This paper reviews the different remote sensing techniques found in the literature to monitor plant water status, allowing farmers to control the irrigation management and to avoid unnecessary ...periods of water shortage and a needless waste of valuable water. The scope of this paper covers a broad range of 77 references published between the years 1981 and 2021 and collected from different search web sites, especially Scopus. Among them, 74 references are research papers and the remaining three are review papers. The different collected approaches have been categorized according to the part of the plant subjected to measurement, that is, soil (12.2%), canopy (33.8%), leaves (35.1%) or trunk (18.9%). In addition to a brief summary of each study, the main monitoring technologies have been analyzed in this review. Concerning the presentation of the data, different results have been obtained. According to the year of publication, the number of published papers has increased exponentially over time, mainly due to the technological development over the last decades. The most common sensor is the radiometer, which is employed in 15 papers (20.3%), followed by continuous-wave (CW) spectroscopy (12.2%), camera (10.8%) and THz time-domain spectroscopy (TDS) (10.8%). Excluding two studies, the minimum coefficient of determination (R2) obtained in the references of this review is 0.64. This indicates the high degree of correlation between the estimated and measured data for the different technologies and monitoring methods. The five most frequent water indicators of this study are: normalized difference vegetation index (NDVI) (12.2%), backscattering coefficients (10.8%), spectral reflectance (8.1%), reflection coefficient (8.1%) and dielectric constant (8.1%).
Macro to micro Konings, Alexandra G.; Rao, Krishna; Steele-Dunne, Susan C.
The New phytologist,
August 2019, Letnik:
223, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Although primarily valued for their suitability for oceanographic applications and soil moisture estimation, microwave remote sensing observations are also sensitive to plant water content (M
w). ...Since M
w depends on both plant water status and biomass, these observations have the potential to be useful for a range of plant drought response studies. In this paper, we introduce the principles behind microwave remote sensing observations to illustrate how they are sensitive to plant water content and discuss the relationship between landscape-scale M
w and common stand-scale metrics, including plant-scale relative water content, live fuel moisture content and leaf water potential. Lastly, we discuss how various sensor types can be leveraged for specific applications depending on the spatio-temporal resolution needed.
Accurate observations of cloud microphysical properties are needed for evaluating and improving the representation of cloud processes in climate models and better estimate of the Earth radiative ...budget. However, large differences are found in current cloud products retrieved from ground‐based remote sensing measurements using various retrieval algorithms. Understanding the differences is an important step to address uncertainties in the cloud retrievals. In this study, an in‐depth analysis of nine existing ground‐based cloud retrievals using ARM remote sensing measurements is carried out. We place emphasis on boundary layer overcast clouds and high level ice clouds, which are the focus of many current retrieval development efforts due to their radiative importance and relatively simple structure. Large systematic discrepancies in cloud microphysical properties are found in these two types of clouds among the nine cloud retrieval products, particularly for the cloud liquid and ice particle effective radius. Note that the differences among some retrieval products are even larger than the prescribed uncertainties reported by the retrieval algorithm developers. It is shown that most of these large differences have their roots in the retrieval theoretical bases, assumptions, as well as input and constraint parameters. This study suggests the need to further validate current retrieval theories and assumptions and even the development of new retrieval algorithms with more observations under different cloud regimes.
Key Points
Large differences exist for cloud properties retrieved from various techniques
These differences are highly related to the algorithm details and inputs
Cloud retrieval uncertainties need to be further understood and quantified
Drought-induced tree mortality events are expected to increase in frequency under climate change. However, monitoring and modeling of tree mortality is limited by the high spatial variability in ...vegetation response to climatic drought stress and lack of physiologically meaningful stress variables that can be monitored at large scales. In this study, we test the hypothesis that relative water content (RWC) estimated by passive microwave remote sensing through vegetation optical depth can be used as an empirical indicator of tree mortality that both integrates variations in plant drought stress and is accessible across large areas. The hypothesis was tested in a recent severe drought in California, USA. The RWC showed a stronger threshold relationship with mortality than climatic water deficit (CWD) – a commonly used mortality indicator – although both relationships were noisy due to the coarse spatial resolution of the data (0.25° or approximately 25 km). In addition, the threshold for RWC was more uniform than that for CWD when compared between Northern and Southern regions of California. A random forests regression (machine learning) with 32 variables describing topography, climate, and vegetation characteristics predicted forest mortality extent i.e. fractional area of mortality (FAM) with satisfactory accuracy-coefficient of determination Rtest2 = 0.66, root mean square error = 0.023. Importantly, RWC was more than twice as important as any other variable in the model in estimating mortality, confirming its strong link to mortality rates. Moreover, RWC showed a moderate ability to aid in forecasting mortality, with a relative importance of RWC measured one year in advance of mortality similar to that of other relevant explanatory variables measured in the mortality year. The results of this study present a promising new approach to estimate drought stress of forests linked to mortality risk.
•Drought-driven tree mortality's link to remotely sensed indicators investigated•Relative water content using satellite-based vegetation optical depth estimated•Relative water content was the best predictor of mortality among 32 variables.
Sentinel-1 Synthetic Aperture Radar (SAR) data have provided an unprecedented opportunity for crop monitoring due to its high revisit frequency and wide spatial coverage. The dual-pol (VV-VH) ...Sentinel-1 SAR data are being utilized for the European Common Agricultural Policy (CAP) as well as for other national projects, which are providing Sentinel derived information to support crop monitoring networks. Among the Earth observation products identified for agriculture monitoring, indicators of vegetation status are deemed critical by end-user communities. In literature, several experiments usually utilize the backscatter intensities to characterize crops. In this study, we have jointly utilized the scattering information in terms of the degree of polarization and the eigenvalue spectrum to derive a new vegetation index from dual-pol (DpRVI) SAR data. We assess the utility of this index as an indicator of plant growth dynamics for canola, soybean, and wheat, over a test site in Canada. A temporal analysis of DpRVI with crop biophysical variables (viz., Plant Area Index (PAI), Vegetation Water Content (VWC), and dry biomass (DB)) at different phenological stages confirms its trend with plant growth dynamics. For each crop type, the DpRVI is compared with the cross and co-pol ratio (σVH0/σVV0) and dual-pol Radar Vegetation Index (RVI = 4σVH0/(σVV0 + σVH0)), Polarimetric Radar Vegetation Index (PRVI), and the Dual Polarization SAR Vegetation Index (DPSVI). Statistical analysis with biophysical variables shows that the DpRVI outperformed the other four vegetation indices, yielding significant correlations for all three crops. Correlations between DpRVI and biophysical variables are highest for canola, with coefficients of determination (R2) of 0.79 (PAI), 0.82 (VWC), and 0.75 (DB). DpRVI had a moderate correlation (R2≳ 0.6) with the biophysical parameters of wheat and soybean. Good retrieval accuracies of crop biophysical parameters are also observed for all three crops.
•Proposed a new dual-pol radar vegetation index for Sentinel-1.•DpRVI follows the phenological trend with plant growth.•Investigated Dop and eigenvalue spectrum of dual-pol data to map crop condition.•DpRVI outperforms VH/VV and RVI for correlations with biophysical parameters.
•A model is proposed to describe the water-heat coupling process during freezing.•Unfrozen water function for saline soil is determined and applied in modeling.•Frozen depth of the saline region is ...predicted based on the coupling analysis.•Finale ice formation and water dynamics are simulated and validated.•Temperature variation hysteresis in soil profile is proved and analysed.
Frozen depth has a great significance for the foundation engineering in cold regions, always showing a high correlation with some attendant engineering phenomena, including water aggregation, frost heave, and salt accumulation. To study the heat-water dynamics and frozen depth characteristics during the freezing process, soils in western Jilin Province of China, a typical seasonal frozen region, were selected for investigation. A coupled heat and water model was proposed to describe the water-heat coupling process during freezing, with full consideration of the unfrozen water variation, the ice layer formation, and the interaction among different elements. Then, the dynamics of the heat-water and frozen depth were simulated based on the boundary conditions of temperature variation with reference to the meteorological data. The in- situ monitoring data from the whole winter were used to analyse the model performance. The results show that water content and temperature data match the test data, and the Root Mean Square Error (RMSE) values of the temperatures (within 2 °C) at different depths were acceptable, indicating that the water-heat dynamics can predict the maximum frozen depth well. In addition, the temperature of the soil profile varies rapidly in the first 60 days of winter, and the frozen depth continues to increase even though the temperature starts to rise after freezing for 80 days. The moisture transfers upwards with the effect of heat flow, and the formation of ice occurred mainly at a depth of 1.5 m. Heat conduction plays an important role in modelling, predominantly leading to the hysteresis in the frozen depth variation during freezing. This new method can provide a reference for water-heat movement and the prediction of the frozen depth during freezing in the saline soil regions.
Drought-induced tree mortality has major impacts on ecosystem carbon and water cycles, and is expected to increase in forests across the globe with climate change. A large body of research in the ...past decade has advanced our understanding of plant water and carbon relations under drought. However, despite intense research, we still lack generalizable, cross-scale indicators of mortality risk. In this Viewpoint, we propose that a more explicit consideration of water pools could improve our ability to monitor and anticipate mortality risk. Specifically, we focus on the relative water content (RWC), a classic metric in plant water relations, as a potential indicator of mortality risk that is physiologically relevant and integrates different aspects related to hydraulics, stomatal responses and carbon economy under drought. Measures of plant water content are likely to have a strong mechanistic link with mortality and to be integrative, threshold-prone and relatively easy to measure and monitor at large spatial scales, and may complement current mortality metrics based on water potential, loss of hydraulic conductivity and nonstructural carbohydrates. We discuss some of the potential advantages and limitations of these metrics to improve our capacity to monitor and predict drought-induced tree mortality.
A noninvasive, immediate, and convenient method for assessing muscle tissue status during exercise-induced muscle damage (EIMD) has not been established. This study was designed to assess and ...determine parameters suitable for measuring EIMD after eccentric exercise, using multi-frequency bioimpedance analysis (BIA). Thirty-five young male participants performed dumbbell exercises with their left arm, and their BIA parameters were measured at various time points up to 168 h post exercise using a multi-frequency BIA device. At all-time points, intra and extracellular water content was greater in the left arm than in the right arm, whereas the impedance, reactance, resistance, and phase angle were lower in the left arm than in the right arm. Established EIMD indices, such as maximal isometric voluntary contraction, were measured and used in correlational analyses. Only reactance was correlated with biomarkers, indicating muscle damage (r = − 0.56 to − 0.49). Furthermore, reactance was found to correlate well with indirect indicators of EIMD, suggesting that it may be a suitable marker for evaluating EIMD. However, the relationship with the limited evaluation indices employed in this study is constrained. Future studies should investigate the correlation between reactance and direct damage indicators, such as structural damage, observed in biopsies.
Droughts in a warming climate have become more common and more extreme, making understanding forest responses to water stress increasingly pressing. Analysis of water stress in trees has long focused ...on water potential in xylem and leaves, which influences stomatal closure and water flow through the soil‐plant‐atmosphere continuum. At the same time, changes of vegetation water content (VWC) are linked to a range of tree responses, including fluxes of water and carbon, mortality, flammability, and more. Unlike water potential, which requires demanding in situ measurements, VWC can be retrieved from remote sensing measurements, particularly at microwave frequencies using radar and radiometry. Here, we highlight key frontiers through which VWC has the potential to significantly increase our understanding of forest responses to water stress. To validate remote sensing observations of VWC at landscape scale and to better relate them to data assimilation model parameters, we introduce an ecosystem‐scale analog of the pressure–volume curve, the non‐linear relationship between average leaf or branch water potential and water content commonly used in plant hydraulics. The sources of variability in these ecosystem‐scale pressure‐volume curves and their relationship to forest response to water stress are discussed. We further show to what extent diel, seasonal, and decadal dynamics of VWC reflect variations in different processes relating the tree response to water stress. VWC can also be used for inferring belowground conditions—which are difficult to impossible to observe directly. Lastly, we discuss how a dedicated geostationary spaceborne observational system for VWC, when combined with existing datasets, can capture diel and seasonal water dynamics to advance the science and applications of global forest vulnerability to future droughts.
Changes of vegetation water content (VWC) are linked to a range of tree responses to drought, including fluxes of water and carbon, mortality, flammability, and more, and can be retrieved from microwave remote sensing measurements. We highlight key frontiers through which remotely sensed VWC has the potential to significantly increase our understanding of forest responses to water stress. We argue that separate consideration of diel, seasonal, and decadal timescales can facilitate interpretation of VWC measurements for different process studies, and that VWC observations can be useful for constraining belowground water uptake. To link remotely sensed VWC estimates to plant hydraulic models, the utility and interpretation of ecosystem‐scale pressure‐volume curves are discussed.
PDF
