研究目的
To present the latest development of the DART LiDAR module, specifically Gaussian decomposition of simulated ALS and TLS waveforms and provision of LiDAR data in standard formats.
研究成果
The development enhances DART's capability to simulate LiDAR data in standard formats, bridging the gap between simulations and real data processing. It supports applications in validation, sensitivity studies, and inversion accuracy assessments for ALS and TLS systems.
研究不足
The complexity of waveform data management in LAS format and the need for efficient storage for high pulse repetition frequencies in ALS and TLS systems are noted. The model may not cover all real-world variations in LiDAR systems.
1：Experimental Design and Method Selection:
The study uses the DART model to simulate LiDAR waveforms for ALS and TLS systems, employing Gaussian decomposition to convert waveforms into point clouds. The method includes quasi-Monte Carlo Ray Tracing for waveform simulation and integration with laspy library for LAS format conversion.
2：Sample Selection and Data Sources:
Simulated 3-D scenes (e.g., 40m x 40m with houses and trees) are used, with user-defined configurations such as altitude, platform trajectory, and pulse divergence.
3：List of Experimental Equipment and Materials:
DART software (version 5.7.0), laspy library, CloudCompare software for visualization and processing.
4：0), laspy library, CloudCompare software for visualization and processing.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: DART reads the 3-D scene and LiDAR configurations, simulates waveforms using ray tracing, and processes them through Gaussian decomposition to output point clouds in text or LAS format with associated waveforms.
5：Data Analysis Methods:
Analysis involves converting waveforms to points with parameters like peak amplitude and temporal standard deviation, and using software like CloudCompare for further processing.
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