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Evaluating sound attenuation of single trees using 3D information.

Jian Lu1, Fanhua Kong1, Haiwei Yin2

  • 1School of Geography and Ocean Science, Nanjing University, Xianlin Ave.163, 210023, Nanjing, China.

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|October 11, 2024
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Summary

Single trees can reduce urban noise pollution by 2-3 dBA, particularly at higher frequencies. Tree canopy characteristics, like leaf area index, significantly impact sound attenuation, aiding urban soundscape planning.

Keywords:
3D tree characteristicsLiDARSingle treesSound attenuationSupport vector machine prediction

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Area of Science:

  • Urban ecology
  • Acoustics
  • Environmental science

Background:

  • Urban noise pollution is a growing concern impacting public health.
  • While urban tree belts are known noise buffers, the acoustic impact of individual trees is understudied.
  • Understanding single-tree sound mitigation is crucial for optimizing urban soundscapes.

Purpose of the Study:

  • To develop a methodology for evaluating and predicting the sound attenuation of single trees.
  • To identify key 3D tree morphological characteristics influencing noise propagation.
  • To establish a predictive model for single-tree sound attenuation.

Main Methods:

  • Terrestrial LiDAR was used to extract 3D structural characteristics of 26 trees.
  • Sound attenuation was quantified using a controlled sound source and receiver setup.
  • A support vector regression (SVR) model with a linear kernel was developed to predict sound attenuation based on tree morphology.

Main Results:

  • Single trees provided an insertion loss of 2-3 dBA, with greater attenuation at frequencies above 500 Hz.
  • Increased crown leaf area index and average leaf inclination significantly reduced sound levels.
  • The SVR-LN model demonstrated strong predictive performance (R² = 0.74) for sound attenuation using tree characteristics.

Conclusions:

  • Individual trees possess significant sound attenuation capabilities, influenced by canopy structure.
  • The developed methodology and SVR model offer a reliable framework for assessing tree acoustic performance.
  • Findings support strategic tree selection and planting for enhanced urban noise mitigation and healthier living environments.