MoistureMap: Multi-sensor Retrieval of Soil Moisture

Mahdi AllahmoradiPhD Candidate

Supervisor: Jeffrey Walker

Contributors:Dongryeol Ryu, Chris Rudiger

This research will test the hypothesis that This research will test the hypothesis that

more accurate soil moisture information can more accurate soil moisture information can

be derived from SMOS if vegetation and soil be derived from SMOS if vegetation and soil

temperature information are derived from temperature information are derived from

other coincident remote sensing observations other coincident remote sensing observations

at higher resolution. at higher resolution.

Research Aim

Ground/RS Data, Models, …

SMOS MoistureMap

SMOS overview

• SMOS Approximate launch date: May 2009 Lifetime: Minimum 3 years Frequency: L-band (21cm - 1.4 GHz) Orbit: Sun-synchronous Overpass time: 6 am - 6 pm Temporal resolution: 3 Days Spatial resolution: 40 - 50 km (35 km

at centre of Field of View)

SOURCE: ESA

Theoretical Aspect

The theory behind microwave remote sensing of soil moisture is based on the large contrastlarge contrast between the dielectric properties of liquid waterliquid water and dry soil.dry soil.

- For smooth bare soil (Planck’s law):

- Vegetated soil (Tau - omega model):

equation of Ulaby et al. (1986)

1 1 1 1b veg veg veg veg soilT e T e T

pb p soilT e Tpb p soilT e T

pb p soilT e T

Vegetation Effect

VWCb* Jackson, 93

'''* bLAIb Wigneron et al. 07

* b, b’ and b” are empirical parameters

Vegetation Effect:

NIR RED

NIR RED

R RNDVI

R R

Estimation of VWC using Vegetation indicesEstimation of VWC using Vegetation indices

NIR SWIRNDWI

NIR SWIR

Reduced sensitivity to VWC changes in dense vegetation(Jackson, 2004)

SWIR 1640 nm suitable for croplandsSWIR 2130 nm suitable for native vegetation (Maggioni, et al. 2006)

Brightness Temperature → Soil Moisture

Tb

Land Cover

Soil Moisture

Soil Temperature

Vegetation Water Content or LAI

Soil Texture

Surface Roughness

Modis Data

MTSAT 1R&

WindSatData

MaybeWindSat

Data

Modis Aqua

orWindSat

NAFE ground

data

Spaceborne Remote Sensors

• MODIS TerraTerra launched December 1999 AquaAqua 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

Spaceborne Remote Sensors

• WindSat Launched on 6th 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

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

Algorithm Development

Soil Temperature

Soil Moisture

Vegetation Water Content

Remotely Sensed Data

Modis Aqua/Terra

WindSat

MTSAT 1R

SMOSNAFE Airborne Data

VerificationVerification

NAFE Ground Data

Algorithm