Sentinel-1 Surface Soil MoistureComparison against an optimized Metop ASCAT soil moisture product and in situ data in Lower Austria

Isabella Pfeil, Sebastian Hahn, Bernhard Bauer-Marschallinger, Mariette Vreugdenhil,

Simon Hochstöger, Wolfgang Wagner

Outline

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Introduction Study area

• In situ soil moisture network Petzenkirchen ASCAT optimization to local conditions Results

• Sentinel-1 vs. in situ soil moisture• Sentinel-1 vs. satellite soil moisture

Objectives

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Sentinel-1 surface soil moisture (SSM)• Available observations since 2014• TU Wien: development of SSM retrieval• Assessment of the performance of the current retrieval algorithm

Comparison to:• In situ soil moisture from a network in lower Austria• ASCAT SSM – optimized for test region

Study Area

Agricultural catchment (66 ha) In situ soil moisture network „Hydrological Open Air Laboratory“ (HOAL) 21 permanent, 11 temporary soil moisture stations Upscaled to coarse satellite footprint

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Optimization of the ASCAT SSM retrieval

Metop ASCAT

Advanced Scatterometer Data available since 2007 6-36 hours revisit rate 25 km spatial resolution WARP algorithm – soil moisture retrieval:

• Scaling between historically driest and wettest measurements

• Backscatter normalization• Cross-over angles (global: 25°, 40°)

Optimization to local conditions?• Test area: region around HOAL (lower Austria)

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(from Wagner et al., 2013)

Variation of the cross-over angles

Dry conditions: 25°, wet conditions: 40° (globally found) Can retrieval be improved over Petzenkirchen?

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Global parameters: varying bias over year Optimized parameters: larger bias, but constant over year

ASCAT SSM time series – 2015

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ASCAT-HOAL:Spearman‘s R: 0.54RMSD: 0.045

ASCAT-HOAL:Spearman‘s R: 0.72RMSD: 0.052

Retrieval with global parameters

Retrieval with optimized parameters

ASCAT SSM time series – 2016

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ASCAT-HOAL:Spearman‘s R: 0.18RMSD: 0.052

ASCAT-HOAL:Spearman‘s R: 0.30RMSD: 0.048

Retrieval with global parameters

Retrieval with optimized parameters

Global parameters: varying bias over year Optimized parameters: larger bias, rather constant over year

Validation of Sentinel-1 SSM

Sentinel-1 Surface Soil Moisture

Sentinel-1A: part of the ESA Copernicus Programme• Land surface monitoring at a very high spatial resolution

Soil moisture at 1 km spatial scale Temporal revisit time: 3-8 days (depending on location)

SSM retrieval• Adaptation of the TU Wien Change Detection Model• Scaling of the normalized backscatter between the historically driest and wettest

value

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𝑆𝑆𝑆𝑆𝑆𝑆 =𝜎𝜎40𝑜𝑜 − 𝜎𝜎𝑑𝑑𝑑𝑑𝑑𝑑(40)

𝑜𝑜

𝜎𝜎𝑤𝑤𝑤𝑤𝑤𝑤(40)𝑜𝑜 − 𝜎𝜎𝑑𝑑𝑑𝑑𝑑𝑑(40)

𝑜𝑜

(Rama, Cc-by-sa-2.0-fr)

Sentinel-1 Surface Soil Moisture

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20m SAR backscatter in dB 1km Soil Moisture in %

(from Bauer-Marschallinger et al., 2017)

Sentinel-1 SSM over HOAL

96 observations in 2015 and 2016 Averaged for 3x3 pixels over HOAL Masked for frozen air temperatures (in situ data) Absolute units: multiplication with porosity

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Sentinel-1 vs. ASCAT and in situ soil moisture

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Spearman‘s R: S1-ASCAT: 0.58S1-HOAL: 0.39p < 0.01

Spearman‘s R: S1-ASCAT: 0.61S1-HOAL: 0.36p < 0.05

Conclusions

ASCAT SSM retrieval parameters can be optimized• Better representation of regional conditions• A bias remains, but constant over year

SSM retrieval from Sentinel-1A• Correlations between 0.35 and 0.6• Static vegetation correction biases during growing period• Temporal coverage depending on location

Next steps• ASCAT optimization in other regions• Continue improvement of Sentinel-1 retrieval• Include Sentinel-1B

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References

Wagner, Wolfgang, Guido Lemoine, and Helmut Rott. "A method for estimatingsoil moisture from ERS scatterometer and soil data." Remote sensing ofenvironment 70.2 (1999): 191-207.

Pathe, Carsten, et al. "Using ENVISAT ASAR global mode data for surface soilmoisture retrieval over Oklahoma, USA." IEEE Transactions on Geoscience andRemote Sensing 47.2 (2009): 468-480.

Wagner, Wolfgang, et al. "The ASCAT soil moisture product: A review of its specifications, validation results, and emerging applications." MeteorologischeZeitschrift 22.1 (2013): 5-33.

Bauer-Marschallinger, Bernhard, et al. "1km Soil Moisture from DownsampledSentinel-1 SAR Data: Harnessing Assets and Overcoming Obstacles." EGU General Assembly Conference Abstracts. Vol. 19. 2017.

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