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Related Experiment Video

Updated: Jan 23, 2026

Methods of Soil Resampling to Monitor Changes in the Chemical Concentrations of Forest Soils
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APPLICATION OF THE FOREST SHIELDING FACTOR TO THE MAXIMUM-LIKELIHOOD EXPECTATION MAXIMIZATION METHOD FOR AIRBORNE

M Sasaki1, Y Sanada, A Yamamoto2

  • 1Sector of Fukushima Research and Development, Japan Atomic Energy Agency, 45-169 Sukakeba, Minamisoma, Fukushima, Japan.

Radiation Protection Dosimetry
|June 6, 2019
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Summary

This study enhances airborne radiation monitoring accuracy using the maximum-likelihood expectation maximization (ML-EM) method. Tree shielding factors, correlated with height, improve dose rate calculations in forests.

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Area of Science:

  • Environmental Science
  • Radiation Physics
  • Geospatial Analysis

Background:

  • Accurate airborne radiation monitoring is crucial for environmental safety.
  • The maximum-likelihood expectation maximization (ML-EM) method offers potential for improved accuracy.
  • Environmental factors like tree cover significantly influence radiation measurements.

Purpose of the Study:

  • To evaluate the shielding factor of trees for airborne radiation monitoring.
  • To integrate tree shielding factors into the ML-EM method for enhanced accuracy.
  • To assess the reliability of the improved ML-EM method for dose rate calculations in forested areas.

Main Methods:

  • Field radiation measurements were conducted to determine tree shielding factors.
  • Tree shielding factors were correlated with tree height.
  • The evaluated shielding factors were applied to the ML-EM method using data from Fukushima forest.

Main Results:

  • A strong correlation was found between tree shielding factors and tree heights.
  • The ML-EM method incorporating tree shielding factors provided more reliable dose rate calculations.
  • The proposed method demonstrated improved accuracy compared to conventional approaches.

Conclusions:

  • Tree height is a reliable indicator for estimating radiation shielding in forested environments.
  • Integrating tree shielding factors into the ML-EM method significantly enhances airborne radiation monitoring accuracy.
  • The developed approach offers a more dependable tool for assessing radiation levels in complex terrains.