Post on 31-Mar-2015
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