REMOTE SENSING OF BIOPHYSICAL VARIABLES AT MULTIPLE SPATIAL SCALES ALONG A LATITUDINAL GRADIENT IN THE CANADIAN ARCTIC

加拿大北极沿纬度梯度多空间尺度生物物理变量的遥感

• 批准号: RGPIN-2014-03822
• 负责人: Treitz, Paul
• 金额: $ 2.7万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=566109
• 关键词: REMOTE; SENSING; BIOPHYSICAL; VARIABLES; MULTIPLE

Tundra ecosystems account for a large proportion of Canada’s land surface and are important systems within the context of environmental change research. Tundra ecosystems are thought to be particularly sensitive to changes in climate, yet it remains unclear as to how they will respond. Changes in tundra ecosystem patterns and processes will be expressed through shifts in vegetation phenology and species composition and abundance. In addition to the obvious impacts of increasing air temperatures, there are a number of factors that serve as controls on vegetation growth in the Canadian Arctic, including soil moisture, nutrient availability, soil type and topography/micro-topography, some of which are also impacted by warming temperatures. Hence, high spatial resolution remote sensing provides an opportunity to estimate and monitor vegetation variability, with the potential to quantify biophysical variables that control carbon fluxes over large areas. However, detailed in situ studies are required for calibration and validation of appropriate remote sensing models to estimate these variables. The focus of my NSERC Discovery Grant will be on modeling biophysical variables at multiple scales along a latitudinal gradient (~64°-75°N) for the Canadian Arctic; providing a mean-July temperature gradient of approximately 10°C. This research will be conducted at Sabine Peninsula (77ºN) and Cape Bounty (75ºN), Melville Island; Boothia Peninsula (71ºN); and Apex River, Baffin Island (64ºN), Nunavut. Although there have been studies examining biophysical variables at these latitudes, they have largely been limited to broad spatial scales (i.e., 1-8 km2) with limited field support. There has been very little research conducted in Canada's North on relating biophysical variables to high spatial resolution remote sensing data (<10 m); nor how these variables are linked to ecosystem processes (e.g., carbon flux/net ecosystem exchange). My research will: (i) quantify the relationships between biophysical variables and spectral reflectance at high spatial resolutions; (ii) model the relationships between biophysical variables and ecosystem processes; and (iii) model biophysical variables, including carbon exchange, at multiple scales in order to project changes in these variables over space and time. Variables of significance for productivity modeling and estimating net ecosystem exchange include above-ground phytomass, percent vegetation cover and fraction of absorbed photosynthetically active radiation. These are critical structural and physiological variables linked to many ecosystem processes (e.g., phytomass plays a significant role in assessing carbon stocks, is an important element in global change and productivity models, and is a measure of vegetation community structure which influences biodiversity). These variables will be measured using direct measurement and photo-plot techniques employing near-infrared photography and spectral indices. In order to scale up variables, models will be developed between field measurements and photo-plot data for comparison to high (WorldView-2), intermediate (Landsat 8) and coarse (MODIS) resolution remote sensing data. With the results of this research, i.e., modeling of biophysical variables and ecosystem processes at multiple scales, we will be able to make knowledgeable policy decisions related to development in the North. In addition, this research will help us develop adaptation strategies for communities and resource industries living and operating in Canada’s North. Finally, training of undergraduate and graduate students will contribute to the next generation of Arctic scientists, specifically earth and environmental scientists trained in arctic field methods and remote sensing image processing.

苔原生态系统占加拿大土地表面的很大一部分，并且是环境变化研究中的重要系统。苔原生态系统被认为对气候变化特别敏感，但尚不清楚它们将如何反应。苔原生态系统模式和过程的变化将通过植被物候和物种组成和抽象的转移来表达。除了升高空气温度的明显影响外，还有许多因素可以控制加拿大北极的植被生长，包括土壤水分，养分可利用性，土壤类型和地形/微型摄影，其中一些也受到变暖的频率的影响。因此，高空间分辨率的遥远灵敏度为估计和监测植被变异性提供了机会，并有可能量化在大面积上控制碳通量的生物物理变量。但是，需要详细的原位研究来校准和验证适当的遥感模型以估计这些变量。我的NSERC发现赠款的重点将是为加拿大北极的纬度梯度（〜64°-75°N）的多个尺度上的生物物理变量建模；提供约10°C的平均温度梯度。这项研究将在梅尔维尔岛（Melville Island）的萨宾半岛（77°N）和Cape Bounty（75°N）进行。 Boothia Peninsula（71ºN）;努纳武特（Nunavut）的巴芬岛（Baffin Island）（64ºN）的Apex River。尽管已经有研究在这些纬度上检查生物物理变量，但它们在很大程度上仅限于广泛的空间尺度（即1-8 km2），并且野外支持有限。在加拿大北部，关于将生物物理变量与高空间分辨率遥感数据（<10 m）联系起来的研究很少。这些变量如何链接到生态系统过程（例如碳通量/净生态系统交换）。我的研究将：（i）量化在高空间分辨率下生物物理变量与光谱反射率之间的关系； （ii）建模生物物理变量与生态系统过程之间的关系； （iii）在多个尺度上建模生物物理变量，包括碳交换，以便在时空上投射这些变量的变化。生产力建模和估算净生态系统交换的重要性变量包括地上植物量，蔬菜百分比覆盖和吸收的光合作用活性辐射的比例。这些是与许多生态系统过程相关的关键结构和生理变量（例如，植物量在评估碳量中起重要作用，是全球变化和生产力模型中的重要因素，并且是对影响生物多样性的蔬菜社区结构的测量）。这些变量将使用近红外摄影和光谱指数的直接测量和光图技术进行测量。为了扩展变量，将在现场测量和照片图数据之间开发模型，以与高（WorldView-2），中级（Landsat 8）和粗（MODIS）分辨率远程灵敏度数据进行比较。根据这项研究的结果，即，在多个尺度上对生物物理变量和生态系统过程进行建模，我们将能够做出与北方发展有关的知识渊博的政策决策。此外，这项研究将有助于我们为在加拿大北部生活和运营的社区和资源行业制定适应策略。最后，对本科生和研究生的培训将为下一代北极科学家做出贡献，特别是接受北极现场方法和遥感图像处理培训的地球和环境科学家。