Soil Moisture Remote Sensing

MSFC scientists have expertise in soil moisture remote sensing with particular emphasis on retrieval algorithm sensitivity and issues associated with validation. The team has recently developed an innovative algorithm for processing remotely sensed data that improves differentiation of image features. The team has also developed two methods for disaggregating passive microwave data from low to high resolution required by hydrologic models.


Focus Areas:

  • Passive microwave retrieval algorithm validation and sensitivity
  • Validation approach centered on distributed hydrologic modeling
  • Influence of near-surface moisture and temperature profiles
  • Characterization of emitting depth
  • Vegetation and surface roughness corrections
Experiments: Sensor Data Processing and Analysis:

     Modeling Tools

Microwave Radiative Transfer Model
Land Surface Hydrologic Model
Kalman Filter Assimilation Algorithm
Optimal Deconvolution Algorithm
Disaggregation Algorithm



          Active Leadership Role in Field Experiments

  • Design and conduct field experiments
  • Active role in national experiments
  • Supervised, directed field activities
  • Protocol development, instrument decisions


Technical Contact: Dr. Charles Laymon (
Responsible Official: Dr. James L. Smoot (
Page Curator: Diane Samuelson (