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Simple algorithm to determine the near-edge smoke boundaries with scanning lidar
Vladimir A Kovalev1, Jenny Newton, Cyle Wold
1Fire Sciences Laboratory, Forest Service, U.S. Department of Agriculture, P.O. Box 8089, Missoula, Montana 59807, USA. vkovalev@fs.fed.us
Applied Optics
|April 9, 2005
Summary
This study introduces a new lidar algorithm to accurately detect smoke plume edges without needing predefined thresholds. The robust method effectively identifies boundaries even with noisy data, improving fire monitoring capabilities.
Area of Science:
- Atmospheric Science
- Environmental Monitoring
- Remote Sensing
Background:
- Accurate determination of smoke plume boundaries is crucial for air quality assessment and fire management.
- Existing lidar methods often rely on empirical criteria or threshold values, limiting their adaptability.
- Signal noise, particularly at the far range, can challenge the precise detection of plume edges.
Purpose of the Study:
- To develop and validate a modified gradient algorithm for precise near-edge smoke plume boundary detection using scanning lidar.
- To eliminate the need for empirical criteria and a priori threshold selection in smoke boundary determination.
- To assess the algorithm's robustness against signal random noise in lidar measurements.
Main Methods:
- A modified gradient algorithm was developed, calculating the running derivative of the ratio of signal standard deviation (STD) to the accumulated sum of STD.
- The global maximum of this derived function was identified to pinpoint smoke plume boundaries.
- The algorithm was tested using experimental data from a scanning lidar operated during prescribed fires.
Main Results:
- The modified gradient algorithm successfully identified near-edge smoke plume boundaries without requiring empirical criteria or threshold settings.
- The method demonstrated robustness against signal random noise, particularly at the far end of the lidar measurement range.
- Analysis of experimental data confirmed the algorithm's reliability and effectiveness in real-world prescribed fire scenarios.
Conclusions:
- The proposed modified gradient algorithm offers an objective and robust approach for determining smoke plume boundaries using lidar backscatter signals.
- This method enhances the capability for accurate smoke plume characterization in environmental and fire science applications.
- The algorithm's insensitivity to noise and lack of empirical dependencies make it a valuable tool for advanced lidar data analysis.