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: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=653304
• 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.

考虑到草地和森林在全球的重要性、对未来干扰增加的预测以及为保护机制提供信息的必要性，探索和发展遥感技术来识别植物胁迫以及描述大地理区域长期胁迫的潜在原因是至关重要的。过去的遥感研究观察到植物对胁迫的光谱变化，但很少努力解释支持进化光谱的光学变化。如果不了解植物光谱差异的原因，预测胁迫对植物生理过程的负面影响是具有挑战性的。扩展我之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，以定量测量植物在不同生命周期阶段的光学特性，并将这些发现导入一个强大的辐射传输建模框架，允许植物胁迫色素的吸收和散射是动态的。具体目标是利用实验室实验、野外数据、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，并监测扰动对植被的影响。本研究将重点关注的干扰事件是：1)横跨安大略省森林的翡翠灰蛀虫侵扰，以及2)加拿大草原预计的干旱。目前还没有开发出类似的系统，为森林和草原提供跨空间和时间的明确信息。因此，拟议的项目将支持近期和长期的研究，以改善森林和草地资源管理，并从根本上提高我们适应和管理干扰事件对加拿大植被生态系统的负面影响的能力。