Downscaling SMAP soil moisture images with wavelets transform and PCA method
| Autor: | Garcia Gabriel, Venturini Virginia |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
010504 meteorology & atmospheric sciences
Pixel Moisture Soil science 04 agricultural and veterinary sciences 01 natural sciences Wavelet Principal component analysis 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Environmental science Spatial variability Image resolution Water content 0105 earth and related environmental sciences Remote sensing Downscaling |
| Zdroj: | 2017 First IEEE International Symposium of Geoscience and Remote Sensing (GRSS-CHILE). |
| Popis: | The soil moisture estimation is important for the management of natural and agricultural-livestock resources. Passive and active microwave satellite sensors are suitable for quantifying the moisture in the first centimeters of the soil. Passive sensors allow precise soil moisture estimation, but with low spatial resolution. Therefore, it is necessary to fuse them with products with better spatial resolution to enhance their applications. The main problem for re-scaling soil moisture is to find a variable whose spatial variability were similar to that of soil moisture. In this paper the improvement of the pixel size of SMAP images are proposed by their fusion with precipitation maps of the GPM mission. Although there are different fusion techniques, the wavelets and principal component methods are selected for this work, since the literature indicates that they are the most used. The results suggest that GPM precipitation maps are suitable for introducing variability in soil moisture maps and that wavelets results in lower errors than the principal component method, when compared with in situ data. The spatial distribution of soil moisture observations is not good enough to verify the detail of the spatial variability. |
| Databáze: | OpenAIRE |
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