Spatial and temporal variability of biophysical variables in southwestern France from airborne L-band radiometry

Zakharova, Elena; Calvet, Jean‐Christophe; Lafont, S.; Albergel, Clément; Wigneron, Jean‐Pierre; Pardé, Mickaël; Kerr, Yann H.; Zribi, Mehrez

doi:10.5194/hess-16-1725-2012

Cited by 10 publications

(5 citation statements)

References 72 publications

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“…Therefore, when the corn optical depth and the height and areal density of the corn stalks are fixed, the GVWC, i.e., the variable w in Equation (14), is positively correlated with the LAI. This result indicates that a higher input LAI is associated with a higher w, whereas a lower input LAI is associated with a lower w. Figure 11b shows that both the GLASS LAI and LAINET LAI display positive correlations with the corresponding retrieved corn GVWC, agreeing with other relevant studies [43,44]. The analysis above demonstrates that lower GLASS LAI data cause the corn GLASS-GVWC to be lower than the corn LAINET-GVWC at the identical time and place in the validation region.…”

Section: Discussionsupporting

confidence: 81%

Gravimetric Vegetation Water Content Estimation for Corn Using L-Band Bi-Angular, Dual-Polarized Brightness Temperatures and Leaf Area Index

et al. 2015

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Abstract:In this study, an algorithm to retrieve the gravimetric vegetation water content (GVWC, %) of corn was developed. First, the method for obtaining the optical depth from L-band (1.4 GHz) bi-angular, dual-polarized brightness temperatures (TB) for short vegetation was investigated. Then, the quantitative relationship between the corn optical depth, corn GVWC and corn leaf area index (LAI) was constructed. Finally, using the Polarimetric L-band

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Section: Discussionsupporting

confidence: 81%

Gravimetric Vegetation Water Content Estimation for Corn Using L-Band Bi-Angular, Dual-Polarized Brightness Temperatures and Leaf Area Index

et al. 2015

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“…Finally, the b parameter is, in general, higher at V polarization, which could be explained by the fact that the vegetation was predominantly oriented in the vertical direction [23]. These results are consistent with the findings of Zakharova et al [42], who observed a similar evolution of a polarization-independent bVWC parameter for low vegetation canopies (i.e., grassland, wheat and irrigated maize). They showed a clear decrease of the bVWC parameter during the vegetation growing phase, with b values of 0.15 during spring and values around 0.05 during summer, when the vegetation was fully grown.…”

Section: Volumetric Soil Water Contentsupporting

confidence: 91%

Vegetation Optical Depth and Soil Moisture Retrieved from L-Band Radiometry over the Growth Cycle of a Winter Wheat

et al. 2018

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L-band radiometer measurements were performed at the Selhausen remote sensing field laboratory (Germany) over the entire growing season of a winter wheat stand. L-band microwave observations were collected over two different footprints within a homogenous winter wheat stand in order to disentangle the emissions originating from the soil and from the vegetation. Based on brightness temperature (T B ) measurements performed over an area consisting of a soil surface covered by a reflector (i.e., to block the radiation from the soil surface), vegetation optical depth (τ) information was retrieved using the tau-omega (τ-ω) radiative transfer model. The retrieved τ appeared to be clearly polarization dependent, with lower values for horizontal (H) and higher values for vertical (V) polarization. Additionally, a strong dependency of τ on incidence angle for the V polarization was observed. Furthermore, τ indicated a bell-shaped temporal evolution, with lowest values during the tillering and senescence stages, and highest values during flowering of the wheat plants. The latter corresponded to the highest amounts of vegetation water content (VWC) and largest leaf area index (LAI). To show that the time, polarization, and angle dependence is also highly dependent on the observed vegetation species, white mustard was grown during a short experiment, and radiometer measurements were performed using the same experimental setup. These results showed that the mustard canopy is more isotropic compared to the wheat vegetation (i.e., the τ parameter is less dependent on incidence angle and polarization). In a next step, the relationship between τ and in situ measured vegetation properties (VWC, LAI, total of aboveground vegetation biomass, and vegetation height) was investigated, showing a strong correlation between τ over the entire growing season and the VWC as well as between τ and LAI. Finally, the soil moisture was retrieved from T B observations over a second plot without a reflector on the ground. The retrievals were significantly improved compared to in situ measurements by using the time, polarization, and angle dependent τ as a priori information. This improvement can be explained by the better representation of the vegetation layer effect on the measured T B .

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“…Along the Atlantic-Mediterranean transect formed by the SMOSMANIA network ( Fig. 1), the grassland cover fraction ranges between 10 and 40 % (Zakharova et al, 2012). Various mineral soil types can be found along this transect, ranging from sand to clay and silt loam (see Supplement 1).…”

Section: Introductionmentioning

confidence: 92%

“…They are often measured in the lab on perturbed soil samples (Abu-Hamdeh and Reeder, 2000;Lu et al, 2007). Although recent advances in line-source probe and heat pulse methods have made it easier to monitor soil thermal conductivity in the field (Bristow et al, 1994;Zhang et al, 2014), such measurements are currently not made in operational meteorological networks. Moreover, for given soil moisture conditions, λ depends to a large extent on the fraction of soil minerals presenting high thermal conductivities such as quartz, hematite, dolomite or pyrite (Côté and Konrad, 2005).…”

Section: Introductionmentioning

confidence: 99%

Deriving pedotransfer functions for soil quartz fraction in southern France from reverse modeling

Calvet

Fritz

Berne

et al. 2016

SOIL

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Abstract. The quartz fraction in soils is a key parameter of soil thermal conductivity models. Because it is difficult to measure the quartz fraction in soils, this information is usually unavailable. This source of uncertainty impacts the simulation of sensible heat flux, evapotranspiration and land surface temperature in numerical simulations of the Earth system. Improving the estimation of soil quartz fraction is needed for practical applications in meteorology, hydrology and climate modeling. This paper investigates the use of long time series of routine ground observations made in weather stations to retrieve the soil quartz fraction. Profile soil temperature and water content were monitored at 21 weather stations in southern France. Soil thermal diffusivity was derived from the temperature profiles. Using observations of bulk density, soil texture, and fractions of gravel and soil organic matter, soil heat capacity and thermal conductivity were estimated. The quartz fraction was inversely estimated using an empirical geometric mean thermal conductivity model. Several pedotransfer functions for estimating quartz content from gravimetric or volumetric fractions of soil particles (e.g., sand) were analyzed. The soil volumetric fraction of quartz (fq) was systematically better correlated with soil characteristics than the gravimetric fraction of quartz. More than 60 % of the variance of fq could be explained using indicators based on the sand fraction. It was shown that soil organic matter and/or gravels may have a marked impact on thermal conductivity values depending on which predictor of fq is used. For the grassland soils examined in this study, the ratio of sand-to-soil organic matter fractions was the best predictor of fq, followed by the gravimetric fraction of sand. An error propagation analysis and a comparison with independent data from other tested models showed that the gravimetric fraction of sand is the best predictor of fq when a larger variety of soil types is considered.

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Spatial and temporal variability of biophysical variables in southwestern France from airborne L-band radiometry

Cited by 10 publications

References 72 publications

Gravimetric Vegetation Water Content Estimation for Corn Using L-Band Bi-Angular, Dual-Polarized Brightness Temperatures and Leaf Area Index

Gravimetric Vegetation Water Content Estimation for Corn Using L-Band Bi-Angular, Dual-Polarized Brightness Temperatures and Leaf Area Index

Vegetation Optical Depth and Soil Moisture Retrieved from L-Band Radiometry over the Growth Cycle of a Winter Wheat

Deriving pedotransfer functions for soil quartz fraction in southern France from reverse modeling

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