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Related Concept Videos

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To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
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Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
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Correction scheme for close-range lidar returns.

Gionata Biavati1, Guido Di Donfrancesco, Francesco Cairo

  • 1Max Planck Institute for Biogeochemistry, Hans-Knoell-Strasse 10, 07745 Jena, Germany. gionata.biavati@bgc‐jena.mpg.de

Applied Optics
|October 22, 2011
PubMed
Summary

Elastic lidar systems struggle with close-range signals due to incomplete overlap. This study introduces a straightforward method using geometrical models and dual-angle lidar data to correct and retrieve these crucial near-field signals.

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Area of Science:

  • Atmospheric optics
  • Remote sensing technology
  • Laser physics

Background:

  • Elastic lidar systems face challenges in accurately measuring close-range atmospheric signals.
  • Defocusing and incomplete overlap between the laser beam and receiver field of view degrade signal quality.
  • Existing methods often fail to fully capture near-field backscatter data.

Purpose of the Study:

  • To develop and validate a novel method for estimating and correcting signal loss in elastic lidar systems at close ranges.
  • To enable the retrieval of accurate lidar signals within the region of incomplete overlap.
  • To improve the performance and data completeness of elastic lidar measurements.

Main Methods:

  • Empirical estimation and correction of signal loss due to incomplete overlap.
  • Utilization of a simple geometrical model of the lidar's optical apparatus.
  • Analysis of two lidar data acquisitions performed at different elevation angles.
  • Numerical correction optimization based on collected data.

Main Results:

  • Successfully demonstrated the ability to retrieve lidar signals in the region of incomplete overlap.
  • Validated the technique using both synthetic and experimental lidar data.
  • The proposed method provides an optimized numerical correction for signal loss.
  • The technique is straightforward to implement and effective.

Conclusions:

  • The developed method effectively addresses the challenge of incomplete overlap in elastic lidar systems.
  • Accurate retrieval of close-range backscatter signals is achievable with this approach.
  • This technique enhances the utility of elastic lidar for near-field atmospheric studies.
  • The geometrical model and dual-angle acquisition strategy offer a robust solution.