Soil Moisture Retrieval From ASAR Measurements Over Natural Surfaces With a Large Roughness Variability

Abstract

In this work, the accuracy of soil moisture retrieved from ASAR data over bare or sparsely vegetated surfaces is investigated by means of a simulation study. The soil moisture retrieval method is based on an optimization algorithm that appropriately inverts theoretical direct models by assimilating a priori information on surface parameters. In order to account for a large variability of roughness conditions, two complementary models have been used, namely the Integral Equation Method model and the Geometrical Optics model. The performance of the inversion method has been assessed on simulated noisy ASAR data, as a function of different a priori information quality level.

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Document Details

Document Type
Technical Report
Publication Date
Jul 25, 2005
Accession Number
ADA450255

Entities

People

  • F. Mattia
  • G. Pasquariello
  • G. Satalino
  • L. Dente

Tags

Communities of Interest

  • Sensors
  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Backscattering
  • C Band
  • Data Science
  • Data Sets
  • Dielectric Permittivity
  • Errors
  • Estimators
  • Information Science
  • Measurement
  • Moisture
  • Moisture Content
  • Noise
  • Random Variables
  • Roughness
  • Statistical Algorithms

Readers

  • Atmospheric Remote Sensing.
  • Calculus or Mathematical Analysis
  • Radar Systems Engineering.