The assessment of uncertainties in satellite-derived global surface albedo products is a critical aspect for studying the climate, ecosystem change, hydrology or the Earth's radiant energy budget. However, it is challenged by the spatial scaling errors between satellite and field measurements. This study aims at evaluating the forthcoming MODerate Resolution Imaging Spectroradiometer (MODIS) (Collection V006) Bidirectional Reflectance Distribution Function (BRDF)/albedo productMCD43Dover aMediterranean agricultural area.Here,we present the results from the accuracy assessment of theMODIS blue-sky albedo. The analysis is based on collocated comparisonswith higher spatial resolution estimates from Formosat-2 that were first evaluated against local in situmeasurements. The intersensor comparison is achieved by taking into account the effective point spread function (PSF) for MODIS albedo, modeled as Gaussian functions in the North–South and East–West directions. The equivalent PSF is estimated by correlation analysis between MODIS albedo and Formosat-2 convolved albedo. Results show that it is 1.2 to 2.0 times larger in the East–West direction as compared to the North–South direction. We characterized the equivalent PSF by a full width at half maximum size of 1920 m in East–West, 1200 m in North–South. This provided a very good correlation between the products, showing absolute (relative) Root Mean Square Errors from 0.004 to 0.013 (2% to 7%), and almost no bias. By inspecting 1-km plots homogeneous in land cover type,we found poorer performances over rice and marshes (i.e., relative Root Mean Square Error of about 11% and 7%, and accuracy of 0.011 and −0.008, respectively), and higher accuracy over dry and irrigated pastures, as well as orchards (i.e., relative uncertainty b3.8% and accuracy b0.003). The study demonstrates that neglecting theMODIS PSFwhen comparing the Formosat-2 albedo against theMODIS one induces an additional uncertainty up to 0.02 (10%) in albedo. The consistency between fine and coarse spatial resolution albedo estimates indicates the ability of the daily MCD43D product to reproduce reasonably well the dynamics of albedoThe assessment of uncertainties in satellite-derived global surface albedo products is a critical aspect for studying the climate, ecosystem change, hydrology or the Earth's radiant energy budget. However, it is challenged by the spatial scaling errors between satellite and field measurements. This study aims at evaluating the forthcoming MODerate Resolution Imaging Spectroradiometer (MODIS) (Collection V006) Bidirectional Reflectance Distribution Function (BRDF)/albedo productMCD43Dover aMediterranean agricultural area.Here,we present the results from the accuracy assessment of theMODIS blue-sky albedo. The analysis is based on collocated comparisonswith higher spatial resolution estimates from Formosat-2 that were first evaluated against local in situmeasurements. The intersensor comparison is achieved by taking into account the effective point spread function (PSF) for MODIS albedo, modeled as Gaussian functions in the North–South and East–West directions. The equivalent PSF is estimated by correlation analysis between MODIS albedo and Formosat-2 convolved albedo. Results show that it is 1.2 to 2.0 times larger in the East–West direction as compared to the North–South direction. We characterized the equivalent PSF by a full width at half maximum size of 1920 m in East–West, 1200 m in North–South. This provided a very good correlation between the products, showing absolute (relative) Root Mean Square Errors from 0.004 to 0.013 (2% to 7%), and almost no bias. By inspecting 1-km plots homogeneous in land cover type,we found poorer performances over rice and marshes (i.e., relative Root Mean Square Error of about 11% and 7%, and accuracy of 0.011 and −0.008, respectively), and higher accuracy over dry and irrigated pastures, as well as orchards (i.e., relative uncertainty b3.8% and accuracy b0.003). The study demonstrates that neglecting theMODIS PSFwhen comparing the Formosat-2 albedo against theMODIS one induces an additional uncertainty up to 0.02 (10%) in albedo. The consistency between fine and coarse spatial resolution albedo estimates indicates the ability of the daily MCD43D product to reproduce reasonably well the dynamics of albed

Thermal infrared (TIR) emissivities of soils with different textures were measured for several soil moisture (SM) contents under controlled conditions using the Box method and a high-precision multichannel TIR radiometer. The results showed a common increase of emissivity with SM at water contents lower than the field capacity. However, this dependence is negligible for higher water contents. The highest emissivity variations were observed in sandy soils, particularly in the 8-9-μm range due to water adhering to soil grains and decreasing the reflectance in the 8-9-μm quartz doublet region. Thus, in order to model the emissivity dependence on soil water content, different approaches were studied according to the a priori soil information. Soil-specific relationships were provided for each soil texture and different spectral bands between 8 and 13 μm, with determination coefficients up to 0.99, and standard estimation errors in emissivity lower than ± 0.014. When considering a general relationship for all soil types, standard estimation errors up to ±0.03 were obtained. However, if other soil properties (i.e., organic matter, quartz, and carbonate contents) were considered, along with soil water content, the general relationship predicted TIR emissivities with a standard estimation error of less than ±0.008. Furthermore, the study showed the possibility of retrieving SM from TIR emissivities with a standard estimation error of about ±0.08 m³ . m^-3.

The net radiation flux available at the Earth's surface drives evapotranspiration, photosynthesis and other physical and biological processes. The only cost-effectiveway to capture its spatial and temporal variability at regional and global scales is remote sensing. However, the accuracy of net radiation derived fromremote sensing data has been evaluated up to now over a limited number of in situ measurements and ecosystems. This study aims at evaluating estimates and uncertainties on net radiation derived from Landsat-7 images depending on reliability of the input surface variables albedo, emissivity and surface temperature. The later includes the reliability of remote sensing information (spectral reflectances and top of canopy brightness temperature) and shortwave and longwave incoming radiations. Primary information describing the surface is derived from remote sensing observations. Surface albedo is estimated from spectral reflectances using a narrow-to-broadband conversion method. Land surface temperature is retrieved from top of canopy brightness temperature by accounting for land surface emissivity and reflection of atmospheric radiation; and emissivity is estimated using a relationship with a vegetation index and a spectral database of soil and plant canopy properties in the study area. The net radiation uncertainty is assessed using comparison with ground measurements over the Crau–Camargue and lower Rhone valley regions in France. Wefound RootMean Square Errors between retrievals and fieldmeasurements of 0.25–0.33 (14–19%) for albedo, ~1.7 K for surface temperature and ~20W·m−2 (5%) for net radiation. Results show a substantial underestimation of Landsat-7 albedo (up to 0.024), particularly for estimates retrieved using the middle infrared,which could be due to different sources: the calibration of field sensors, the correction of radiometric signals fromLandsat-7 or the differences in spectral bands with the sensors for which the models where originally derived, or the atmospheric corrections.We report a global uncertainty in net radiation of 40–100W·m−2 equally distributed over the shortwave and longwave radiation, which varies spatially and temporally depending on the land use and the time of year. In situ measurements of incoming shortwave and longwave radiation contribute themost to uncertainty in net radiation (10–40W·m−2 and 20–30 W·m−2, respectively), followed by uncertainties in albedo (b25 W·m−2) and surface temperature (~8 W·m−2). For the latter, the main factors were the uncertainties in top of canopy reflectances (b10 W·m−2) and brightness temperature (5–7 W·m−2). The generalization of these results to other sensors and study regions could be considered, except for the emissivity if prior knowledge on its characterization is not availabl

Evapotranspiration (ET) is a fundamental variable of the hydrological cycle and its estimation is required for irrigation management, water resources planning and environmental studies. Remote sensing provides spatially distributed cost-effective information for ET maps production at regional scale. We have developed EVASPA too for mapping ET from remote sensing data at spatial and temporal scales relevant to hydrological or agronomica studies.[br/] EVASPA includes several algorithms for estimating evapotranspiration and various equations for estimating the required input information (net radiation, ground heat flux, evaporative fraction…), which provides a way to assess uncertainties in the derivation of ET. The tool integrates data from various remote sensing sensors and it can be easily adapted to new sensors. To test the tool, evapotranspiration maps have been produced for the Crau-Camargue pilot site (south-eastern France), where several energy balance stations deployed in contrasted areas provide ground measurements. An overall description of the tool and first results of performance asse sment (comparison to ground data) are presented here