Scaling Algorithms

MSFC scientists have developed algorithms to enhance the spatial characteristics of remote sensing data and thus improve its usefulness in hydrologic models and other hydrologic applications. These include algorithms for disaggregating low-resolution microwave remote sensing data to the higher resolutions required by models and another to enhance the clarity of microwave data by taking advantage of the typical over-sampling performed by microwave remote sensors.


Focus Areas:

  • Developed two methods for disaggregating low resolution passive microwave data to high resolution required by hydrologic models
  • Developed an innovative algorithm for processing remotely sensed data that improves differentiation of image features

Benchmark Applications:

Optimal Deconvolution (ODC) uses mathematical reconstruction of sensor response functions to better characterize true microwave brightness temperature representation of features on the groung (e.g. agricultural field).


Scaling Algorithms

  • Airborne and satellite microwave sensors : Add value by improving spatial characteristics of remotely sensed data
  • Hydrology models and water management decision support tools: Provide improved soil moisture information

Technical Contact: Dr. Bill Crosson (
Responsible Official: Dr. James L. Smoot (
Page Curator: Diane Samuelson (