A method for automatic extraction of forest canopy closure by UAV digital elevation model

Abstract

The invention discloses a method for automatically extracting forest canopy density through an unmanned aerial vehicle digital elevation model, and takes Dongtai Forest Farm of Jiangsu Province as the implementation object of the method. Firstly, the image data of Dongtai Forest Farm was acquired by UAV, and the image data was spliced ​​through digital modeling to extract the DEM data; then, the remote sensing image processing software was used to extract the pixel value interval of the non-canopy area in the target DEM data, And carry out mask processing, and finally obtain the proportion of the masked section and the non-masked section through statistical analysis, so as to obtain the accurate value of the forest canopy density. Compared with other canopy closure measurement algorithms, the accuracy and precision of this method have been greatly improved, especially the work efficiency has been greatly improved.

Description

technical field [0001] The invention belongs to the technical fields of forestry investigation, resource dynamic monitoring, biodiversity and the like, and relates to a method for automatically extracting forest canopy density through an unmanned aerial vehicle digital elevation model (UAV-DEM). Background technique [0002] Forest is an important material resource for the survival and development of human beings, and it plays a vital role in the balance of terrestrial ecosystems. Forest resource survey is an important task in the process of forest management and development. Implementing forest resource survey work can effectively understand Growth and decline of forest resources. In forest resources investigation, canopy density is a very important index parameter, which is of great significance to the assessment of the current situation of forest resources. [0003] The traditional methods for extracting canopy density of forest resources include visual inspection, canop...

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Problems solved by technology

[0003] The traditional methods for extracting canopy density of forest resources include visual inspection, canopy projection, line transect, sample point, and photograph. Since the development of remote sensing technology, researchers have tried to obtain the value of forest canopy density through remote sensing image data. At present, most of the image data based on this research are DOM (Digital Orthophoto) and DSM (Digital Surface Model), which requires professionals to assist a large number of in-house processing operations to complete, and at the same time, the accuracy is poor and the efficiency is low.

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