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| Titel |
An algorithm for generating soil moisture and snow depth maps from microwave spaceborne radiometers: HydroAlgo |
| VerfasserIn |
E. Santi, S. Pettinato, S. Paloscia, P. Pampaloni, G. Macelloni, M. Brogioni |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 16, no. 10 ; Nr. 16, no. 10 (2012-10-16), S.3659-3676 |
| Datensatznummer |
250013520
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| Publikation (Nr.) |
 copernicus.org/hess-16-3659-2012.pdf |
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| Zusammenfassung |
| A systematic and timely monitoring of land surface parameters that affect
the hydrological cycle at local and global scales is of primary importance
in obtaining a better understanding of geophysical processes and in managing
environmental resources as well as natural disasters. Soil moisture and snow
water equivalent are two quantities that play a major role in these
applications. In this paper an algorithm for hydrological purposes (called
hereinafter HydroAlgo), which is able to generate maps of snow depth (SD)
and soil moisture content (SMC) from AMSR-E data, has been developed and
implemented within the framework of the JAXA ADEOS-II/AMSR-E and GCOM/AMSR-2
programs, as well as of a project of the Italian Space Agency that is
devoted to civil protection from floods and landslides. As auxiliary output,
the algorithm also generates maps of vegetation biomass (VB). An initial
phase of pre-processing includes the improvement of spatial resolution, as
well as masking for urban areas, water bodies, and dense vegetation. The
algorithm was then split into two branches, the first of which focused on
the retrieval of SMC and the second, on SD. Both parameters were retrieved
using Artificial Neural Network (ANN) methods. The algorithm was calibrated
using a wide set of experimental data collected on three sites: Mongolia and
Australia (for SMC), and Siberia (for SD), integrated with model
simulations. These results were then validated by comparing the algorithm
outputs with experimental data collected on two additional sites: a part of
a watershed in Northern Italy, and a large portion of Scandinavia. An
additional test of the algorithm was also performed on a large scale, and
included sites characterized by differing climatic and meteorological
conditions. |
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