Mapping surface fluxes using Visible - Near Infrared and Thermal Infrared data with the SEBAL Algorithm

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1 Mapping surface fluxes using Visible - Near Infrared and Thermal Infrared data with the SEBAL Algorithm F. Jacob 1, A. Olioso 1, X.F. Gu 1, J.F. Hanocq 1, O. Hautecoeur 2, and M. Leroy 2 1 INRA bioclimatologie, Domaine St Paul, Avignon Cedex 9, France 2 CESBio, 18 avenue E.Belin, BP 2801, Toulouse Cedex 4, France Camera-ready Copy for Physics and Chemistry of the Earth Manuscript-No.??? Offset requests to: F. Jacob INRA-Bioclimatologie Domaine St Paul, Site Agroparc Avignon Cedex 9, France

2 First author: Jacob 1 Mapping surface fluxes using Visible - Near Infrared and Thermal Infrared data with the SEBAL Algorithm F. Jacob 1, A. Olioso 1, X.F. Gu 1, J.F. Hanocq 1, O. Hautecoeur 2, and M. Leroy 2 1 INRA bioclimatologie, Domaine St Paul, Avignon Cedex 9, France 2 CESBio, 18 avenue E.Belin, BP 2801, Toulouse Cedex 4, France Received??? Accepted??? Abstract. Maps of surface fluxes were generated thanks to the SEBAL algorithm with airborne Visible, Near Infra-Red and Thermal Infra-Red remote sensing data over the ReSeDA experimental site in 1997 for 8 days. The SEBAL inputs are albedo, NDVI and brightness temperature maps. Albedo and NDVI were retrieved thanks to the multi-directional PolDER data in four wave-bands (443, 550, 670 and 865 nm). Surface brightness temperature was obtained using nadir measurements from a Thermal Infra-Red video camera, and corresponding to the [ ] μm spectral band. The aim of this study was to evaluate several aspects of SEBAL. Its basic assumption is that the study area presents simultaneously sites with very high and low evapotranspiration, allocated through the correlation between albedo and surface temperature. This has been verified for all the days of the experiment. The two key-points concern the estimation of the wind speed and of the air temperature through the spatial variability with respect to hydrological contrast. These estimations appeared to be realistic. Finally, validation on surface fluxes at a 20 m resolution was provided by comparison to field measurements performed on several crop fields. 1 Introduction Several environmental studies such as agronomy, hydrology or meteorology requires the knowledge of the land surface energetic status, through different components of the surface energy balance (Noilhan and Planton, 1989; Mahfouf et al., 1995; Noilhan and Lacarrere, 1995). Earth observation thanks to remote sensing technic provides the possibility to map several land surface properties which drive the energetic transfers at the soil - vegetation - atmosphere interface (Olioso et al., 1999). For the latter, the required accuracy varies from an application to another. Generally, it is about ±50 W.m 2 for the sensible heat flux (Seguin et al., 1999). Among the numerous models developed the two last decades, Correspondence to: F. JACOB the SEBAL one present the interest to map surface energy fluxes using exclusively remote sensing data. The main characteristic of the model is that it retrieves required variables not available directly from remote sensing through the spatial variability with respect to hydrological contrast. We propose in this study to evaluate its characteristics using the ReSeDA database. SEBAL is fed thanks to multidirectional Visible (Vis) - Near Infra-Red (NIR) and Thermal Infra-Red airborne remote sensing data. The latter allow to verify the existence of the spatial variability and the resulting correlation between the albedo and the surface temperature. The validation thanks to field measurements has several interesting aspects. i) The use of high spatial resolution data induces less problems with respect to spatial variability. ii) The multi-temporal aspect allows to considered several situations, both on a meteorological plan and a soil occupation one. iii) The numerous field data allow to consider several aspects of the model, both on intermediary variables and on surface energy balance components. After the presentation of the data, the model and the methods used to estimate input variables of the latter, we discuss the SEBAL results, both on its key points and on the surface energy flux estimations. 2 Data acquisition and preprocessing 2.1 The ReSeDA Field Experiment The ReSeDA experiment lasted from December 1996 to December 1997, in the south east of France (N 43 o 47, E 4 o 45 ). Experimental site was an agricultural region about 5 5 km 2 with sunflower, wheat, corn, grassland and alfalfa fields about m 2 (Prévot and et al., 1998). Several remotely sensed data have been acquired during this period, devoted to different studies. In this study, we considered Vis- NIR and TIR airborne remote sensing data, as well as field measurements of micro-meteorological variables and surface energy fluxes.

3 First author: Jacob Airborne data Airborne remote sensing data were acquired using two instruments approximately one or two times per month, on clear sky days and at a 3000 m altitude involving a 20 m nadir spatial resolution. Four flight lines were parallel to the solar plan, and one perpendicular. These five lines were completed within 45 minutes centered at the solar noon. The PolDER instrument were used for the acquisition of the Vis-NIR data. The latter were multi-directional (±50 o ), and corresponded to 10 or 20 nm bandwidth centered on 443 nm, 550 nm, 670 nm and 865 nm. Several pre-processes such as instrumental, atmospheric and geometric corrections (Leroy et al., 2000) led to sampled BRDF for each pixel. TIR data were acquired thanks to a video camera INFRA- METRICS with a wide angle allowing multi-angular observations (±40 o ). The spectral band ranged from 7.25 to μm. Radiometric corrections (Jacob et al., 1999) and image registration provided a dataset of multi-directional surface brightness temperature estimations. 2.3 Field data Daily field measurements performed on seven points located on alfalfa, wheat, and sunflower crops. The data set corresponded to 20 minutes mean values of wind speed, air temperature, net radiation, soil heat flux, sensible and latent heat flux. The latter were estimated and computed through three methods: bowen ratio, aerodynamic and eddy correlation method. 3 The model The SEBAL model (Bastiaanssen et al., 1998a,b) is a single layer surface energy balance model. Its objective is to use exclusively remote sensing data. It s originality is to retrieve wind speed and air temperature through the spatial variability with respect to hydrological contrast depicted by the study area. This involves that the latter is assumed to present simultaneously sites with very high and low evapotranspiration. The model input variables are maps of albedo, Normalized Difference Vegetation Index (NDVI) and Surface Brightness Temperature (SBT). From these latter, emissivity, soil heat flux and momentum roughness length are computed using empirical or semi-empirical relationships. The existence of the spatial variability is verified through the correlation between albedo and SBT. From the latter, it is possible to allocate pixels with very low evapotranspiration whose properties allow to compute an averaged value of the wind speed. The spatial variability in SBT allows to retrieve pixel by pixel the difference between surface and air temperatures, assuming that they are linearly related. Finally, the latent heat flux is calculated as the surface energy balance residue, and the model provides maps of the surface energy fluxes having a 1 The name of the company is given for the benefit of the reader and do not imply any endorsement of the product or company by the authors. temporal signification corresponding to the delay of remote sensing data acquisition. 4 Data processing The three model input variables (albedo, NDVI and SBT) were generated using the multi-directional Vis-NIR and TIR airborne remote sensing data. The mapping of albedo and NDVI was performed using Vis-NIR data through BRDF kernel-driven models. The inversion of such models allowed to retrieve the whole BRDFs from the sampled ones provided by the multi-angular data. Then, the NDVI was calculated as the normalized difference between the nadir reflectances in the channels 670 and 865 nm. The integration of the whole retrieved BRDF led to hemispherical reflectances, whose linear combination provided the albedo. Three BRDF kernel-driven models and three coefficient sets for the linear combination were tested, giving similar results (Jacob et al., 2000). SBT maps were obtained using the set of multi-directional TIR data. In this case, we considered a mean value of the data acquired over the 45 minutes corresponding to the five flight lines (Sect 2), and having a nadir view angle lower than 20 o. 5 Results and discussion Three aspects of the model were tested: i) the assumed existence of an hydrological contrast detected through the correlation between albedo and SBT, ii) the estimations of the wind speed and of the difference between surface and air temperatures, iii)the validity of the of the surface energy flux maps. In order to verify the correlation between albedo and SBT, we have used the following procedure. For a given day, considering the albedo and SBT maps, we have computed for each albedo class between 0.05 and 0.4 by step of 0.01, the SBT mean value and the corresponding standard deviation. Results has shown that the correlation was verified for each day of the experiment (fig.1), as well as the existence of the hydrological contrast, even for days preceded by rainy events. This could be explained by the fact that airborne observations was performed during clear sky days, inducing that the experimental area depicted simultaneously low evaporation sites such as illuminated bare soils and high evaporation ones such as alfalfa, sunflower and wheat fields. The high values of standard deviation for each albedo class could be explained by the natural variability (the author of the model has also remarked such a scattering), or by the inaccuracy on image registrations. Nevertheless, these results were encouraging since the key points of the model are based on the existence of such a correlation. Indeed, the properties of the sites with very low evapotranspiration and the variability inside the SBT map are used to compute respectively wind speed and air temperature. From field measurements, we were able to verify these two key

4 First author: Jacob 3 32 Surface Brightness Temperature ( C) Surface Albedo Model estimates of Ts Ta ( C) Field measurements of Ts Ta ( C) Fig. 1. Evolution of brightness temperature versus albedo for the ReSeDA experimental site and the day of experiment 12 March Dots and segment represent respectively mean value and standard deviation. Fig. 2. Comparison between SEBAL simulations and field measurements of Ts TA for the whole ReSeDA experiment. points. The validation has given results not very accurate, but realistic (tab.1 and fig.2). This was an important result, because the similar models use generally ground measurements, while SEBAL considers exclusively remote sensing data, their correlation and their spatial variability. The last point was the validity of the surface energy flux maps (tab.2). The SEBAL net radiation estimations were close to field measurements, the results being in agreement with several works presented in the literature (Moran et al., 1994; Kustas et al., 1994). Comparison between soil heat flux from SEBAL simulations and field measurements were not satisfactory. Nevertheless, the RMSE corresponded to the field data accuracy. Therefore, it was not possible to conclude on the validity of the two methods. As explained in Sect.2, three methods were used to calculate the in-situ convective fluxes. In this context, the SEBAL sensible and latent heat fluxes validation required first a discussion on these estimations. Unfortunately, the quality of results from bowen ratio and aerodynamic methods were very poor, and only few ones from eddy correlation method were available. From the validation thanks to the latter, is was therefore not possible to draw a general conclusion. Other investigations are then necessary to assess these field measurements. SEBAL final results were maps of surface energy fluxes at a 20 m spatial sampling and corresponding to 45 minutes averaging (fig.3). They depicted a strong spatial variability inside of very heterogeneous fields that can reach 50 W:m 2, and a pattern on the larger scale corresponding to the whole Variable Absolute Relative Correlation RMSE RMSE coefficient Wind speed 0.63 m:s 1 30% 0.85 Ts Ta 3 o C Table 1. Results of validation for SEBAL intermediary variables over the whole ReSeDA experiment. site. 6 Conclusion The vocation of this study was to map evapotranspiration using two original tools such as high spatial remotely sensed data and a surface energy balance model exploiting spatial variability related to hydrological conditions. The ReSeDA experiment allowed to perform an interesting validation: on several variables estimated by the model, with high spatial resolution remote sensing data inducing problems due to heterogeneity less important, and over cycles of several crops during one year. Unfortunately, an assessment of field measurements is necessary at the present time to validate the convective fluxes computed by SEBAL. However, it has been shown that the basic assumption of the model, i.e. the correlation between SBT and albedo through spatial variability, was verified for each day of the experiment with available remote sensing data. Moreover, the key points of the model, i.e. the estimation of wind speed and air temperature from spatial variability gave realistic results, which is a very encouraging result. Energy Absolute Relative Correlation Flux RMSE RMSE coefficient Rn 60 W:m 2 10% 0.8 G0 40 W:m 2 30% 0.4 H 50 W:m 2 25% - LE 50 W:m 2 25% - Table 2. Results of validation for SEBAL energy fluxes over the whole ReSeDA experiment.

First author: Jacob 4 W.m 2 Fig. 3. Map of 45 minutes averaged evapotranspiration for the ReSeDA experimental site on the 10 April 1997 at a 20 m spatial sampling. References Bastiaanssen, W.

5 First author: Jacob 4 W.m 2 Fig. 3. Map of 45 minutes averaged evapotranspiration for the ReSeDA experimental site on the 10 April 1997 at a 20 m spatial sampling. References Bastiaanssen, W., Menenti, M., Feddes, R., and Holtslag, A., A remote sensing surface energy balance algorithm for land (SEBAL). I: Formulation, Journal of Hydrology, , , 1998a. Bastiaanssen, W., Pelgrum, H., Wang, J., Ma, Y., Moreno, J., Roerink, G., and van der WAL, T., A remote sensing surface energy balance algorithm for land (SEBAL). II: Validation, Journal of Hydrology, , , 1998b. Jacob, F., Gu, X., Hanocq, J.-F., and Baret, F., A procedure for atmospheric corrections of single channel and multidirectional thermal infra-red data. Application to the ReSeDA experiment, International Journal of Remote Sensing, submitted, Jacob, F., Weiss, M., Olioso, A., Hautecoeur, O., Fran cois, C., Leroy, M., and Ottlé, C., Albedo estimation from polder data, in Special ReSeDA session, EGS symposium, submitted, Kustas, W., Perry, E., Doraiswamy, P., and Moran, M., Using satellite remote sensing to extrapolate evapotranspiration estimates in time and space over a semiarid rangeland basin, Remote sensing of Environment, 49, , Leroy, M., Hautecoeur, O., Berthelot, B., and Gu, X., The airborne polder data during the reseda experiment., in Special ReSeDA session, EGS symposium, submitted, Mahfouf, J., Manzi, A., Noilhan, J., Giordani, H., and Déqué, M., The land surface scheme ISBA within the météo-france climate model arpege. Part I. Implementation and preliminary results, Journal of Climate, 8, , Moran, M., Kustas, W., Vidal, A., Stannard, D., Blanford, J., and Nichols, W., Use of ground-based remotely sensed data for surface energy balance evaluation of a semiarid rangeland, Water Resources Research, 30, , Noilhan, J. and Lacarrere, P., GCM grid-scale evaporation from mesocale modeling, Journal of Climate, 8, , Noilhan, J. and Planton, S., A simple parameterization of land surface processes for meteorological models, Monthly weather review, 117, , Olioso, A., Chauki, H., Courault, D., and Wigneron, J., Estimation of evapotranspiration and photosynthesis by assimilation of remote sensing data into svat models, Remote Sensing of Environment, 68, , Prévot, L. and et al., Assimilation of multi-sensor and multi-temporal remote sensing data to monitor vegetation and soil: the Alpilles ReSeDA project, in IGARSS 98, International Geoscience and Remote Sensing Symposium, Ed. L. Tsang, Seattle, pp , Seguin, B., Becker, F., Phulpin, T., Gu, X., Guyot, G., Kerr, Y., King, C., Lagouarde, J., Ottlé, C., Stoll, M., Tabbagh, T., and Vidal, A., IRSUTE: A minisatellite project for land surface heat flux estimation from field to regional scale, Remote Sensing of Environment, 68, , 1999.

Measuring and Analyzing of Thermal Infrared Emission Directionality over crop canopies with an airborne wide-angle thermal IR camera.

Measuring and Analyzing of Thermal Infrared Emission Directionality over crop canopies with an airborne wide-angle thermal IR camera. X. F. Gu 1, F. Jacob 1, J. F. Hanocq 1, T. Yu 1,2, Q. H. Liu 2, L.