Rain storage in forests detected with ERS tandem mission SAR

Joost de Jong, Wim Klaassen, Albert Ballast

OnderzoeksoutputAcademicpeer review

16 Citaten (Scopus)
264 Downloads (Pure)

Samenvatting

Rainfall interception by vegetation is a major component in the hydrological balance at the land surface. Small-scale variations in rainfall interception occur when both rainfall and land surface are highly variable. A key parameter of interception is the amount of rain stored on vegetation. As radar backscatter is strongly influenced by the free-water content of vegetation, SAR remote sensing might be applied to analyze large-scale rainfall interception. We concentrated in this study on C-band radar and rainfall storage in forests. The backscatter sensitivity to wetness is simulated with a radiative transfer model, which has been modified to describe the changes in dimension and dielectric constant of leaves and needles due to wetting. The simulations indicate that backscatter may decrease when a sparse coniferous forest is wetted, while the backscatter of a closed forest is found to increase with 1-4 dB due to rain storage. Thus, the sensitivity to storage strongly depends on the type of forest. The simulations are empirically tested by analyzing two sets of successive SAR image pairs from the ERS tandem mission. Given the short time between these measurements, it is argued that backscatter changes are caused mainly by changes in rain storage. The observed backscatter change is compared with wetness change estimated by a stand are hydrological model using ground-based rain radar observations as input. The observed backscatter change between a wet and a dry forest varied between 0.7 dB and 2.5 dB, in the range of the simulations. It is concluded that C-band SAR is sensitive to forest wetness, although for a quantitative assessment of water storage on forest additional information on a least forest structure is needed. (C) Elsevier Science Inc., 2000.

Originele taal-2English
Pagina's (van-tot)170-180
Aantal pagina's11
TijdschriftRemote Sensing of Environment
Volume72
Nummer van het tijdschrift2
DOI's
StatusPublished - mei-2000

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