A method for estimating the cutting volume of coniferous forest based on two-stage unmanned aerial vehicle images

Abstract

The invention relates to a method for estimating the cutting volume of coniferous forest based on two-stage unmanned aerial vehicle images. The unmanned aerial vehicle (UAV) images were obtained before and after cutting in the coniferous forest cutting area, then the azimuth elements inside and outside the aerial photograph are automatically calculated to generate mosaic images and image point clouds, which are geometrically precisely corrected by ground control points. By a point cloud matching method, the position of each tree corresponds to the corresponding ground position one by one, andthe canopy point clouds and ground point clouds are obtained by cloth simulation filtering algorithm. The canopy height model of cutting area is obtained by subtracting the difference of DEM generatedby point cloud from the digital surface model generated by point cloud of forest canopy. The canopy height model was processed by using the local maximum method of dynamic windows, and the position of each coniferous tree in the cutting area was obtained. A DBH-tree height regression model is researched and established, according to the binary standing volume formula, the volume of single timberand the felling volume are calculated. The method of the invention provides a new way for fast, efficient, objective and accurate estimation of cutting volume of coniferous forest.

Description

technical field [0001] The invention relates to the field of battery testing, in particular to a method for estimating the logging volume of coniferous forests based on two-phase unmanned aerial vehicle images. Background technique [0002] Forest volume refers to the total volume of tree trunks existing in a certain forest area (Meng Xianyu, 2006). It is an important basis to reflect the richness of forest resources and measure the quality of forest ecological environment. It is also an important symbol of forest carbon sequestration capacity and an important component of forest aboveground biomass. Therefore, stock volume is an important stand survey factor, which provides an important basis for forest logging, utilization and management (Xie Shiqin et al., 2017). Due to the shortcomings of high labor intensity, long survey period, time-consuming and labor-intensive and other shortcomings, the forest stock volume data obtained by the traditional first- and second-class fo...

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Problems solved by technology

[0004] Based on the research content of scholars at home and abroad, it is found that most of the research areas for stock volume estimation are flat forestry plots, and less attention has been paid to small forestry areas such as mountainous areas in Fujian Province with large altitude differences and steep terrain, especially for forest logging. There are few research reports on the remote sensing estimation of stock volume by UAV

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