GB/T 36100-2018 in English

Quality Evaluation Indicators for Airborne LiDAR Point Cloud Data

1. Background of Standard Formulation

With the rapid development of LiDAR technology, airborne LiDAR (LiDAR) has been widely used in surveying and mapping, geographic information, disaster monitoring and other fields. In order to ensure the quality of LiDAR point cloud data, the GB/T 36100-2018 standard came into being, aiming to provide unified data quality evaluation indicators and calculation methods.

2. Comparison of standard frameworks

3. Interpretation of core technologies

5.1 LiDAR point cloud density calculation method

Formula analysis:

Wherein, $\rho$ represents the point cloud density, in units of points/square meter; $n$ is the total number of laser points in the survey area, $n_i$ is the number of laser points in the $i$th water area, $m$ is the total number of water areas, $A$ is the area of the entire survey area, and $A_i$ is the coverage area of the $i$th water area.

5.2 Elevation accuracy evaluation indicators

4. Implementation suggestions

Data collection: Ensure the calibration and stability of the lidar equipment, especially under complex terrain conditions.

Quality control: During data processing, strictly perform error analysis according to the calculation formula in the standard, and regularly check the quality indicators of point cloud data.

Application optimization: Adjust the weight of the evaluation indicators according to the specific application scenario, such as adding the assessment of flight strip splicing errors in areas with drastic elevation changes.