Retrieving Leaf and Canopy Water Content of Winter Wheat Using Vegetation Water Indices

Quantification of vegetation parameters such as Vegetation Optical Depth (VOD) and Vegetation Water Content (VWC) can be used for better irrigation management, yield forecasting, and soil moisture estimation. Since VOD is directly related to vegetation water content and canopy structure, it can be used as an indicator for VWC. Over the past few decades, optical and passive microwave satellite data have mostly been used to monitor VWC. However, recent research is using active data to monitor VOD and VWC benefitting from their high spatial and temporal resolution.Attenuation of the microwave signal through the vegetation layer is parametrized by the VOD. VOD is assumed to be linearly related to VWC with the proportionality constant being an empirical parameter b. For a given wavelength and polarization, b is assumed static and only parametrized as a function of vegetation type. The hypothesis of this study is that the VOD is not similar for dry and wet vegetation and the static linear relationship between attenuation and vegetation water content is a simplification of reality.The aim of this research is to understand the effect of surface canopy water on VOD estimation and the relationship between VOD and vegetation water content during the growing season of a corn canopy. In addition to studying the dependence of VOD on bulk VWC for dry and wet vegetation, the effect of different factors, such as different growth stages and internal vegetation water content is investigated using time series analysis.A field experiment was conducted in Florida, USA, for a full growing season of sweet corn. The corn field was scanned every 30 minutes with a truck-mounted, fully polarimetric, L-band radar. Pre-dawn vegetation water content was measured using destructive sampling three times a week for a full growing season. VWC could therefore be analyzed by constituent (leaf, stem, ear) or by height. Meteorological data, surface canopy water (dew or interception), and soil moisture were measured every 15 minutes for the entire growing season.The methodology of Vreugdenhil et al.&#160; [1], developed by TU Wien for ASCAT data, was adapted to present a new technique to estimate VOD from single-incidence angle backscatter data in each polarization. The results showed that the effect of surface canopy water on the VOD estimation increased by vegetation biomass accumulation and the effect was higher in the VOD estimated from the co-pol compared with the VOD estimated from the cross-pol.&#160;Moreover, the surface canopy water considerably affected the regression coefficient values (b-factor) of the linear relationship between VOD and VWC from dry and wet vegetation. This finding suggests that considering a similar b-factor for the dry and the wet vegetation will introduce errors in soil moisture retrievals. Furthermore, it highlights the importance of considering canopy wetness conditions when using tau-omega.<ul><li>[1] Vreugdenhil,W. A. Dorigo,W.Wagner, R. A. De Jeu, S. Hahn, andM. J. VanMarle, &#8220;Analyzing the vegetation parameterization in the TU-Wien ASCAT soil moisture retrieval,&#8221; IEEE Transactions on Geoscience and Remote Sensing, vol. 54, pp. 3513&#8211;3531, 2016</li> </ul>

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Testing the Relevance of Daily MODIS Data to Monitor Mediterranean Shrubland Canopy Water Content with Temporal Cross-Correlation Analyses

International Journal of Agricultural and Environmental Information Systems ◽

10.4018/jaeis.2013010101 ◽

2013 ◽

Vol 4 (1) ◽

pp. 1-19 ◽

Cited By ~ 2

Author(s):

Carole Delenne ◽

Jean-Stéphane Bailly ◽

Michel Deshayes

Keyword(s):

Water Content ◽

Forest Fire ◽

Fire Hazard ◽

Statistical Tests ◽

Delay Effect ◽

Field Surveys ◽

Modis Data ◽

Mediterranean Shrubland ◽

Canopy Water ◽

Water Indices

Drought alert systems for forest fire prevention often rely on vegetation water content (VWC) monitoring which is a key parameter in forest fire hazard. In southern France, VWC is now monitored through regular field surveys. Thanks to the theoretical sensitivity of shortwave infrared reflectance to VWC, MODIS satellite data are potentially able to monitor VWC depending on plant species VWC magnitude. In this paper, a specific statistical approach based on temporal cross-correlations is developed in order to test the correlation between two MODIS water indices and VWC measurements coming from field surveys. This test assesses the ability of daily MODIS data to monitor Mediterranean shrubland canopy water content and detect any delay effect between MODIS and field survey temporal series. Statistical tests are carried out for 29 sites containing 18 dominant shrubland Mediterranean species. 67% and 54% of significant correlation were found using respectively the NDII and NDWI indices from MODIS data. Correlation were found low with a dominant negative delay effect, i.e., with a MODIS signal that reacts a few days after the field VWC. Test results show that, even if deeper pre-processing of MODIS data may be required, site soil, site vegetation cover, and heterogeneity at MODIS pixel scale, as well as species VWC sensitivity make correlation between field VWC and MODIS water indices non univoque and highly variable. Many obstacles are still to overcome, for an accurate monitoring of Mediterranean shrubland canopy water content using MODIS daily data.

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Remote Estimation of Leaf and Canopy Water Content in Winter Wheat with Different Vertical Distribution of Water-Related Properties

Remote Sensing ◽

10.3390/rs70404626 ◽

2015 ◽

Vol 7 (4) ◽

pp. 4626-4650 ◽

Cited By ~ 17

Author(s):

Shishi Liu ◽

Yi Peng ◽

Wei Du ◽

Yuan Le ◽

Lu Li

Keyword(s):

Winter Wheat ◽

Vertical Distribution ◽

Water Content ◽

Remote Estimation ◽

Canopy Water

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Association of biomass production and canopy spectral reflectance indices in winter wheat

Canadian Journal of Plant Science ◽

10.4141/cjps08137 ◽

2009 ◽

Vol 89 (3) ◽

pp. 485-496 ◽

Cited By ~ 5

Author(s):

B. Prasad ◽

M. A. Babar ◽

B. F. Carver ◽

W. R. Raun ◽

A. R. Klatt

Keyword(s):

Winter Wheat ◽

Grain Yield ◽

Water Content ◽

Biomass Production ◽

Spectral Reflectance ◽

Water Based ◽

Canopy Spectral Reflectance ◽

Reflectance Indices ◽

Canopy Water ◽

Spectral Reflectance Indices

Increased biomass production could be an important criterion for future grain yield improvement in wheat (Triticum aestivum L.). Quick assessment of genetic variations for biomass production may become a useful tool for wheat breeders. The potential of using canopy spectral reflectance indices (SRI) to assess genetic variation for biomass production in winter wheat was evaluated. Three experiments were conducted for 2 yr (2003-2004 and 2004-2005) at Oklahoma State University, Stillwater, OK. The first experiment consisted of 25 winter wheat cultivars, and the other two experiments contained two sets of 25 F4:6 and F4:7 recombinant inbred lines from two crosses developed by breeding programs in the great plains of the United States of America. Three groups of SRI (vegetation-based, pigment-based, and water-based) were tested for their ability to assess biomass production at three growth stages (booting, heading, and grainfilling). The water index and the normalized water indices gave stronger genetic correlations (P < 0.01) and linear relationship for biomass production compared with the vegetation-based and pigment-based indices. The strong association of water-based indices with biomass was related to the canopy water content of the genotypes. Canopy water content was significantly (P < 0.05) correlated with biomass production. A strong positive association (P < 0.05) of grain yield and dry biomass was observed at the heading and grainfilling stages. Our study demonstrated the potential of using water-based SRI as a breeding tool to estimate genetic variability and identify genotypes with higher biomass production, and could eventually help to achieve higher grain yield in winter wheat. Key words: Wheat; biomass; grain yield; spectral reflectance index

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Reconstructing Continuous Vegetation Water Content To Understand Sub-daily Backscatter Variations

10.5194/hess-2021-459 ◽

2021 ◽

Author(s):

Paul C. Vermunt ◽

Susan C. Steele-Dunne ◽

Saeed Khabbazan ◽

Jasmeet Judge ◽

Nick C. van de Giesen

Keyword(s):

Soil Moisture ◽

Water Content ◽

Water Cycle ◽

Water Dynamics ◽

High Temporal Resolution ◽

Daily Variations ◽

Vegetation Water Content ◽

Dew Formation ◽

Vegetation Water ◽

Canopy Water

Abstract. Microwave observations are sensitive to vegetation water content (VWC). Consequently, the increasing temporal and spatial resolution of spaceborne microwave observations creates a unique opportunity to study vegetation water dynamics and its role in the diurnal water cycle. However, we currently have a limited understanding of sub-daily variations in VWC and how they affect passive and active microwave observations. This is partly due to the challenges associated with measuring internal VWC for validation, particularly non-destructively and at timescales of less than a day. In this study, we aimed to (1) use field sensors to reconstruct diurnal and continuous records of internal VWC of corn, and (2) use these records to interpret the sub-daily behaviour of a 10-day time series of polarimetric L-band backscatter with high temporal resolution. Sub-daily variations of internal VWC were calculated based on the cumulative difference between estimated transpiration and sap flow rates at the base of the stems. Destructive samples were used to constrain the estimates and for validation. The inclusion of continuous surface canopy water estimates (dew or interception) and surface soil moisture allowed us to attribute hour-to-hour backscatter dynamics to either internal VWC, surface canopy water or soil moisture variations. Our results showed that internal VWC varied with 10–20 % during the day in non-stressed conditions, and the effect on backscatter was significant. Diurnal variations of internal VWC and nocturnal dew formation affected vertically polarized backscatter most. Moreover, on a typical dry day, backscatter variations were 1.5 (HH-pol) to 3 (VV-pol) times more sensitive to VWC than to soil moisture. These results demonstrate that radar observations have the potential to provide unprecedented insight into the role of vegetation water dynamics in land-atmosphere interactions at sub-daily timescales.

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Continuous observation of canopy water content changes with GPS sensors

10.5194/egusphere-egu21-15551 ◽

2021 ◽

Author(s):

Vincent Humphrey ◽

Brian L. Dorsey ◽

Christian Frankenberg

Keyword(s):

Water Content ◽

Liquid Water ◽

Large Scale ◽

Climatic Conditions ◽

Leaf Water ◽

Global Navigation Satellite Systems ◽

Leaf Water Content ◽

Vegetation Water ◽

Canopy Water

Canopy water content is a direct indicator of vegetation water use and hydraulic stress, reflecting how ecosystems respond and adapt to droughts and heatwaves. It represents an interesting target for Earth system models which attempt to predict the response and resilience of the vegetation in the face of changing climatic conditions. So far, in-situ estimates of vegetation water content often rely on infrequent and time-consuming samplings of leaf water content, which are not necessarily representative of the canopy scale. On the other hand, several satellite techniques have demonstrated a promising potential for monitoring vegetation optical depth and water content, but these large-scale measurements are still difficult to reference against sparse in-situ level observations.Here, we present an experimental technique based on Global Navigation Satellite Systems (GNSS) to bridge this persisting scale gap. Because GNSS microwave signals are obstructed and scattered by vegetation and liquid water, placing a GNSS sensor in a forest and measuring changes in signal quality can provide continuous information on canopy water content and forest structure. We demonstrate that variations in GNSS signal attenuation reflect the distribution of biomass density and liquid water in the canopy, consistent with ancillary relative leaf water content measurements, and can be monitored continuously. Of particular interest, this technique can resolve diurnal variations in canopy water content at sub-hourly time steps. The few rainfall events captured during the 8-months observational record also suggest that canopy water interception can be monitored at 5 minutes intervals. We discuss future strategies and requirements for deploying such off-the-shelf passive bistatic radar systems at existing FluxNet sites.

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Effects of sub-daily internal and external canopy water fluctuations on radar backscatter

10.5194/egusphere-egu2020-13128 ◽

2020 ◽

Author(s):

Paul Vermunt ◽

Susan Steele-Dunne ◽

Saeed Khabbazan ◽

Jasmeet Judge ◽

Leila Guerriero

Keyword(s):

Soil Moisture ◽

The Netherlands ◽

Water Content ◽

Growing Season ◽

Agricultural Crop ◽

Radar Backscatter ◽

Vegetation Water Content ◽

Vegetation Water ◽

Canopy Water ◽

Daily Patterns

Radar observations of vegetated surfaces are highly affected by water in the soil and canopy. Consequently, radar has been used to monitor surface soil moisture for decades now. In addition, radar has been proven a useful tool for monitoring agricultural crop growth and development and forest fuel load estimation, as a result of the sensitivity of backscatter to vegetation water content (VWC). These current applications are based on satellite revisit periods of days to weeks. However, with future satellite constellations and geosynchronous radar missions, such as ESA&#8217;s Earth Explorer candidate mission HydroTerra, we will be able to monitor soil and vegetation multiple times per day. This opens up opportunities for new applications.Examples could be (1) early detection of water stress in vegetation through anomalies in daily cycles of VWC, and (2) spatio-temporal estimations of rainfall interception, an important part of the water balance. However, currently, we lack the knowledge to physically understand sub-daily patterns in backscatter. Hence, the aim of our research is to understand the effect of water-related factors on sub-daily patterns of radar backscatter of a growing corn canopy.Two intensive field campaigns were conducted in Florida (2018) and The Netherlands (2019). During both campaigns, soil moisture, external canopy water (dew, interception), soil water potential, and weather conditions were monitored every 15 minutes for the entire growing season. In addition, regular destructive sampling was performed to measure seasonal and sub-daily variations of vegetation water content. In Florida, hourly field scans were made with a truck-mounted polarimetric L-band scatterometer. In The Netherlands, these measurements were extended with X- and C-band frequencies.Here, results will be presented from both campaigns. Different periods in the growing season will be highlighted. In particular, we will elaborate on the effects of variations in internal and external canopy water, and soil moisture on diurnal backscatter patterns.

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Canopy Water Content Estimation for Typical Emerged Plant Community from Simulation Worldview-2 Data: A Case Study in Wild Duck Lake Wetland, Beijing

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.779-780.1571 ◽

2013 ◽

Vol 779-780 ◽

pp. 1571-1575

Author(s):

Chuan Lin ◽

Zhao Ning Gong ◽

Wen Ji Zhao

Keyword(s):

Remote Sensing ◽

Water Content ◽

Quantitative Estimation ◽

Physiological Status ◽

Electromagnetic Spectrum ◽

Growth Trend ◽

Wild Duck ◽

Vegetation Water Content ◽

Vegetation Water ◽

Canopy Water

Quantitative estimation of vegetation water content with remote sensing technique is of great significance for vegetation physiological status and growth trend monitoring. It also provides a theoretical foundation for actual application of vegetation water content diagnosis using remote sensing images in Wild Duck Lake wetland. In this paper the NDVIs and SRs calculated from simulation WorldVeiw-2 curves can be used to model and predict canopy water content of typical emerged plant. The NDVIs and SRs involving the additional spectral bands of WorldView-2, such as the red-edge and near infrared regions of the electromagnetic spectrum, improve the prediction accuracy compared with the traditional NDVIs and SRs.

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