Remote Sensing of Forest Carbon Accumulation

森林碳积累遥感

基本信息

批准号：
RGPIN-2018-03851
负责人：
Coops, Nicholas
金额：
$ 13.7万
依托单位：
University of British Columbia
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
起止时间：
2022-01-01 至 2023-12-31
项目状态：
已结题

来源：
https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=753572
关键词：
Remote Sensing Forest Carbon Accumulation

项目摘要

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.

目的：我研究的总体目标是加深我们对植被色素、生物化学和林分结构之间相互作用的理解，以及如何利用遥感技术来估计森林植被在一定空间和时间尺度上的特性。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，我的小组的研究为增加认识到高光谱分辨率数据可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应力中最受限制的一个决定的。我们使用光化学反射指数 (PRI) 等光谱指数来量化这些变化。我最近的主要贡献集中在 (i) 对从不同植被物种和林分结构获取的叶片光谱数据进行建模，(ii) AMSPEC III（一种内部自动光谱辐射计系统）的部署，以及 (iii)提高人们对森林结构（影响树冠间和树冠内阴影）对林分整体光照状况及其对 LUE 垂直分层的影响的认识。研究问题：我的提案中的关键假设将集中于 LUE / PRI 关系的短期和长期时间变化。在短期内，冠层遮荫对植物光合作用效率的作用，从长远来看，其他色素和其他叶子过程对植被胁迫的作用。定义了三个研究目标：自从对 PRI 和 LUE 进行初步研究以来，我们知道 PRI 在精细时间尺度上对叶黄素循环的变化做出响应，主要由冠层中的光照状况驱动。在每周到季节的时间尺度上，其他植物色素的变化更慢。我的第一个目标分别关注叶黄素循环和季节性变化的色素池循环引起的这些短期和长期变化。其次，由于我们对由于下层阳光衰减而导致的冠层内碳同化的垂直分布知之甚少，因此我们将使用光探测和测距数据、森林建筑模型以及冠层传感器来测量和模拟与上述树冠响应相关的垂直光照状况。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。我的最终目标是检查是否可以修改现有的森林生理模型以纳入来自多个来源的 LUE 动态估计，或者是否需要新的模型结构。