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Application of infrared thermography to assess cassava physiology under water deficit condition
摘要： Water deficit stress is a major factor that inhibits the overall growth and development in cassava (Manihot esculenta), leading to decreased storage root yield. We conducted a study to investigate whether thermal sensing could be used to indicate water deficit stress and the health and yield of cassava crops in field. The objective of the study was to use thermal imaging to determine relationship between crop water stress index (CWSI) and physiological changes, and to identify the critical CWSI point in fields of cassava cv. Rayong 9 under well-irrigated and water-deficit conditions. At the time of storage root initiation (85 DAP [day after planting]), thermal imagery was collected and the physiological changes and growth characters were measured prior to storage root harvesting (162 DAP). Thermal infrared imager was used to measure the canopy temperature and CWSI of cassava plants. Net photosynthetic rate (Pn), stomatal conductance (gs) and transpiration rates (Tr) of cassava plants under water deficit conditions for 29 d (114 DAP) were significantly decreased, leading to delayed plant growth as compared to those under well-irrigated conditions. In contrast, air vapor pressure deficit (VPDair) and CWSI in drought-stressed plants were higher than well irrigated plants. High correlations between Tr/gs/Pn and CWSI were observed. The study concludes that CWSI is a sensitive indicator of water deficit stress caused due to stomatal function.
关键词： net photosynthetic rate,crop water stress index,thermal imagery,Cassava,stomatal conductance
更新于2025-09-23 15:21:01
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[IEEE IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium - Yokohama, Japan (2019.7.28-2019.8.2)] IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium - Measuring Leaf Equivalent Water Thickness of Short-Rotation Coppice Willow Canopy Using Terrestrial Laser Scanning
摘要： Accurate measurements of leaf Equivalent Water Thickness (EWT) can help in early detection of vegetation stress. Terrestrial Laser Scanning (TLS) intensity data have the potential to provide 3D estimates of EWT, overcoming the limitations of the 2D estimates provided by remote sensing optical data. Such limitations include the sensors being solar illumination dependent and unable to provide information about the vertical variation in EWT. In this study, intensity data from the Leica P20 and P40 commercial TLS instruments were combined in a Normalized Difference Index (NDI). NDI was used to measure EWT in six short-rotation coppice willow (Salix spp.) plots from different varieties with an average error of 7.3% (R2 = 0.8, RMSE = 0.0011 g cm-2). The effects of wind and senescence of leaves on the accuracy of the EWT estimation were also investigated.
关键词： agricultural crops,ground LiDAR,biomass energy,water stress,Vegetation water content
更新于2025-09-19 17:13:59
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[IEEE 2019 Compound Semiconductor Week (CSW) - Nara, Japan (2019.5.19-2019.5.23)] 2019 Compound Semiconductor Week (CSW) - Buried tunnel junction current injection for InP-based nanomembrane photonic crystal surface emitting lasers on Silicon
摘要： Microwave backscatter from vegetated surfaces is influenced by vegetation structure and vegetation water content (VWC), which varies with meteorological conditions and moisture in the root zone. Radar backscatter observations are used for many vegetation and soil moisture monitoring applications under the assumption that VWC is constant on short timescales. This research aims to understand how backscatter over agricultural canopies changes in response to diurnal differences in VWC due to water stress. A standard water-cloud model and a two-layer water-cloud model for maize were used to simulate the influence of the observed variations in bulk/leaf/stalk VWC and soil moisture on the various contributions to total backscatter at a range of frequencies, polarizations, and incidence angles. The bulk VWC and leaf VWC were found to change up to 30% and 40%, respectively, on a diurnal basis during water stress and may have a significant effect on radar backscatter. Total backscatter time series are presented to illustrate the simulated diurnal difference in backscatter for different radar frequencies, polarizations, and incidence angles. Results show that backscatter is very sensitive to variations in VWC during water stress, particularly at large incidence angles and higher frequencies. The diurnal variation in total backscatter was dominated by variations in leaf water content, with simulated diurnal differences of up to 4 dB in X- through Ku-bands (8.6–35 GHz). This study highlights a potential source of error in current vegetation and soil monitoring applications and provides insights into the potential use for radar to detect variations in VWC due to water stress.
关键词： Agriculture,vegetation water content (VWC),microwaves,hydrology,water stress,diurnal differences,radar,vegetation
更新于2025-09-16 10:30:52
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Four Dimensional Mapping of Vegetation Moisture Content Using Dual-Wavelength Terrestrial Laser Scanning
摘要： Recently, terrestrial laser scanning (TLS) has shown potential in measuring vegetation biochemical traits in three dimensions (3D) by using reflectance derived from backscattered intensity data. The 3D estimates can provide information about the vertical heterogeneity of canopy biochemical traits which affects canopy reflectance but cannot be measured from spaceborne and airborne optical remote sensing data. Leaf equivalent water thickness (EWT), a metric widely used in vegetation health monitoring, has been successfully linked to the normalized difference index (NDI) of near and shortwave infrared wavelengths at the leaf level. However, only two previous studies have linked EWT to NDI at the canopy level in field campaigns. In this study, an NDI consisting of 808 and 1550 nm wavelengths was used to generate 3D EWT estimates at the canopy level in a broadleaf mixed-species tree plot during and after a heatwave. The relative error in EWT estimates was 6% across four different species. Temporal changes in EWT were measured, and the accuracy varied between trees, a factor of the errors in EWT estimates on both dates. Vertical profiles of EWT were generated for six trees and showed vertical heterogeneity and variation between species. The change in EWT vertical profiles during and after the heatwave differed between trees, demonstrating that trees reacted in different ways to the drought condition.
关键词： drought,leaf water content,vegetation,Lidar,water stress
更新于2025-09-11 14:15:04
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Evaluation of the SPARSE Dual-Source Model for Predicting Water Stress and Evapotranspiration from Thermal Infrared Data over Multiple Crops and Climates
摘要： Using surface temperature as a signature of the surface energy balance is a way to quantify the spatial distribution of evapotranspiration and water stress. In this work, we used the new dual-source model named Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) based on the Two Sources Energy Balance (TSEB) model rationale which solves the surface energy balance equations for the soil and the canopy. SPARSE can be used (i) to retrieve soil and vegetation stress levels from known surface temperature and (ii) to predict transpiration, soil evaporation, and surface temperature for given stress levels. The main innovative feature of SPARSE is that it allows to bound each retrieved individual ?ux component (evaporation and transpiration) by its corresponding potential level deduced from running the model in prescribed potential conditions, i.e., a maximum limit if the surface water availability is not limiting. The main objective of the paper is to assess the SPARSE model predictions of water stress and evapotranspiration components for its two proposed versions (the “patch” and “layer” resistances network) over 20 in situ data sets encompassing distinct vegetation and climate. Over a large range of leaf area index values and for contrasting vegetation stress levels, SPARSE showed good retrieval performances of evapotranspiration and sensible heat ?uxes. For cereals, the layer version provided better latent heat ?ux estimates than the patch version while both models showed similar performances for sparse crops and forest ecosystems. The bounded layer version of SPARSE provided the best estimates of latent heat ?ux over different sites and climates. Broad tendencies of observed and retrieved stress intensities were well reproduced with a reasonable difference obtained for most of the points located within a con?dence interval of 0.2. The synchronous dynamics of observed and retrieved estimates underlined that the SPARSE retrieved water stress estimates from Thermal Infra-Red data were relevant tools for stress detection.
关键词： remote-sensing,water stress,model,partition,evapotranspiration
更新于2025-09-09 09:28:46
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Extending the SCOPE model to combine optical reflectance and soil moisture observations for remote sensing of ecosystem functioning under water stress conditions
摘要： A radiative transfer and process-based model, called Soil-Canopy-Observation of Photosynthesis and Energy fluxes (SCOPE), relates remote sensing signals with plant functioning (i.e., photosynthesis and evapotranspiration). Relying on optical remote sensing data, the SCOPE model estimates photosynthesis and evapotranspiration, but these ecosystem-level fluxes may be significantly overestimated if water availability is the primary limiting factor for vegetation. Remedying this shortcoming, additional information from extra sources is needed. In this study, we propose considering water stress in SCOPE by incorporating soil moisture data in the model, besides using satellite optical reflectance observations. A functional link between soil moisture, soil surface resistance, leaf water potential and carboxylation capacity is introduced as an extra element in SCOPE, resulting in a soil moisture integrated version of the model, SCOPE-SM. The modified model simulates additional state variables: (i) vapor pressure (ei), both in the soil pore space and leaf stomata in equilibrium with liquid water potential; (ii) the maximum carboxylation capacity (Vcmax) by a soil moisture dependent stress factor; and (iii) the soil surface resistance (rss) through approximation by a soil moisture dependent hydraulic conductivity. The new approach was evaluated at a Fluxnet site (US-Var) with dominant C3 grasses and covering a wet-to-dry episode from January to August 2004. By using the original SCOPE (version 1.61), we simulated half-hourly time steps of plant functioning via locally measured weather data and time series of Landsat (TM and ETM) imagery. Then, SCOPE-SM was similarly applied to simulate plant functioning for three cases using Landsat imagery: (i) with modeled ei; (ii) with modeled ei and Vcmax; and (iii) with modeled ei, Vcmax, and rss. The outputs of all four simulations were compared to flux tower plant functioning measurements. The results indicate a significant improvement proceeding from the first to the fourth case in which we used both Landsat optical imagery and soil moisture data through SCOPE-SM. Our results show that the combined use of optical reflectance and soil moisture observations has great potential to capture variations of photosynthesis and evapotranspiration during drought episodes. Further, we found that the information contained in soil moisture observations can describe more variations of measured evapotranspiration compared to the information contained in thermal observations.
关键词： SCOPE-SM model,Landsat,Evapotranspiration,Vegetation properties,Water stress,Remote sensing,Soil moisture,Vegetation functioning,Vapor pressure,Photosynthesis,Maximum carboxylation capacity,Soil surface resistance,Reflectance
更新于2025-09-09 09:28:46
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Assessing the Reliability of Thermal and Optical Imaging Techniques for Detecting Crop Water Status under Different Nitrogen Levels
摘要： Efficient management of irrigation water is fundamental in agriculture to reduce the environmental impacts and to increase the sustainability of crop production. The availability of adequate tools and methodologies to easily identify the crop water status in operating conditions is therefore crucial. This work aimed to assess the reliability of indices derived from imaging techniques—thermal indices (Ig (stomatal conductance index) and CWSI (Crop Water Stress Index)) and optical indices (NDVI (Normalized Difference Vegetation Index) and PRI (Photochemical Reflectance Index))—as operational tools to detect the crop water status, regardless the eventual presence of nitrogen stress. In particular, two separate experiments were carried out in a greenhouse, on two spinach varieties (Verdi F1 and SV2157VB), with different microclimatic conditions and under different levels of water and nitrogen application. Statistical analysis based on ANOVA test was carried out to assess the independence of thermal and optical indices from the crop nitrogen status. These imaging indices were successively compared through correlation analysis with reference destructive and non-destructive measurements of crop water status (stomatal conductance, chlorophyll a fluorescence, and leaf and soil water content), and linear regression models of thermal and optical indices versus reference measurements were calibrated. All models were significant (Fisher p-value lower than 0.05), and the highest R2 values (greater than 0.6) were found for the regression models between CWSI and the soil water content, NDVI and the leaf water content, and PRI and the stomatal conductance. Further analysis showed that imaging indices acquired by thermal cameras (especially CWSI) can be used as operational tools to detect the crop water status, since no dependence on plant nitrogen conditions was observed, even when the soil water depletion was very limited. Our results confirmed that imaging indices such as CWSI, NDVI and PRI can be used as operational tools to predict soil water status and to detect drought stress under different soil nitrogen conditions.
关键词： crop water status,crop water stress prediction,optical imaging sensor,thermal camera,spectral imaging index
更新于2025-09-04 15:30:14