Zhengquan Li

A practical algorithm to infer soil and foliage component temperatures from bi-angular ATSR-2 data

An operational algorithm is proposed to retrieve soil and foliage component temperatures over heterogeneous land surface based on the analysis of bi-angular multi-spectral observations made by ATSR-2. Firstly, on the basis of the radiative transfer theory in a canopy, a model is developed to infer the two component temperatures using six channels of ATSR-2. Four visible, near-infrared and short wave infrared channels are used to estimate the fractional vegetation cover within a pixel. A split-window method is developed to eliminate the atmospheric effects on the two thermal channels. An advanced method using all four visible, near-infrared and short wave channel measurements at two view angles is developed to perform atmospheric corrections in those channels allowing simultaneous retrieval of aerosol opacity and land surface bi-directional reflectance. Secondly, several case studies are undertaken with ATSR-2 data. The results indicate that both foliage and soil temperatures can be retrieved from bi-angular surface temperatures measurements. Finally, limitations and uncertainties in retrieving component temperatures using the present algorithm are discussed.

On the separate retrieval of soil and vegetation temperatures from ATSR data

The Along-Track Scanning Radiometer (ATSR) onboard the European Remote Sensing satellite (ERS) is presently the only one available to provide quasi-simultaneous thermal infrared measurements at two view angles. Such data represent an opportunity to explore the potential information on the directional observations in the thermal infrared region, in view of the preparation of a new generation of multi-angle satellite sensors. Based on the analysis of one ATSR image, the results of this work indicate that the magnitude of the directional effect on the brightness temperature (ground anisotropic radiance), although quite sensitive to errors in atmospheric conditions, may still be retrieved with acceptable uncertainty. In order to retrieve both vegetation and soil temperatures from directional brightness temperatures, it is shown that an appropriate description of the nature and content of the pixel is needed, otherwise this retrieval will be quite uncertain.

Assimilation of land surface temperature data from ATSR in an NWP environment--a case study

Directional thermal observations from the ATSR-2 satellite sensor were used to estimate separate vegetation and soil temperatures for a number of cloud free scenes covering south-east Spain over five days in 1999. Underlying methodology for this is a simplified radiative transfer scheme and a concurrent estimate of the fraction of ground covered with vegetation. The vegetation and soil temperatures were used together with near-surface relative humidity measurements to adjust the root zone soil moisture content and roughness length for heat in a newly developed multi-component land surface parameterization scheme, embedded in a regional weather forecast model. The ATSR surface temperature data have a strong influence on the modification of the thermal roughness length. The optimal roughness length gradually changes over the growing season, as can be expected from the dependence of thermal roughness on vegetation density. Application of the method to a grassland scene in The Netherlands resulted in a much smaller adjustment to the thermal roughness length. The distribution of the roughness over the Spanish test area appeared to be consistent in time, as correlation coefficients of roughness values between two subsequent acquisition dates were significantly positive. Small improvements in the calculated surface energy balance appear from independent near-surface air temperature observations in the Spanish area. The use of bi-angular thermal infrared observations seems useful to improve the description of aerodynamic roughness properties on regional scales.

Effect of spatial variation on areal evapotranspiration simulation in Haibei, Tibet plateau, China

Quantification of areal evapotranspiration from remote sensing data requires the determination of surface energy balance components with support of field observations. Much attention should be given to spatial resolution sensitivity to the physics of surface heterogeneity. Using the Priestley–Taylor model, we generated evapotranspiration maps at several spatial resolutions for a heterogeneous area at Haibei, and validated the evapotranspiration maps with the flux tower data. The results suggested that the mean values for all evapotranspiration maps were quite similar but their standard deviations decreased with the coarsening of spatial resolution. When the resolution transcended about 480 m, the standard deviations drastically decreased, indicating a loss of spatial structure information of the original resolution evapotranspiration map. The absolute values of relative errors of the points for evapotranspiration maps showed a fluctuant trend as spatial resolution of input parameter data layers coarsening, and the absolute value of relative errors reached minimum when pixel size of map matched up to measuring scale of eddy covariance system. Finally, based on the analyses of the semi‐variogram of the original resolution evapotranspiration map and the shapes of spatial autocorrelation indices of Moran and Geary for evapotranspiration maps at different resolutions, an appropriate resolution was suggested for the areal evapotranspiration simulation in this study area.