Quantifying Vegetation Stress from the Leaf to Landscape Scale: Integrating Lab/Field Observations, Radiative Transfer Modelling, and UAV Hyperspectral Imaging System

量化从叶子到景观尺度的植被压力：集成实验室/现场观测、辐射传递模型和无人机高光谱成像系统

• 批准号: RGPIN-2016-05614
• 负责人: He, Yuhong
• 金额: $ 2.11万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=633670
• 关键词: Quantifying; Vegetation; Stress; Leaf; Landscape

Given the global importance of grasslands and forests, the projections of increased future disturbances, and the need to inform conservation mechanisms, it is vital to explore and develop remote sensing techniques to identify plant stress as well as characterize the underlying causes of stress in large geographical areas over time. Past remote sensing studies observed spectral changes in plants in response to stress, but made little effort to explain optical changes underpinning the evolved spectra. Without an understanding of why plant spectra differ, it is challenging to predict the negative impacts of stress on the physiological processes within the plant. Expanding my previous work in vegetation remote sensing, I propose an interdisciplinary 5-year program to quantitatively measure plant optical properties at various lifecycle stages and to import these findings into a robust radiative transfer modelling framework that permits absorbance and scattering of plant stress pigments to be dynamic. The specific goal is to use lab experiments, field data, UAV-based hyperspectral images, and radiative transfer models to identify early stress, and monitor the effects of disturbance on vegetation across time. The disturbance events this study will focus on are 1) the Emerald Ash borer infestation across Ontario forests, and 2) the projected drought over Canadian grasslands. No similar system, providing explicit information across space and time for forests and grasslands, has been developed. As a result, the proposed program will support both immediate and long-term research that will improve forest and grassland resource management and fundamentally increase our ability to adapt to, and manage, the negative impacts of disturbance events on Canadian vegetative ecosystems.

鉴于草原和森林的全球重要性，对未来干扰增加的预测，以及为保护机制提供信息的需要，探索和开发遥感技术以确定植物胁迫以及确定随着时间的推移大片地理区域胁迫的根本原因至关重要。过去的遥感研究观察到植物在胁迫下的光谱变化，但几乎没有努力解释支撑进化光谱的光学变化。如果不了解植物光谱为什么不同，就很难预测胁迫对植物内部生理过程的负面影响。扩展我以前在植被遥感方面的工作，我提出了一个跨学科的5年计划，在不同的生命周期阶段定量测量植物的光学特性，并将这些发现引入到一个强大的辐射传输模型框架中，该框架允许植物胁迫色素的吸收和散射是动态的。具体目标是使用实验室实验、现场数据、基于无人机的高光谱图像和辐射传输模型来识别早期应力，并监测随时间推移干扰对植被的影响。本研究将关注的干扰事件有：1)安大略省森林中的翡翠白蜡虫成灾；2)加拿大草原上预计的干旱。还没有开发出类似的系统，为森林和草原提供跨空间和跨时间的明确信息。因此，拟议的计划将支持当前和长期的研究，这些研究将改善森林和草原资源管理，并从根本上提高我们适应和管理干扰事件对加拿大营养生态系统的负面影响的能力。