Retrieving land-surface temperature with split-window algorithm was firstly applied to NOAA-AVHRR data.
With the application of MODIS sensor, its data has been used more and more widely. Since MODIS sensor is able
to observe vapor in the air, it can provide the parameters including vapor content and atmospheric transmissivity
for split-window algorithm which can thus be applied more conveniently. The article, adopting the split-window
algorithms of Becker-Li (1990), Sobrino (1991) and Qin Zhihao (2005), retrieves the surface temperature at
daytime and nighttime with MODIS1B data and compares with the surface temperature products of NASA. Finally,
the algorithm of Qin Zhihao is demonstrated to be the one with higher accuracy at daytime and nighttime and the
algorithm for surface temperature at nighttime is simple with acceptable accuracy.
The use of remote sensing technology to estimate regional evapotranspiration has been carried out for many years.
Recently, with the advancements in quantification of remote sensing and the access of MODIS data, more scientists have
been using MODIS data to monitoring regional evapotranspiration (ET) instead of the NOAA/AVHRR data. The surface
energy balance algorithm for land (SEBAL) model combined with NOAA/AVHRR and MODIS data separately is
applied to estimate the 24-hour regional evapotranspiration in a semi-arid agricultural area of northern China. And the
SEBAL regional evapotranspiration model calculated results from MODIS and NOAA/AVHRR data are compared with
the in-situ measured ground surface evaporation. The analysis shows that in estimating regional evapotranspiration of the
satellite based application, MODIS data is more appropriate than NOAA/AVHRR data.