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Due to their low spatial resolution (≥ 10 km), passive microwave data from satellites often contain many mixed pixels. This is one of the main reasons that the retrieval accuracy of snow depth data is unsatisfactory for current practical demands. This paper proposes a multifrequency dual-polarized passive microwave unmixing method for snow. The land cover type of the observation area is partitioned...
Due to the low spatial resolution of passive microwave sensors, the spatiotemporal heterogeneity of snow parameters may be the primary factor influencing the inversion accuracy. However, at present, continuous observations of snow parameters are rare due to the limited automation of snow monitoring equipment. In this study, a passive microwave pixel is selected as the experimental region, and detailed...
Sensitivity analysis of model parameters is a very important step in the process of model regionalization application. By applying the statistical analysis on a vast amount of model outputs against the random combinations of the model parameters, the sensitivity index was first calculated for each parameter in the Microwave Emission Model of Layered Snowpacks (MEMLS). The result shows that the sensitivity...
The snow depth and the amount of regional snow play an important role in the climate change and also affect the management of water resources, and the estimate of the runoff and flood forecasting. At present, snow depth is generally thought to be linearly dependent on the difference of the brightness temperature (i.e. NASA algorithm) in passive microwave remote sensing. But some authors argued according...
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