Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A method for joint retrieval of forest structure parameters from full-waveform LiDAR and hyperspectral data

A laser radar and structural parameter technology, applied in the direction of electromagnetic wave re-radiation, radio wave measurement systems, instruments, etc., can solve the problems of not using full-waveform laser radar data, and comprehensive and in-depth extraction of forest canopy laser radar, etc., to achieve Enhance the ability to describe the spatial structure of the canopy, suppress the high forest coverage, and improve the effect of estimation accuracy

Active Publication Date: 2020-11-10
NANJING FORESTRY UNIV
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the above methods are all based on lidar point cloud data, and do not use full waveform lidar data that can better record the structural characteristics of the canopy
At the same time, there is no method for comprehensively and deeply extracting forest canopy lidar features (waveform features and point cloud features), spectral features and calculating forest structure parameters.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A method for joint retrieval of forest structure parameters from full-waveform LiDAR and hyperspectral data
  • A method for joint retrieval of forest structure parameters from full-waveform LiDAR and hyperspectral data
  • A method for joint retrieval of forest structure parameters from full-waveform LiDAR and hyperspectral data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0037] A method for joint retrieval of forest structure parameters from full-waveform lidar and hyperspectral data, such as figure 1 As shown, the steps are as follows:

[0038] 1) Set up 67 square plots (30×30m 2 ), with the help of aircraft to collect full-waveform lidar data and hyperspectral image data, such as figure 2 shown. The coordinates of the center point of the sample plot were measured using GPS (Trimble GeoXH6000), which positioned by receiving wide-area differential signals, with an accuracy better than 0.5m. And record and count the tree species in the sample plot, and measure the DBH and tree height of each tree at the same time. The stock volume is estimated according to the unitary volume formula combined with the measured diameter at breast height, and the aboveground biomass is calculated through the allometric growth equation combined with diameter at breast height and tree height. According to the single tree survey data, the aboveground biomass was...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a method for jointly inverting forest structure parameters by using a full-waveform lidar and hyperspectral data. Firstly, performing de-noising, smoothing, intensity correction and filtering on airborne full-waveform lidar data, performing interpolation to generate a digital terrain model, and performing high normalization processing on point cloud and waveform data; performing radiation calibration, atmospheric correction and geometric correction preprocessing on a hyperspectral image; then extracting characteristic variables based on normalized point cloud and waveform data and preprocessed hyperspectral data separately; and finally, constructing multivariate regression models combined with ground measured data and the extracted characteristic variables to predict each forest structure parameter. The invention contributes to improving the inversion precision of the forest structure parameters, and effectively suppresses the "saturation" problem of parameter inversion of a stand structure with high forest coverage and high biomass; therefore, the ability and accuracy of forest structure parameter inversion is effectively enhanced; and compared with the stand structure parameter inversion with other similar remote sensing methods, the relative root mean square error is increased by more than 5%.

Description

technical field [0001] The invention belongs to the technical fields of forest resource monitoring and environmental factor investigation, and relates to a method for jointly inverting forest structure parameters with full-waveform laser radar and hyperspectral data. Background technique [0002] Accurate extraction of forest structure parameters is of great significance for forest resource monitoring and environmental factor investigation. At the same time, this information can also be used to grasp the relationship between forest plants and the environment, and to further understand the growth and development of forests, which is of great significance for sustainable forest management, ecological model construction and global carbon cycle research. Conventional forest structure parameter extraction mainly relies on field surveys and interpretation of aerial or satellite images, and its accuracy is often not high, and it is difficult to be practically promoted on the "surfa...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G01S17/89
CPCG01S17/89
Inventor 曹林申鑫云挺刘浩汪贵斌
Owner NANJING FORESTRY UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com