Data from the Moderate-Resolution Imaging Spectroradiometer (<b>MODIS</b>) are being widely used for quantitatively
estimating parameters in the study of atmospheric and land surface processes. Cloud detection is a preliminarily
important step in remotely sensed image processing for many applications. In this article, an integrated method for
MODIS cloud detection based on band combinations within MODIS data itself was developed. Several MODIS data
were applied to evaluate the performance of the new algorithm and the results show that the new algorithm was satisfied
for quantitative cloud detection.
Evapotranspiration (ET) in regional scale is not only a major component of energy and water balance, but also a linking medium between ecological system and climatic system. Due to the increased needs from hydrological, climatological and ecological communities, more interest has been paid on developing algorithms to estimate ET over larger scales by means of combining remote sensing measurements of land surface parameters during the last decades. Compared to all previous remote sensing algorithms for heat fluxes estimations, the Surface Energy Balance System (SEBS) developed by Su (2002) has the most important advantage of its inclusion of a physical model for the estimation of the roughness height for heat transfer which is the most critical parameter in the parameterization of heat fluxes of land surface. In this paper, first, SEBS has been utilized to estimate the surface fluxes over HuangHuaiHai Plain in Northern China by using MODIS/TERRA images, in combination of meteorological data collected in meteorological stations distributed over the study area. The estimated fluxes by SEBS in clouds free days are first compared with the measurements from QRSLSP/Shunyi Campaign near Beijing (Liu et al.2002) and then compared to the measurements by Large Aperture Scintillometers (LAS) in Zhengzhou LAS station located in Henan Province, China. Both the comparisons show that the estimated fluxes from SEBS have a good agreement with the measurements. Based on the validation of the model, an extended modular of SEBS has been utilized to estimate daily ET over the study area and the results showed that the extended SEBS can be used to estimate daily ET over regional scale. Finally, limitations and special care in using SEBS are discussed.