Individual tree automatic extraction method based on multispectral LiDAR data

Abstract

The invention discloses an individual tree automatic extraction method based on multispectral LiDAR data. The method comprises the following steps that the nearest neighbor search method is adopted on each laser point in the benchmark point cloud data with the point cloud of any band of the LiDAR data acting as the benchmark data, and band information of the nearest laser point is acquired in the data of other bands so that the single fusion point cloud data including multispectral information are generated; multi-perspective projection is performed along the Z-direction of the single fusion point cloud data including multispectral information, and the point cloud data are segmented into ground point cloud data and non-ground point cloud data; clustering and normalized segmentation are performed on the non-ground point cloud data, and segmentation is performed according to the geometric and spectral characteristics of the point cloud data so that semantically independent local point cloud blocks are obtained through separation; and a tree target overall characteristic description model based on the three-dimensional local abstract class characteristics is established to perform individual tree automatic extraction processing based on deep learning. The individual tree automatic extraction method based on the multispectral LiDAR data has the advantages of enhancing the tree identification accuracy.

Description

technical field [0001] The invention relates to laser radar data processing and information extraction technology, and is an automatic single tree extraction method based on multispectral LiDAR data. Background technique [0002] LiDAR (Light Detection And Ranging, referred to as LiDAR) is the use of GPS (Global Position System) and IMU (Inertial Measurement Unit, inertial measurement unit) airborne laser scanning; the measured data is a digital surface model (Digital Surface Model, DSM ), the data contains spatial three-dimensional information and laser intensity information; the digital elevation model can be obtained by removing the measurement points such as buildings, man-made objects, and covering plants from these original digital surface models by applying classification (Classification) technology (Digital ElevationModel, DEM), and at the same time obtain the height of the ground cover; use lasers as the emission light source, active remote sensing equipment using p...

AI Technical Summary

Problems solved by technology

However, the data it acquires is not only the sum of the point cloud data collected by all bands, but also has massive characteristics; and the point cloud data collected by multiple bands does not overlap, and there is a certain offset between them (multispectral machine The LiDAR system does not emit beams of all bands at the same time, but there is a small angular deviation between each emitted beam), which brings challenges to the processing method of multispectral LiDAR data

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