Forest stand growth modeling method based on relation model

Abstract

The invention relates to a forest stand growth modeling method based on a relation model. The method includes the following steps that (1) tree trunks are established, and the trunks are considered as models respectively formed by a single cone frustum or multiple cone frustums; (2) bending of the trunks is controlled, the bending degree of the trunks is controlled by adjusting the relative positions of the cone frustums, the shapes of the tree trunks are fit into a parabola set, and every two adjacent cone frustums are processed in a smooth splicing mode; (3) the angles of elevation of branches are controlled, the branches are set on the trunks, the angles of elevation of the branches are set to obey the normal distribution law, and the initial angles of elevation of the branches are determined through a probability density function and a random function; (4) the azimuth angles of the branches are controlled, and the azimuth angles of the branches are controlled through a chaos function; (5) leaves are drawn, the leaves are set on the branches, and image vectorization and triangularization subdivision or leave photo transparency efficient processing are adopted; (6) a tree growth model is established; (7) a forest stand growth model is established. Compared with the prior art, the forest stand growth modeling method has the advantages that modeling is performed based on a small amount of actually measured data of trees, trees and forest stands can be vividly simulated while efficient and fast modeling is achieved.

Description

technical field [0001] The invention relates to a stand growth modeling method based on a relational model, which can be used for software realization of simulating stand growth. Background technique [0002] Since the 21st century, with the rapid development of disciplines such as computer, network, remote sensing technology and 3D information technology, these technologies have gradually become research hotspots in forestry science and application. The proposal of "digital forestry" and "smart forestry" construction strategies has greatly accelerated the pace of forestry informatization, making forestry management develop from simple information management to business decision-making. The dynamic simulation of the three-dimensional structure of stand growth can describe the three-dimensional visualization graphics of stand dynamic changes, three-dimensionally reflect the spatial pattern of stand and the utilization status of forest land, and more intuitively simulate the d...

AI Technical Summary

Problems solved by technology

However, due to the limitations of relevant theories and algorithms, these methods can only be an approximate simulation of natural trees, especially for trees of the same type, the generated models often have more than commonality but not enough individuality

Compared with the tree modeling method based on geometric parameters, the image-based tree modeling method reduces the dependence on tree structure data information, but this method is based on two-dimensional image modeling of trees, which requires complex image analysis processing, segmenting the branches from the image, and extracting effective information for modeling. This process is very difficult, and the validity and accuracy of the obtained information are difficult to control, and the accuracy and authenticity of the constructed model are not high.

The geometric model of trees used in the 3D modeling of forest growth is too simple, lacks professional 3D modeling algorithms, and cannot dynamically simulate the evolution process of forest growth in 3D scenes, and the interactivity is not strong; most of the existing research work is on a single problem However, there is no systematic solution; there is no professional software platform, and there are few and immature professional software systems or functional subsystems developed based on the bottom layer, so it is difficult to form a practical software system to guide forest production and management; forestry The degree of combination and integration of technology and information technology is not high enough, and there are very few researchers who have a solid professional foundation for both technologies, or the communication between different professional researchers is limited, which hinders the in-depth research and development of related technologies; for The research on forest stand growth prediction is mainly concentrated on the theoretical level, that is, using graphs to represent the overall predicted growth of each growth factor in the forest stand, but there is little research on the growth of individual trees in the forest stand. Prediction is not realistic enough

If you want to predict the growth of a single tree, you must study the competition situation, but the competition factors are complex and diverse, even as many as hundreds, which brings great difficulties to the forest growth prediction modeling

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