Method for estimating forest leaf-area index based on point cloud hemisphere slice

Abstract

The invention provides a method which can estimate the forest leaf-area index by means of ground laser point cloud data based on a point cloud hemisphere slice and belongs to the research field of a forest canopy structure parameter acquisition method. The method includes the following steps of: acquiring three-dimensional laser point cloud data of a vegetation canopy, and performing pretreatment on the three-dimensional laser point cloud data; automatically dividing the point cloud data into three types including the point cloud data of a photosynthesis canopy part (e.g. leaves and flowers), the point cloud data of a non-photosynthesis canopy part (e.g. trunks and branches) and the point cloud data of a bare land, based on a local set feature method; researching spatial distribution forms of the point cloud data of the photosynthesis canopy part and the point cloud data of the non-photosynthesis canopy part in a three-dimensional space according to a radial hemisphere point cloud slice algorithm, and calculating the angle porosity; calculating the extinction coefficient; extracting the effective leaf-area index; and evaluating a contribution value of a xylem part to calculation of the forest angle porosity and the forest effective leaf-area index according to a laser point cloud point-to-point classification result. The result show that: according to the ground laser point cloud data, the contribution rate of the xylem part to the effective leaf-area index is 19% to 54% in forests with different densities; and the correlation between the effective leaf-area index calculated by the method and the effective leaf-area index calculated through a fish-eye camera, reaches 74.27%. The method for estimating forest leaf-area index based on the point cloud hemisphere slice enriches the application that the ground laser point cloud data is used to extract a forest canopy three-dimensional structure and bio-physical parameters.

Description

1. Technical field [0001] The present invention relates to a method for estimating forest effective leaf area index (EffectiveLeaf-areaIndex, LAIe) using ground laser point cloud data, and evaluates the contribution of non-photosynthetic canopy to forest angle porosity (AngleGapFraction, AGF) and LAIe. 2. Background technology [0002] The forest canopy is usually divided into photosynthetic parts (such as leaves) and non-photosynthetic parts (such as trunks, branches and flowers). The spatial distribution of leaf elements affects light interception and radiation mechanisms within and below the canopy, which in turn affects plant biophysical processes and habitat distribution of plants and animals. Leaf-area Index (LAI) is generally used to quantitatively describe canopy leaf elements, and is usually defined as half of the total area of ​​green leaves per unit surface area. LAI can be measured by direct or indirect methods. Both aerial laser scanning system and terrestrial ...

AI Technical Summary

Problems solved by technology

Among them, the deficiency of using porosity theoretical model to measure LAI is that it cannot distinguish the non-photosynthetic part from photosynthetic tissue, which leads to process-based models like Boreal Ecosystem Productivity Simulator (BEPS) using porosity Uncertainty when calculating LAI

However, no one has considered the influence of the non-photosynthetic canopy in the laser point cloud on the leaf area index, and the calculated leaf area index is only the effective leaf area index, not the real leaf area index. The research theory and technology of canopy structure need to be further strengthened

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