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Remote Sensing of Forest Carbon Accumulation

Remote Sensing of Forest Carbon Accumulation
森林碳积累遥感
批准号:
RGPIN-2018-03851
负责人:
Coops, Nicholas
金额:
$13.7万
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

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中文摘要
翻译
目的:我的研究的总体目标是增加我们对植被色素,生物化学和森林林分结构之间的相互作用的理解,以及如何利用遥感技术来估计森林植被在一系列空间和时间尺度上的属性。我的研究为气候变化下的陆地碳建模和物种分布预测提供了信息,并通过使用先进的遥感技术,为可持续森林管理和制定保护优先事项做出了贡献。背景:在过去的6年里,我的团队的研究有助于提高人们的认识,即高光谱分辨率数据可以用于为森林生产力模型提供信息。 这种方法的关键是估计光利用效率(LUE),这是由限制光化学反应过程的许多环境压力中最有限的。我们使用光谱指数,如光化学反射指数(PRI)量化这些变化。我最近的主要贡献集中在(i)从不同的植被物种和林分结构中获取的叶光谱数据建模,(ii)部署AMSPEC III,一个内部的,自动光谱辐射计系统和㈢提高对森林结构作用的认识(影响树冠内和树冠间的遮荫)对林分的总体光照状况及其对LUE垂直分层的影响起作用。研究问题:我的建议中的关键假设将集中在LUE / PRI关系的短期和长期时间变化上。在短期内,冠层遮光对植物光合效率的作用,以及在更长的时间内,其他色素和其他叶片过程对植被胁迫的作用。三个研究目标的定义:由于初步研究的PRI和LUE,我们知道,PRI是响应于叶黄素循环的变化,在精细的时间尺度,主要是由冠层中的光制度。在每周到季节的时间尺度上,其他植物色素的变化较慢。我的第一个目标是分别关注由于叶黄素循环和季节性变化的色素库循环而引起的这些短期和长期变化。 其次,由于我们对下层阳光衰减导致的冠层内碳同化的垂直分布了解不多,我们将使用光探测和测距数据,森林结构模型和冠层传感器,测量和模拟与上述冠层响应相关的垂直光机制。最后,除了通过PRI了解光合作用之外,由于即将到来的卫星任务,还存在其他方法。我的最后一个目标是研究现有的森林生理模型是否可以修改,以纳入动态估计的LUE从一些来源,或者如果需要新的模型结构。
英文摘要
Objective: The overall aims of my research are to increase our understanding of the interaction between vegetation pigments, biochemistry and forest stand structure and how remote sensing technologies can be used to estimate properties of forest vegetation at a range of spatial and temporal scales. My research informs terrestrial carbon modelling and species distributions prediction under a changing climate, and through the use of advanced remote sensing technologies, contributes to sustainable forest management and developing conservation priorities.Context: Over the past 6 years my group's research has contributed to an increased awareness that high spectral resolution data can be used to inform models of forest productivity. Key to this approach is estimating light-use efficiency (LUE), which is determined by the most limiting of a number of environmental stresses restraining the photochemical reaction process. We quantify these changes using spectral indices such as the Photochemical Reflectance Index (PRI). My recent key contributions have focused on (i) modeling leaf spectral data acquired from a diverse set of vegetation species and stand structures, (ii) deployment of the AMSPEC III, an in-house, automatic spectra-radiometer system and (iii) an increased awareness of the role forest structure (which influences both inter and intra crown shading) plays on the overall light regime of the forest stand and its impact on the vertical stratification of LUE. Research Questions: Key hypothesis in my proposal will focus on the short and long term temporal variations in the LUE / PRI relationship. In the short term, the role of canopy shading on plant photosynthetic efficiency and over the longer term, the role of other pigments and other leaf processes on vegetation stress. Three research objectives are defined: Since initial research on PRI and LUE we know that PRI is responsive to changes in the xanthophyll cycle at fine time scales, principally driven by the light regime in the canopy. Over weekly to seasonal time scales other vegetation pigments change more slowly. My first objective focuses on these short and long term changes due to the xanthophyll cycle, and seasonally changing pigment pool cycles, respectively. Second, as we have a poor understanding on the vertical distribution of carbon assimilation within a canopy that results from attenuation of sunlight in the lower strata, we will use Light Detection and Ranging data, forest architecture models, and within canopy sensors, to measure and model vertical light regimes linked to the above canopy response. Finally, in addition to understanding photosynthesis through PRI, other approaches exist due to upcoming satellite missions. My final objective is to examine if existing forest physiological models can be modified to incorporate dynamic estimates of LUE from a number of sources or if new model structures are required.
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Remote Sensing
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  • 批准号:
    RGPIN-2018-03851
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
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