This study implements the “neighboring-pixel” (NP) theoretical method, which uses spatially and temporally NPs to reconstruct cloud-contaminated pixels in daily Moderate Resolution Imaging Spectroradiometer (MODIS) land-surface temperature (LST) products. The 2012 MODIS LSTs of the Heihe River Basin (HRB) region in China are used as an example, and the ground-measured LSTs obtained at 17 sites from the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) project are used to validate the reconstruction results. The results show a bias of 0.25 K and RMSE of 4.122 K during the day and a bias of −0.1263 K and RMSE of 2.901 K at night. The error analysis reveals an uncertainty in the estimation of the cloud-contaminated pixels that can be attributed to errors in the estimation of parameters and net solar radiation retrieval and inaccuracies inherent in the NP scheme. The analysis results reveal that the time-gap effect is the main cause of uncertainty in the nighttime reconstruction, whereas the large extreme cases for the daytime reconstruction are generally caused by strong convection systems that usually occur with heavy precipitation in the cloud-contaminated pixels. Despite the uncertainty, the proposed approach is promising for the improvement of MODIS LST application in practice.
Gross Primary Production (GPP) is the sum of carbon absorbed by plant canopy. It is a key measurement of carbon mass
flux in carbon cycle studies. Remote sensing based light use efficiency model is a widely used method to estimate
regional GPP. In this study, MODIS-PSN was used to estimate GPP in Heihe River Basin. In order to better the model
accuracy, maximum light use efficiency (<i>ε</i>0) in MODIS-PSN is estimated using local observed carbon flux data and
meteorological data. After adjustment of parameter <i>ε</i>0, MODIS-PSN can correctly estimate GPP for major vegetation
type in the Heihe River Basin. Then, yearly GPP over Heihe River Basin was estimated. The results indicated that about
1.4*10<sup>13</sup>g carbon enter terrestrial ecosystem through vegetation photosynthesis in the Heihe River Basin one year. In
contrast, there is just 5.73*10<sub>13</sub>g carbon enter terrestrial ecosystem according to the standard MODIS GPP product,
which is greatly underestimated GPP in the Heihe River Bain.
It is very necessary to validate MODIS land surface temperature (LST) for its application, especially in the arid and
semi-arid regions. In this study, the Terra and Aqua MODIS 1km daily LST products (MOD/MYD11A1) are validated
using ground based longwave radiation observation. The longwave radiation ground measurements during 2008 to 2009
were collected from four automatic weather stations in the Heihe River Basin. In this validation process, the land surface
broadband emissivities of the validation stations were obtained from ASTER Spectral library. Then the ground-measured
LSTs of validation stations were converted from surface longwave radiation based on Stefan-Boltzmann's law and
thermal radioactive transfer theory. The validation results indicated that: except for DYKGT station, the mean bias was
less then 1K and the mean absolute error (MAE) range was about 2-3K; MYD11A1 LSTs from Aqua have larger biases,
MAEs, and RMSDs than that of MOD11A1 LSTs from Terra in most cases. The comparisons with ground measured LSTs show that the MAEs and RMSDs from daytime MOD/MYD11A1 comparisons are larger than that from nighttime MOD/MYD11A1 comparisons.