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云南松树松木线虫病的早期特征研究基于对地面物体的超光谱遥感

Xiao Zhang¹, Yingqun Gao², Lianjin Fu¹

¹College of Soil and Water Conservation, Southwest Forestry University, Kunming, 650224, China.

Scientific reports

|July 21, 2025

概括

在松树中早期发现松病 (PWD) 对森林管理至关重要. 这项研究使用高光谱数据来识别早期的光谱和生化变化,使得PWD的确切诊断和控制.

科学领域:

森林病理学和遥感.
植物生理学和生物化学.
数据科学和机器学习用于生态监测.

背景情况:

松病 (PWD) 导致松树快速死亡,需要早期检测才能有效管理.
目前的林业政策要求迅速识别受感染的树木,以防止广泛的流行病.
及时诊断对于控制PWD传播和保护森林生态系统至关重要.

研究的目的:

开发一种用于早期检测松病 (PWD) 的新方法,使用高光谱数据和生理参数.
确定最佳的光谱范围和生物化学指标,以诊断PWD在最初的阶段.
建立一个区域范围的PWD超谱监测的基础.

主要方法:

获取高光谱数据 (350-2500nm) 和松树叶的生物化学分析.
研究早期PWD的光谱特征和生化变化 (总糖,减糖,水分含量).
应用特征选择算法 (CARS,SPA) 来识别关键光谱带和机器学习 (XGBoost) 来进行分类.

主要成果:

在PWD感染早期观察到总糖,减少糖和水分含量的显著下降.
最佳的光谱诊断窗口被确定为455-677nm和1974-2340nm.
在XGBoost分类器实现了高准确度 (91%与CARS,83%与SPA) 在区分健康和受感染的树木,与AUC>0.8.8.

结论:

超光谱数据与生化分析相结合,为早期PWD检测提供了一种可靠的方法.
识别的光谱波段和生物化学标记器为PWD提供了精确的诊断能力.
这种叶片尺度的方法支持区域范围的空中和卫星超光谱监测系统的开发,用于PWD管理.

关键词:

松树 (Pinus yunnanensis) 是一个古老的植物.森林健康监测森林健康监测超光谱数据是指高光谱数据.松病是松的疾病.

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