Publications

Peng, Jian; Loew, Alexander (2014). Evaluation of Daytime Evaporative Fraction from MODIS TOA Radiances Using FLUXNET Observations. REMOTE SENSING, 6(7), 5959-5975.

Abstract
In recent decades, the land surface temperature/vegetation index (LST/NDVI) feature space has been widely used to estimate actual evapotranspiration (ETa) or evaporative fraction (EF, defined as the ratio of latent heat flux to surface available energy). Traditionally, it is essential to pre-process satellite top of atmosphere (TOA) radiances to obtain LST before estimating EF. However, pre-processing TOA radiances is a cumbersome task including corrections for atmospheric, adjacency and directional effects. Based on the contextual relationship between LST and NDVI, some studies proposed the direct use of TOA radiances instead of satellite retrieved LST products to estimate EF, and found that use of TOA radiances is applicable in some regional studies. The purpose of the present study is to test the robustness of the TOA radiances based EF estimation scheme over different climatic and surface conditions. Flux measurements from 16 FLUXNET (a global network of eddy covariance towers) sites were used to validate the Moderate Resolution Imaging Spectro radiometer (MODIS) TOA radiances estimated daytime EF. It is found that the EF estimates perform well across a wide variety of climate and biome types-Grasslands, crops, cropland/natural vegetation mosaic, closed shrublands, mixed forest, deciduous broadleaf forest, and savannas. The overall mean bias error (BIAS), mean absolute difference (MAD), root mean square difference (RMSD) and correlation coefficient (R) values for all the sites are 0.018, 0.147, 0.178 and 0.590, respectively, which are comparable with published results in the literature. We conclude that the direct use of measured TOA radiances instead of LST to estimate daytime EF can avoid complex atmospheric corrections associated with the satellite derived products, and would facilitate the relevant applications where minimum pre-processing is important.

DOI:
10.3390/rs6075959

ISSN:
2072-4292