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A Rapid Laser Probing Method Facilitates the Non-invasive and Contact-free Determination of Leaf Thermal Properties

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一种基于激光模块和深度学习的茎直径测量的自动化方法.

Sheng Wang^1,2, Rao Li^1,2, Huan Li^1,2

¹School of Information Science and Technology, Beijing Forestry University, Beijing, 100083, China.

|July 5, 2023

概括

本研究介绍了一种用于测量树干直径 (SD) 的自动设备,为传统方法提供了高效和准确的替代方案. 这种新的方法可以确保在各种环境中精确地收集森林库存数据.

关键词:

深度学习是一种深度学习.森林库存森林库存森林库存图像传感器是一个图像传感器.激光模块激光模块激光模块测量方法测量方法

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科学领域:

林业科学林业科学
遥感技术遥感技术遥感技术
生态监测生态监测

背景情况:

传统的树干直径 (SD) 测量对于森林管理至关重要,但是劳动密集型和昂贵.
现有的方法需要专家人员,导致时间延迟和费用增加.
需要自动化,高效和准确的SD测量技术.

研究的目的:

开发和验证一种用于自动测量茎直径的新型装置和方法.
为森林资源管理提供具有成本效益和便携性的解决方案.
提高自然环境中SD数据收集的效率和准确性.

主要方法:

一个集成图像传感器和激光模块的设备被开发用于自动SD测量.
一个激光模块在树干上投射了一个参考点进行校准.
一个端到端的模型从图像中确定了车身轮,根据轮和点直径计算SD.

主要成果:

该方法在各种场景 (过渡性林地/灌木,混合森林,城市地区) 中与实地带测量具有很高的一致性.
获得了0.36厘米的绝对平均误差和0.45厘米的根平均平方误差,SD值从2.00厘米到89.00厘米不等.
集成设备成本低,便携,多功能,并且比许多现有方法更准确.

结论:

开发的方法允许在自然环境中自动,高效和准确的茎直径测量.
未来的工作包括将该设备集成到自主移动机器人中,以扩展应用.
这项技术有可能彻底改变森林库存和管理实践.