Laurent Prévot

Estimating surface soil moisture and leaf area index of a wheat canopy using a dual-frequency (C and X bands) scatterometer

Abstract Since microwave remote sensing techniques are insensitive to cloud cover, they can overcome this strong limitation of optical remote sensing. As in the optical domain, their use for monitoring vegetation canopies requires the development of suitable inversion algorithms. These would allow the estimation of variables such as LAI from radar data. This article investigates the possible use of a semiempirical water-cloud model in an inversion scheme. Using radar data obtained with a ground-based dual-frequency (C and X bands, 5.7 and 3.3 cm wavelength, respectively) scatterometer on experimental winter wheat fields, it is first verified that a semiempirical water-cloud model can adequately simulate the backscattering coefficients obtained over the growing season, as a function of LAI and surface soil moisture. Then it is shown that the model can be numerically inverted. This yields simultaneous estimation of LAI and surface soil moisture, the standard deviations of the residuals being respectively 0.64 m2 m−2 and 0.065 cm3 cm−3. Finally, the influence of radar measurement errors on the inversion scheme is quantified by means of a simulation study. This shows that a 1 dB accuracy of the radar is required for a 1 m2 m−2 precision of the estimated LAI.

Analytical parameterization of canopy directional emissivity and directional radiance in the thermal infrared. Application on the retrieval of soil and foliage temperatures using two directional measurements

Abstract This work is aimed at deriving canopy component (soil and foliage) temperatures from remote sensing measurements. A simulation study above sparse, partial and dense vegetation canopies has been performed to improve the knowledge of the behaviour of the composite radiative temperature and emissivity. Canopy structural parameters have been introduced in the analytical parameterization of the directional canopy emissivity and directional canopy radiance:namely, the leaf area index (LAI), directional gap fraction and angular cavity effect coefficient. The parameterization has been physically defined allowing its extension to a wide range of Leaf Inclination Distribution Functions (LIDF). When single values are used as leaves and soil temperatures, they prove to be retrieved with insignificant errors from two directional measurements of the canopy radiance (namely at 0 and 55 from nadir), provided that the canopy structure parameters are known. A sensitivity study to the different parameters shows the...

Coupling canopy functioning and radiative transfer models for remote sensing data assimilation

Abstract Crop functioning models (CFM) are used in many agricultural and environmental applications. Remote sensing data assimilation appears as a good tool to provide more information about canopy state variables in time and space. It permits a reduction in the uncertainties in crop functioning model predictions. This study presents the first step of the assimilation of optical remote sensing data into a crop functioning model. It consists in defining a coupling strategy between well known and validated crop functioning and radiative transfer models (RTM), applied to wheat crops. The radiative transfer model is first adapted to consistently describe wheat, considering of four layers in the canopy that contain different vegetation organs (soil, yellow leaves and senescent stems, green leaves and stems, green and senescent ears). The coupling is then performed through several state variables: leaf area index, leaf chlorophyll content, organ dry matter and relative water content. The relationships between the CFM outputs (agronomic variables) and RTM inputs (biophysical variables) are defined using experimental data sets corresponding to wheat crops under different climatic and stress conditions. The coupling scheme is then tested on the data set provided by the Alpilles–ReSeDA campaign. Results show a good fitting between the simulated reflectance data at top of canopy and the measured ones provided by SPOT images corrected from atmospheric and geometric effects, with a root mean square error lower than 0.05 for all the wavebands.

Modeling maize canopy 3D architecture: Application to reflectance simulation

The aim of this study is to develop a 3D model of maize (Zea mays) canopy structure for accurate reflectance simulations. We focus on fully developed maize plants without paying attention to the reproductive organs. Several experiments are used to describe the dimension, shape, position and orientation of the leaves and stems. They correspond to a wide range of cultural practices. Empirical models are proposed to derive the position, size, and shape of the leaves and stems as a function of three main variables: the final number of leaves, the final height of the canopy and the cumulated leaf area per plant that is considered as a vigor index. Leaf orientation is described through the curvature of the main rib and the cross section used to represent the undulation of the lamina. The statistical distributions of the parameters of each structure sub-models are investigated. It allows to generate realistic computerized plant and canopy 3D architecture representation. The canopy structure is then used to compare the SAIL reflectance model to the reflectance simulated with PARCINOPY which is a monte-carlo ray tracing model. The combined use of detailed canopy architecture models and quasi exact radiative transfer models such as PARCINOPY appears to be a very convenient tool to evaluate more simple reflectance models applied to specific vegetation types. Results show a general good agreement between the two models, except for the exponential hot-spot function used in the SAIL model, and the directionality of the multiple scattering.

Estimation of soil and crop parameters for wheat from airborne radar backscattering data in C and X bands

Abstract The study of radar backscattering signatures of wheat fields was investigated, using data collected on the Orgeval agricultural watershed (France) by the airborne scatterometer ERASME in C and X bands, HH and VV polarizations, at incidence angles from 15° to 45°, during two years for different soil moisture conditions with simultaneous ground-based measurements. A simple parameterization as water-cloud model with two driving parameters (the surface soil moisture and the plant water content) gives satisfactory results to estimate radar cross sections of wheat for a wide range of frequencies (C and X bands) and incidence angles (20° and 40°) within 1 dB in CHH and XHH and 2 dB in CVV and XVV. At the lower frequency (C band) the attenuated soil backscattering by the vegetation is dominant. It is shown that simple linear relations in C band between radar cross section and soil moisture are insufficient. A correction term for the vegetation attenuation is needed and is determined. Low contrast between the backscattering of dry and wet soil (around 6 dB) for a given vegetation density leads to a relatively high error in the estimation of soil moisture by radar (0.06 cm 3 / cm 3 ). At the higher frequency (X band), the radar backscattering is negatively correlated to the vegetation water content with a saturation of the radar cross section as the plant grows (about 6 dB of dynamic range between low and fully grown canopy) with no dependence on the soil signal. The achievable accuracy in the estimation of crop water content is the same at 20° and 40° and higher in XHH (about 0.5 kg/m 2 ) than in XVV.

Directional effect on radiative surface temperature measurements over a semiarid grassland site

In this study, an experimental design was conceived, as part of the Semi-Arid-Land-Surface-Atmosphere (SALSA) program, to document the effect of view angle variation on surface radiative temperature measurements. The results indicated differences between nadir and off-nadir radiative temperature of up to 5 K. The data also illustrated that, under clear sky and constant vegetation conditions, this difference is well correlated with surface soil moisture. However, the correlation decreased when the same comparison was made under changing vegetation conditions. To investigate the possibility of deriving component surface temperatures (soil and vegetation) using dual-angle observations of directional radiative temperature, two radiative transfer models (RTM) with different degrees of complexity were used. The results showed that despite their differences, the two models performed similarly in predicting the directional radiative temperature at a third angle. In contrast to other investigations, our study indicated that the impact of ignoring the cavity effect term is not very significant. However, omitting the contribution of the incoming long-wave radiation on measured directional radiance seemed to have a much larger impact. Finally, sensitivity analysis showed that an accuracy of better than 10% on the plant area index (PAI) was required for achieving a precision of 1 K for inverted vegetation temperature. An error of 1 K in measured directional radiative temperature can lead to an error of about 1 K in the soil and vegetation temperatures derived by inverting the RTM.

Mapping Daily Evapotranspiration Over a Mediterranean Vineyard Watershed

Daily evapotranspiration (ET) was mapped and validated at the regional extent over a vineyard landscape. The mapping was performed using the simplified surface energy balance index (S-SEBI) model, along with an Advanced Spaceborne Thermal Emission and Reflection Radiometer imagery, over two growth cycles. The validation exercise was conducted within a Mediterranean vineyard watershed, over seven sites that differed in canopy, soil, and water conditions. Despite the use of a very simple model over a complex row-structured landscape, the obtained accuracy (0.8 mm/day) was similar to those reported over simpler canopies with full covers, and corresponded to requirements for further applications in agronomy and hydrology, where daily ET can be assimilated into land surface models for calibration and control purposes. An analysis of the validation results suggested that, among the possible factors that could affect S-SEBI performances (spatial variability, vine water status, soil type and color, and row orientation), the first-order influence was row orientation.

Generalized semi-empirical modelling of wheat radar response.

Two semi-empirical models, simulating the backscattering coefficient from different crops, were tested on the same wheat canopy. The physics of the semi-empirical models and the limitations of these models when scattering effects are discussed. The results show that both models can be included in a generalized formulation adapted to a large range of measurement conditions. This conclusion confirms that the radar configuration (waveband, polarization, incidence angle) plays a role similar to that of the canopy structure in the control of the radar backscattering coefficient.

Accounting for vegetation height and wind direction to correct eddy covariance measurements of energy fluxes over hilly crop fields

As agricultural hilly watersheds are widespread throughout the world, there is a strong need for reliable estimates of land surface fluxes, especially evapotranspiration, over crop fields on hilly slopes. In order to obtain reliable estimates from eddy covariance (EC) measurements in such conditions, the current study aimed at proposing adequate planar fit tilt corrections that account for the combined effects of topography, wind direction, and vegetation height on airflow inclinations. EC measurements were collected within an agricultural hilly watershed in northeastern Tunisia, throughout the growth cycles of cereals, legumes, and pasture. The wind had two dominant directions that induced upslope and downslope winds. For upslope winds, the airflows were parallel to the slopes and slightly came closer to the horizontal plane when vegetation grew. For downslope winds, over fields located in the lee of the rim top, the airflows were almost horizontal over bare soil and came closer to the topographical slope when vegetation grew. We therefore adjusted the planar fit tilt correction on EC measurements according to vegetation height and by discriminating between upslope and downslope winds. This adjusted tilt correction improved the energy balance closure in most cases, and the obtained energy balance closures were similar to that reported in the literature for flat conditions. We conclude that EC data collected within crop fields on hilly slopes can be used for monitoring land surface fluxes, provided planar fit tilt corrections are applied in an appropriate manner.

Retrieval of soil and vegetation features from passive microwave measurements

Passive microwave measurements are sensitive to several geophysical parameters of interest to assess global energy and water balance of vegetation‐covered land surfaces: surface temperature, soil moisture and vegetation water content. Depending on the conditions of the study (sensor performance, spatial and temporal resolution of the microwave observations, observed vegetation canopy, ground measurement availability, etc.), numerous approaches have been used to retrieve surface parameters from passive microwave signatures. In this paper a survey of current retrieval methods together with examples of potential applications of passive microwave measurements over vegetation cover are presented. Considering the large number of input parameters contributing to the microwave emission, efforts have to be made to integrate a priori information and synthetic description of vegetation effects into the inversion algorithms.