职位(财务)
公制(单位)
树(集合论)
计算机科学
k-最近邻算法
模式识别(心理学)
人工智能
探测器
数学
统计
工程类
数学分析
电信
运营管理
财务
经济
作者
Kenneth Olofsson,Johan Holmgren
出处
期刊:Silva Fennica
[Finnish Society of Forest Science]
日期:2022-01-01
卷期号:56 (3)
被引量:3
摘要
A new method for the co-registration of single tree data in forest stands and forest plots applicable to static as well as dynamic data capture is presented. This method consists of a stem diameter weighted linking algorithm that improves the linking accuracy when operating on diverse diameter stands with stem position errors in the single tree detectors. A co-registration quality metric threshold, QT, is also introduced which makes it possible to discriminate between correct and incorrect stem map co-registrations with high probability (>99%). These two features are combined to a simultaneous location and mapping-based co-registration method that operates with high linking accuracy and that can handle sensors with drifting errors and signal bias. A test with simulated data shows that the method has an 89.35% detection rate. The statistics of different settings in a simulation study are presented, where the effect of stem density and position errors were investigated. A test case with real sensor data from a forest stand shows that the average nearest neighbor distances decreased from 1.90 m to 0.51 m, which indicates the feasibility of this method.
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