Forestry Vehicle Tree Detection for Reliable Diameter Mapping
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Solution Overview
Problem
Existing forestry vehicles face challenges in accurately measuring and analyzing tree diameter and position in forest areas due to manual methods prone to operator variability and interference from foliage, branches, terrain obstacles, and weather conditions, leading to inconsistent thinning results and increased operational time.
Innovation Solution
A forestry vehicle equipped with a tree detection device, such as Lidar, that analyzes point cloud data using a two-step process to detect individual trees, eliminate noise, and validate tree diameter and position data through software filters and standard deviation, displaying final results on an operator display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual measurement methods are used by operators, then flexibility and adaptability to various terrain conditions are maintained, but measurement precision and consistency deteriorate due to operator variability and subjectivity
Solution Approach 1:
The patent replaces manual mechanical measurement methods with an automated optical detection system (camera-based imaging system). The system captures images of trees and uses image processing algorithms to automatically detect tree positions, calculate diameters, and generate basal area measurements, eliminating operator variability while maintaining adaptability to different terrain conditions through automated image analysis.
2Measurement precision
If automated tree detection systems are implemented, then measurement precision and productivity are improved, but device complexity increases due to additional sensors and processing equipment
Solution Approach 1:
The patent integrates multiple functions into a single comprehensive system. The imaging system simultaneously performs tree detection, diameter measurement, position tracking, and basal area calculation. The controller executes multiple processing algorithms (image processing, point cloud analysis, statistical validation) within a unified device, reducing the need for separate specialized equipment while maintaining high measurement precision.
Solution Approach 2:
The system creates a digital replica (point cloud model) of the physical forest environment. By capturing three-dimensional spatial information through imaging and converting it into a virtual point cloud representation, the system enables precise measurements without requiring physical contact with trees, simplifying the interaction between the device and the complex forest environment.
3Reliability
If multiple validation algorithms are applied to ensure data accuracy, then measurement reliability is improved, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary data processing and filtering before final analysis. Raw imaging data is pre-processed to remove obvious noise and artifacts, and preliminary tree candidate detection is performed before applying more computationally intensive validation algorithms. This staged approach ensures data accuracy through multiple validation steps while minimizing total processing time by eliminating redundant computations.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables precise tree detection and diameter measurement with reduced failure rates, distinguishing between foliage and tree trunks, and automates the process, reducing manual effort and enabling data sharing across multiple vehicles.
Implementation Method 1
A forestry vehicle equipped with a tree detection device, such as Lidar, that analyzes point cloud data
Data Source
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AI summary
The invention is a method for measuring and analyzing a forest area for a forestry vehicle, the vehicle comprising a tree detection device, adapted to be mounted to the vehicle and to detect trees in the forest area, a computing device, adapted to receive a point cloud from the tree detection device and to receive GNSS data from the positioning device, the computing device adapted to analyze the point cloud data from the tree detection device by analyzing software, the computing device adapted to eliminate noise from the point cloud data, so that the computing device in a first step analyzes the point cloud data to detect individual trees and assigning object classification to each tree, and in a second step analyzes each channel data in the point cloud data to detect the diameter of the trees, in a further step analyzing the point cloud for each iteration and validation the tree position data and the tree diameter data using a software filter and a standard deviation of the measurement results, and if the filter results and the standard deviation converge to a predetermined value terminating the computing and recording the results as final, displaying the final data of the trees together with the final diameter on a display in the vehicle to an operator.