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MoistureMap: Multi-sensor Retrieval of Soil Moisture Mahdi Allahmoradi PhD Candidate Supervisor: Jeffrey Walker Contributors: Dongryeol Ryu, Chris Rudiger.

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Presentation on theme: "MoistureMap: Multi-sensor Retrieval of Soil Moisture Mahdi Allahmoradi PhD Candidate Supervisor: Jeffrey Walker Contributors: Dongryeol Ryu, Chris Rudiger."— Presentation transcript:

1 MoistureMap: Multi-sensor Retrieval of Soil Moisture Mahdi Allahmoradi PhD Candidate Supervisor: Jeffrey Walker Contributors: Dongryeol Ryu, Chris Rudiger

2 This research will test the hypothesis that more accurate soil moisture information can be derived from SMOS if vegetation and soil temperature information are derived from other coincident remote sensing observations at higher resolution. Research Aim Ground/RS Data, Models, … SMOS MoistureMap

3 SMOS overview SMOS  Approximate launch date: May 2009  Lifetime: Minimum 3 years  Frequency: L-band (21cm GHz)  Orbit: Sun-synchronous  Overpass time: 6 am - 6 pm  Temporal resolution: 3 Days  Spatial resolution: km (35 km at centre of Field of View) SOURCE: ESA

4 Theoretical Aspect large contrast liquid waterdry soil. The theory behind microwave remote sensing of soil moisture is based on the large contrast between the dielectric properties of liquid water and dry soil. - For smooth bare soil (Planck’s law): - Vegetated soil (Tau - omega model): equation of Ulaby et al. (1986)

5 Vegetation Effect Jackson, 93 Wigneron et al. 07 * b, b’ and b” are empirical parameters Vegetation Effect: Estimation of VWC using Vegetation indices Reduced sensitivity to VWC changes in dense vegetation (Jackson, 2004) SWIR 1640 nm suitable for croplands SWIR 2130 nm suitable for native vegetation (Maggioni, et al. 2006)

6 Brightness Temperature → Soil Moisture Tb Land Cover Soil Moisture Soil Temperature Vegetation Water Content or LAI Soil Texture Surface Roughness Modis Data MTSAT 1R & WindSat Data Maybe WindSat Data Modis Aqua or WindSat NAFE ground data

7 Spaceborne Remote Sensors MODIS  Terra  Terra launched December 1999  Aqua  Aqua launched May 2002  Design Lifetime: 6 years  No. of Bands: 36  Orbit: Sun-synchronous  Overpass time: 10:30 am (Terra) – 13:30 pm (Aqua)  Temporal resolution: 2 days  Spatial resolution of bands: 250 m (1-2) 500 m (3-7) and 1 km (8-36) SOURCE: NASA

8 Spaceborne Remote Sensors WindSat  Launched on 6 th January 2003  Lifetime: Minimum 3 years  Frequencies: 6.8, 10.7, 18.7, 23.8, 37.0 GHz  Orbit: Sun-synchronous  Overpass time: 6 am / 6 pm  Spatial resolution: 8*13 km (for 37.0 GHz) SOURCE: US NAVAL RESEARCH LAB

9 Spaceborne Remote Sensors MTSAT-1R  Launched February 2005  Lifetime: 5 years for meteorological function, 10 years for aviation function  Bands: visible, Infrared (1-4)  orbit: Geostationary  Temporal resolution: 30 minutes  Spatial resolution: visible (1 km nadir), IR1-4 (4km nadir) SOURCE: JAPAN METHEOROLOGICAL AGENCY

10 Algorithm Development Soil Temperature Soil Moisture Vegetation Water Content Remotely Sensed Data Modis Aqua/Terra WindSat MTSAT 1R SMOS NAFE Airborne Data Verification NAFE Ground Data Algorithm


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