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| Titel |
Synergy between passive (SMOS) and active (RADARSAT-2) microwave soil moisture over Berambadi, India |
| VerfasserIn |
Sat Kumar Tomer, Ahmad Al Bitar, Muddu Sekhar, Olivier Merlin, Soumya Bandyopadhyay, Yann Kerr |
| Konferenz |
EGU General Assembly 2013
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250080919
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| Zusammenfassung |
| This study presents comparison and analysis towards blending of the SMOS derived soil
moisture and RADARSAT-2 derived soil moisture over the Berambadi watershed, South
India. SMOS (Soil Moisture and Ocean Salinity) satellite from ESA has a passive microwave
L-Band sensor providing acquisition at ~40 km resolution and less than 3 days temporal
resolution. RADARSAT-2 is an active microwave sensor from (CSA) operating in C-Band at
a decametric spatial resolution and 24 days temporal resolution. Both satellites are
all-weather satellites. SMOS is less impacted by roughness effects as it operates in passive
mode at L-Band compared to RADARSAT-2, which on the other hand has a significantly
higher spatial resolution.
Twenty four images of RADARSAT-2 and SMOS-L2UDP soil moisture product, along
with extensive field data collected in field campaigns during 2010-2012 in the framework of
the ongoing AMBHAS (Assimilation of Multi-satellite data at Berambadi watershed for
Hydrology And land Surface experiment) project were used in the analysis. A non parametric
algorithm based on the CDF transformation method was developed to retrieve the soil
moisture from RADARSAT-2 backscatter coefficient at a spatial resolution of 100 m. This
product is validated using a random sampling procedure to divide the data into
calibration and validation set each one consisting of 12 images. The developed algorithm
provided a good estimate of the surface soil moisture with a RMSE of 0.05 m3
m-3.
Then the validated RADARSAT-2 soil moisture maps were upscaled to compare with the
SMOS data. Eight upscaling strategies were considered, taking into account the surface
heterogeneity in terms of texture (clay sand), surface cover (forest, land cover) and SMOS
mean antenna pattern. The strategies use linear combination of the different parameters.
Significant differences were observed between the eight strategies. The RMSE and coefficient
of determination of the different strategies varied between 0.06-0.09 m3 m-3 and 0.3-0.9
respectively. The best comparisons with a RMSE of 0.06 m3 m-3 and a coefficient of
determination of 0.7 were obtained for upscaling strategies that include land cover
effect.
This result was used in the development of a downscaling procedure to merge the
spatial information from RADARSAT-2 with the temporal dynamics from SMOS
acquisitions. In order to implement this method the persistence of the spatial patterns in the
RADARSAT-2 soil moisture map were evaluated by inspecting the spatiotemporal correlation
coefficient across the two years, which was approximately 0.55. The impact of rain and
farming activities were also taken into consideration in the analysis of the spatial
heterogeneity.
This study shows the potential synergy between the use of active/passive microwave soil
moisture retrievals for spatial and temporal down-scaling of soil moisture. This study also
shows the potential synergies between SMOS and SMAP (Soil Moisture Active Passive)
mission from NASA due to launch in 2015 since SMAP will make active L-band
acquisitions. |
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