Estimation of Vegetation Water Content From the Radar Vegetation Index at L-Band

2016 ◽  
Vol 54 (2) ◽  
pp. 981-989 ◽  
Author(s):  
Yuancheng Huang ◽  
Jeffrey P. Walker ◽  
Ying Gao ◽  
Xiaoling Wu ◽  
Alessandra Monerris
Keyword(s):  
Water Content ◽  
Vegetation Index ◽  
Vegetation Water Content ◽  
L Band ◽  
Vegetation Water

Inferring the effects of surface canopy water on VOD estimation from L-band backscatter 

2021 ◽  
Author(s):  
Saeed Khabbazan ◽  
Paul.C. Vermunt ◽  
Susan.C. Steele Dunne ◽  
Ge Gao ◽  
Mariette Vreugdenhil ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Linear Relationship ◽  
Water Content ◽  
Growing Season ◽  
Empirical Parameter ◽  
Vegetation Water Content ◽  
L Band ◽  
Vegetation Water ◽  
Canopy Water ◽  
Effect Of Surface

<p>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.</p><p>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.</p><p>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.</p><p>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.</p><p>The methodology of Vreugdenhil et al.  [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. 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.</p><ul><li>[1] Vreugdenhil,W. A. Dorigo,W.Wagner, R. A. De Jeu, S. Hahn, andM. J. VanMarle, “Analyzing the vegetation parameterization in the TU-Wien ASCAT soil moisture retrieval,” IEEE Transactions on Geoscience and Remote Sensing, vol. 54, pp. 3513–3531, 2016</li> </ul>

Radar Vegetation Index for Estimating the Vegetation Water Content of Rice and Soybean

2012 ◽  
Vol 9 (4) ◽  
pp. 564-568 ◽  
Author(s):  
Yihyun Kim ◽  
T. Jackson ◽  
R. Bindlish ◽  
Hoonyol Lee ◽  
Sukyoung Hong
Keyword(s):  
Water Content ◽  
Vegetation Index ◽  
Vegetation Water Content ◽  
Vegetation Water

scholarly journals Estimating Gravimetric Water Content of a Winter Wheat Field from L-Band Vegetation Optical Depth

2019 ◽  
Vol 11 (20) ◽  
pp. 2353
Author(s):  
Thomas Meyer ◽  
Thomas Jagdhuber ◽  
María Piles ◽  
Anita Fink ◽  
Jennifer Grant ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Water Content ◽  
Water Status ◽  
Growth Cycle ◽  
Wheat Field ◽  
Vegetation Height ◽  
Vegetation Water Content ◽  
L Band ◽  
Vegetation Water

A considerable amount of water is stored in vegetation, especially in regions with high precipitation rates. Knowledge of the vegetation water status is essential to monitor changes in ecosystem health and to assess the vegetation influence on the water budget. In this study, we develop and validate an approach to estimate the gravimetric vegetation water content (mg), defined as the amount of water [kg] per wet biomass [kg], based on the attenuation of microwave radiation through vegetation. mg is expected to be more closely related to the actual water status of a plant than the area-based vegetation water content (VWC), which expresses the amount of water [kg] per unit area [m2]. We conducted the study at the field scale over an entire growth cycle of a winter wheat field. Tower-based L-band microwave measurements together with in situ measurements of vegetation properties (i.e., vegetation height, and mg for validation) were performed. The results indicated a strong agreement between the in situ measured and retrieved mg (R2 of 0.89), with mean and standard deviation (STD) values of 0.55 and 0.26 for the in situ measured mg and 0.57 and 0.19 for the retrieved mg, respectively. Phenological changes in crop water content were captured, with the highest values of mg obtained during the growth phase of the vegetation (i.e., when the water content of the plants and the biomass were increasing) and the lowest values when the vegetation turned fully senescent (i.e., when the water content of the plant was the lowest). Comparing in situ measured mg and VWC, we found their highest agreement with an R2 of 0.95 after flowering (i.e., when the vegetation started to lose water) and their main differences with an R2 of 0.21 during the vegetative growth of the wheat vegetation (i.e., where the mg was constant and VWC increased due to structural changes in vegetation). In addition, we performed a sensitivity analysis on the vegetation volume fraction (δ), an input parameter to the proposed approach which represents the volume percentage of solid plant material in air. This δ-parameter is shown to have a distinct impact on the thermal emission at L-band, but keeping δ constant during the growth cycle of the winter wheat appeared to be valid for these mg retrievals.

Sensitivity of Passive Microwave Observations to Soil Moisture and Vegetation Water Content: L-Band to W-Band

2011 ◽  
Vol 49 (4) ◽  
pp. 1190-1199 ◽  
Author(s):  
Jean-Christophe Calvet ◽  
Jean-Pierre Wigneron ◽  
Jeffrey Walker ◽  
Fatima Karbou ◽  
André Chanzy ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Passive Microwave ◽  
Vegetation Water Content ◽  
W Band ◽  
L Band ◽  
Vegetation Water

scholarly journals Microwave Vegetation Index from Multi-Angular Observations and Its Application in Vegetation Properties Retrieval: Theoretical Modelling

2019 ◽  
Vol 11 (6) ◽  
pp. 730 ◽  
Author(s):  
Somayeh Talebiesfandarani ◽  
Tianjie Zhao ◽  
Jiancheng Shi ◽  
Paolo Ferrazzoli ◽  
Jean-Pierre Wigneron ◽  
...  
Keyword(s):  
Water Content ◽  
Vegetation Index ◽  
Soil Layer ◽  
Global Scale ◽  
Optical Observations ◽  
Theoretical Modelling ◽  
Vegetation Monitoring ◽  
L Band ◽  
Vegetation Water ◽  
Global Vegetation

Monitoring global vegetation dynamics is of great importance for many environmental applications. The vegetation optical depth (VOD), derived from passive microwave observation, is sensitive to the water content in all aboveground vegetation and could serve as complementary information to optical observations for global vegetation monitoring. The microwave vegetation index (MVI), which is originally derived from the zero-order model, is a potential approach to derive VOD and vegetation water content (VWC), however, it has limited application at dense vegetation in the global scale. In this study, we preferred to use a more complex vegetation model, the Tor Vergata model, which takes into account multi-scattering effects inside the vegetation and between the vegetation and soil layer. Validation with ground-based measurements proved this model is an efficient tool to describe the microwave emissions of corn and wheat. The MVI has been derived through two methods: (i) polarization independent ( MVI B P ) and (ii) time invariant ( MVI B T ), based on model simulations at the L band. Results show that the MVI B T has a stronger sensitivity to vegetation properties compared with MVI B P . MVI B T is used to retrieve VOD and VWC, and the results were compared to physical VOD and measured VWC. Comparisons indicated that MVI B T has a great potential to retrieve VOD and VWC. By using L band time-series information, the performance of MVIs could be enhanced and its application in a global scale could be improved while paying attention to vegetation structure and saturation effects.

scholarly journals Relationship between Vegetation Biophysical Properties and Surface Temperature Using Multisensor Satellite Data

2007 ◽  
Vol 20 (22) ◽  
pp. 5593-5606 ◽  
Author(s):  
Seungbum Hong ◽  
Venkat Lakshmi ◽  
Eric E. Small
Keyword(s):  
Surface Temperature ◽  
Water Content ◽  
Land Surface ◽  
Vegetation Index ◽  
Climatic Variability ◽  
Regional Distribution ◽  
Spatial And Temporal Variability ◽  
Area Index ◽  
Vegetation Water Content ◽  
Vegetation Water

Abstract Vegetation is an important factor in global climatic variability and plays a key role in the complex interactions between the land surface and the atmosphere. This study focuses on the spatial and temporal variability of vegetation and its relationship with land–atmosphere interactions. The authors have analyzed the vegetation water content (VegWC) from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), the leaf area index (LAI), the normalized difference vegetation index (NDVI), the land surface temperature (Ts), and the Moderate Resolution Imaging Spectroradiometer (MODIS). Three regions, which have climatically differing characteristics, have been selected: the North America Monsoon System (NAMS) region, the Southern Great Plains (SGP) region, and the Little River Watershed in Tifton, Georgia. Temporal analyses were performed by comparing satellite observations from 2003 and 2004. The introduction of the normalized vegetation water content (NVegWC) derived as the ratio of VegWC and LAI corresponding to the amount of water in individual leaves has been estimated and this yields significant correlation with NDVI and Ts. The analysis of the NVegWC–NDVI relationship in the above listed three regions displays a negative exponential relation, and the Ts–NDVI relationship (TvX relationship) is inversely proportional. The correlation between these variables is higher in arid areas such as the NAMS region, and becomes less correlated in the more humid and more vegetated regions such as the area of eastern Georgia. A land-cover map is used to examine the influence of vegetation types on the vegetation biophysical and surface temperature relationships. The regional distribution of vegetation reflects the relationship between the vegetation biological characteristics of water and the growing environment.

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