Forest stock volume distribution prediction method based on airborne laser radar data

An airborne laser radar and laser radar technology, which is applied in the field of sustainable forest management and ecological factor investigation, and forest resource monitoring, can solve the problem of not comprehensive and in-depth prediction of stock volume distribution indicators, and insufficient use of laser radar three-dimensional structure information, etc. problems, achieving strong adaptability and flexibility, maintaining biodiversity, and improving overall accuracy

Inactive Publication Date: 2019-01-08
NANJING FORESTRY UNIV
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Problems solved by technology

However, the above methods are all based on simple lidar variables and do not make full use of the three-dimensional structure information of lidar
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  • Forest stock volume distribution prediction method based on airborne laser radar data
  • Forest stock volume distribution prediction method based on airborne laser radar data
  • Forest stock volume distribution prediction method based on airborne laser radar data

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Embodiment 1

[0031] The implementation site of this example is located in Yushan National Forest Park, Changshu City, Jiangsu Province. The climate is a subtropical monsoon climate, with an annual average temperature of 15.4°C. The rainwater is concentrated in June to September, and the annual average precipitation is about 1047.7mm. The forest type belongs to urban man-made. The main forest types are broad-leaved forest, coniferous forest and mixed forest. Among them, the main broad-leaved tree species are cork oak (Quercus variabilis), white oak (Quercus fabri), liquidambar formosana (Liquidambar formosana), oak oak (Quercus aliena), oak oak (Quercus acutissima) and other deciduous broad-leaved tree species and some such as incense Camphor (Cinnamomum camphora), witch hazel (Liquidambar formasana), bayberry (Myrica rubra (Lour.) S.et Zucc), pistachio (Pistacia chinensis.), holly (Ilex chinensis) and other evergreen broad-leaved tree species; main coniferous tree species Evergreen conifer...

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Abstract

The invention discloses a forest stock volume distribution prediction method based on onboard laser radar data, and belongs to the field of the forest resource monitoring, forest sustainable management control and ecological factor investigation. The method comprises the following steps: firstly performing normalization processing on laser radar point cloud data, and extracting characteristic variables from the normalized point cloud data; performing optimization on the laser radar characteristic variables and inverting a Weibull scale parameter and a Weibull shape parameter by resolving the Weibull scale parameter and the Weibull shape parameter by adopting a maximum likelihood method; and finally predicting the forest stock volume distribution by using a two-parameter Weibull distribution parameter. Compared with other similar estimation method, total precision of the estimation method of the forest stock volume distribution disclosed by the invention is improved by 5% and more, themethod not only is beneficial to mechanism explanation of the characteristic variables, but also can be used for the natural forest and the secondary forest.

Description

technical field [0001] The invention belongs to the fields of forest resource monitoring, sustainable forest management and ecological factor investigation, and more specifically relates to a method for estimating forest volume distribution based on airborne laser radar data. Background technique [0002] Accurate forest stock distribution information is of great significance for forest resource monitoring, sustainable forest management and ecological factor investigation. At the same time, this information can also be used to grasp forest competition, maintain biodiversity, and strengthen sustainable forest management, which is of great significance for promoting global carbon balance. The conventional acquisition of forest stock distribution information mainly relies on field surveys, which has a large workload and is not conducive to the update of forest stock distribution information. As an active remote sensing technology, lidar technology (LiDAR) is less affected by w...

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Application Information

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IPC IPC(8): G01S17/88
CPCG01S17/88
Inventor 曹林张峥男佘光辉
Owner NANJING FORESTRY UNIV
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