature and stomatal conductance. The results also suggested mild water stress during vegetative growth stages and after a hailstorm during the mid-reproductive stage. Furthermore, the random forest model optimally estimated the maize crop temperature and stomatal conductance over the various phenological stages. Specifically, maize foliar temperature was best predicted during the mid-vegetative growth stage and stomatal conductance was best predicted during the early reproductive growth stage. Resultant maps of the modelled maize growth stages captured the spatial heterogeneity of maize foliar temperature and stomatal conductance within the maize field. Overall, the findings of the study demonstrated that the use of UAV optical and thermal imagery, in concert with prediction-based machine learning, is a useful tool, available to smallholder farmers to help them make informed management decisions that include the optimal implementation of irrigation schedules.
9 citations
TL;DR: In this article, the authors developed and tested a simple methodology for CO2 emission retrieval applied to hyperspectral PRISMA data, which was applied to two test cases relating to the LUSI volcanic area and the Solfatara area in the caldera of Campi Flegrei (Italy).
Abstract: The aim of this work is to develop and test a simple methodology for CO2 emission retrieval applied to hyperspectral PRISMA data. Model simulations are used to infer the best SWIR channels for CO2 retrieval purposes, the weight coefficients for a Continuum Interpolated Band Ratio (CIBR) index calculation, and the factor for converting the CIBR values to XCO2 (ppm) estimations above the background. This method has been applied to two test cases relating to the LUSI volcanic area (Indonesia) and the Solfatara area in the caldera of Campi Flegrei (Italy). The results show the capability of the method to detect and estimate CO2 emissions at a local spatial scale and the potential of PRISMA acquisitions for gas retrieval. The limits of the method are also evaluated and discussed, indicating a satisfactory application for medium/strong emissions and over soils with a reflectance greater than 0.1.
9 citations
TL;DR: In this article, a random forest model was developed using sample data derived from meteorological measurements including air temperature, relative humidity, wind speed, and photosynthetic active radiation (Par) to predict the lower baseline (Twet) and upper baseline (Tdry) canopy temperatures for Chinese Brassica from 27 November to 31 December 2020 (E1) and from 25 May to 20 June 2021 (E2).
Abstract: The determination of crop water status has positive effects on the Chinese Brassica industry and irrigation decisions. Drought can decrease the production of Chinese Brassica, whereas over-irrigation can waste water. It is desirable to schedule irrigation when the crop suffers from water stress. In this study, a random forest model was developed using sample data derived from meteorological measurements including air temperature (Ta), relative humidity (RH), wind speed (WS), and photosynthetic active radiation (Par) to predict the lower baseline (Twet) and upper baseline (Tdry) canopy temperatures for Chinese Brassica from 27 November to 31 December 2020 (E1) and from 25 May to 20 June 2021 (E2). Crop water stress index (CWSI) values were determined based on the predicted canopy temperature and used to assess the crop water status. The study demonstrated the viability of using a random forest model to forecast Twet and Tdry. The coefficients of determination (R2) in E1 were 0.90 and 0.88 for development and 0.80 and 0.77 for validation, respectively. The R2 values in E2 were 0.91 and 0.89 for development and 0.83 and 0.80 for validation, respectively. Our results reveal that the measured and predicted CWSI values had similar R2 values related to stomatal conductance (~0.5 in E1, ~0.6 in E2), whereas the CWSI showed a poor correlation with transpiration rate (~0.25 in E1, ~0.2 in E2). Finally, the methodology used to calculate the daily CWSI for Chinese Brassica in this study showed that both Twet and Tdry, which require frequent measuring and design experiment due to the trial site and condition changes, have the potential to simulate environmental parameters and can therefore be applied to conveniently calculate the CWSI.
9 citations
References
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TL;DR: The Surface Energy Balance Algorithm for Land (SEBAL) as mentioned in this paper estimates the spatial variation of most essential hydro-meteorological parameters empirically, and requires only field information on short wave atmospheric transmittance, surface temperature and vegetation height.
2,628 citations
TL;DR: In this paper, a crop water stress index (CWSI) was calculated using infrared thermometry, along with wet and dry-bulb air temperatures and an estimate of net radiation.
Abstract: Canopy temperatures, obtained by infrared thermometry, along with wet- and dry-bulb air temperatures and an estimate of net radiation were used in equations derived from energy balance considerations to calculate a crop water stress index (CWSI). Theoretical limits were developed for the canopy air temperature difference as related to the air vapor pressure deficit. The CWSI was shown to be equal to 1 - E/Ep, the ratio of actual to potential evapotranspiration obtained from the Penman-Monteith equation. Four experimental plots, planted to wheat, received postemergence irrigations at different times to create different degrees of water stress. Pertinent variables were measured between 1340 and 1400 each day (except some weekends). The CWSI, plotted as a function of time, closely paralleled a plot of the extractable soil water in the 0- to 1.1-m zone. The usefulness and limitations of the index are discussed.
1,642 citations
TL;DR: METRIC uses as its foundation the pioneering SEBAL energy balance process developed in The Netherlands by Bastiaanssen, where the near-surface temperature gradients are an indexed function of radiometric surface temperature, thereby eliminating the need for absolutely accurate surface temperature and theneed for air-temperature measurements.
Abstract: Mapping evapotranspiration at high resolution with internalized calibration (METRIC) is a satellite-based image-processing model for calculating evapotranspiration (ET) as a residual of the surface energy balance. METRIC uses as its foundation the pioneering SEBAL energy balance process developed in The Netherlands by Bastiaanssen, where the near-surface temperature gradients are an indexed function of radiometric surface temperature, thereby eliminating the need for absolutely accurate surface temperature and the need for air-temperature measurements. The surface energy balance is internally calibrated using ground-based reference ET to reduce computational biases inherent to remote sensing-based energy balance and to provide congruency with traditional methods for ET. Slope and aspect functions and temperature lapsing are used in applications in mountainous terrain. METRIC algorithms are designed for relatively routine application by trained engineers and other technical professionals who possess a fami...
1,570 citations
TL;DR: The spectral characteristics of vegetation are introduced and the development of VIs are summarized, discussing their specific applicability and representativeness according to the vegetation of interest, environment, and implementation precision.
Abstract: Vegetation Indices (VIs) obtained from remote sensing based canopies are quite simple and effective algorithms for quantitative and qualitative evaluations of vegetation cover, vigor, and growth dynamics, among other applications These indices have been widely implemented within RS applications using different airborne and satellite platforms with recent advances using Unmanned Aerial Vehicles (UAV) Up to date, there is no unified mathematical expression that defines all VIs due to the complexity of different light spectra combinations, instrumentation, platforms, and resolutions used Therefore, customized algorithms have been developed and tested against a variety of applications according to specific mathematical expressions that combine visible light radiation, mainly green spectra region, from vegetation, and nonvisible spectra to obtain proxy quantifications of the vegetation surface In the real-world applications, optimization VIs are usually tailored to the specific application requirements coupled with appropriate validation tools and methodologies in the ground The present study introduces the spectral characteristics of vegetation and summarizes the development of VIs and the advantages and disadvantages from different indices developed This paper reviews more than 100 VIs, discussing their specific applicability and representativeness according to the vegetation of interest, environment, and implementation precision Predictably, research, and development of VIs, which are based on hyperspectral and UAV platforms, would have a wide applicability in different areas
1,190 citations
TL;DR: In this paper, several experiments involving the measurement of foliage-air temperature differentials (TF-TA) and air vapor pressure deficits (VPD) were conducted on squash, alfalfa, and soybean crops at Tempe and Mesa, Arizona; Manhattan, Kansas; Lincoln, Nebraska; St Paul, Minnesota; and Fargo, North Dakota.
1,094 citations