An intertidal zone salt marsh vegetation point cloud filtering method based on an XGboost algorithm

By combining UAV multi-line array LiDAR technology with the XGboost algorithm, and utilizing point cloud intensity, incident angle, distance, and normal vector features, a point cloud filtering model for intertidal salt marsh vegetation is constructed. This solves the problem of insufficient accuracy in obtaining terrain information in salt marsh vegetation-covered areas in traditional methods, and achieves high-precision point cloud filtering and terrain information acquisition.

CN117370800BActive Publication Date: 2026-07-24GUANGZHOU URBAN PLANNING & DESIGN SURVEY RES INST
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
GUANGZHOU URBAN PLANNING & DESIGN SURVEY RES INST
Filing Date
2023-10-09
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Traditional topographic surveying methods struggle to obtain high-precision digital elevation models in intertidal regions, especially in areas with dense salt marsh vegetation, making it difficult to accurately separate ground points from non-ground points.

Method used

Three-dimensional point cloud data of the intertidal zone was acquired using UAV multi-line array LiDAR technology. Point cloud intensity, incident angle, distance, elevation and normal vector were used as input features. The XGboost algorithm was used to construct a classification model of ground points and non-ground points. The objective function was optimized through gradient boosting strategy to achieve high-precision filtering of point cloud data.

Benefits of technology

It achieves high-precision filtering of point clouds of intertidal salt marsh vegetation, which can accurately separate ground points and non-ground points, improves the accuracy and applicability of terrain information acquisition, and avoids a complex intensity correction process.

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Abstract

The present application relates to unmanned aerial vehicle multi-line array LiDAR technical field, especially an intertidal zone salt marsh vegetation point cloud filtering method based on XGboost algorithm, adopts unmanned aerial vehicle multi-line array LiDAR technology to obtain the three-dimensional point cloud data of intertidal zone;XGboost algorithm is used to build the classification model of ground points and non-ground points, the classification model uses the point cloud intensity, incident angle, distance, elevation and normal vector in point cloud data as input features, the classification model built by XGboost algorithm is trained by the input features;The ground points and non-ground points in point cloud data are separated by using the classification model that has completed training.The present application has the advantages that: compared with traditional classic filtering algorithm, better results can be obtained, has stronger applicability and universality, and can replace the necessary complex intensity correction process when using intensity information for classification, can be well used for intertidal zone salt marsh vegetation point cloud filtering, and higher filtering precision can be obtained.
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