DISSERTATION RESEARCH: The shadows cast by trees: using allometry, tree-resolving lidar, and ecostem models to inform the global view of forests

论文研究：树木投射的阴影：使用异速生长、树木解析激光雷达和生态系统模型来了解森林的全球视野

• 批准号: 0910275
• 负责人: Joseph Berry
• 金额: $ 1.48万
• 依托单位: Carnegie Institution of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-06-01 至 2011-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0910275&HistoricalAwards=false
• 关键词: DISSERTATION; RESEARCH; shadows; cast; trees

Vegetation plays an important role in shaping our climate and weather, by controlling the exchange of water and CO2 between the Earth and its atmosphere. Unfortunately, there is no way to measure these processes directly at continental scales, which limits our ability to predict future climate and even short-term weather. The United States' collection of Earth-observing satellites gives a nearly complete view of the global biosphere every day, but this picture is so coarse that it can be difficult to interpret. A technique has been developed in this researcher's laboratory to infer the sizes and numbers of trees in coarse satellite imagery, using the shadows cast by trees. The concept is that bigger trees and denser forests cast larger shadows, which can make a forest appear darker. The algorithm, i.e. list of well-defined instructions for interpreting the satellite data, depends critically on the relationship between crown size and tree density for typical forest stands. The U.S. Forest Service has amassed an extraordinary dataset of tree architecture (size and shape) by species for forests in the continental U.S., but data are lacking for other parts of the world, especially tropical regions. This research in Hawaii will use a state-of-the art airborne system laser system to measure tree crowns, and thereby dramatically expand our understanding of forest structure in tropical regions. The results of this study will allow better interpretation of daily coarse-resolution satellite imagery for improved weather and climate forecasting, and for monitoring large-scale changes in forest biomass. This research will foster collaboration with other groups working on this topic.

植被通过控制地球与其大气之间的水和二氧化碳的交换，在塑造我们的气候和天气中起着重要作用。不幸的是，没有办法直接在大陆尺度上衡量这些过程，这限制了我们预测未来气候甚至短期天气的能力。美国每天都对全球生物圈几乎完整地观察了美国的地球观察卫星的收藏，但是这幅画是如此粗糙，以至于难以解释。该研究人员的实验室已经开发了一种技术，可以使用树木铸造的阴影来推断粗卫星图像中的树木和数量。这个概念是，较大的树木和茂密的森林会散发出更大的阴影，这会使森林看起来更黑。该算法，即解释卫星数据的定义明确指令列表，主要取决于典型森林支架的冠状大小和树密度之间的关系。美国森林服务局在美国大陆的森林中积累了一个非凡的树木建筑（尺寸和形状）数据集，但世界其他地区（尤其是热带地区）缺乏数据。这项在夏威夷的研究将使用最先进的机载系统激光系统来测量树冠，从而大大扩展我们对热带地区森林结构的理解。这项研究的结果将允许更好地解释每日的粗分辨率卫星图像，以改善天气和气候预测，并监测森林生物量的大规模变化。这项研究将促进与此主题工作的其他小组的合作。