کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
568666 | 1452320 | 2012 | 4 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: A three-dimensional gap filling method for large geophysical datasets: Application to global satellite soil moisture observations A three-dimensional gap filling method for large geophysical datasets: Application to global satellite soil moisture observations](/preview/png/568666.png)
The presence of data gaps is always a concern in geophysical records, creating not only difficulty in interpretation but, more importantly, also a large source of uncertainty in data analysis. Filling the data gaps is a necessity for use in statistical modeling. There are numerous approaches for this purpose. However, particularly challenging are the increasing number of very large spatio-temporal datasets such as those from Earth observations satellites. Here we introduce an efficient three-dimensional method based on discrete cosine transforms, which explicitly utilizes information from both time and space to predict the missing values. To analyze its performance, the method was applied to a global soil moisture product derived from satellite images. We also executed a validation by introducing synthetic gaps. It is shown this method is capable of filling data gaps in the global soil moisture dataset with very high accuracy.
Journal: Environmental Modelling & Software - Volume 30, April 2012, Pages 139–142