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

植被通过控制地球和大气之间的水和二氧化碳交换，在塑造我们的气候和天气方面发挥着重要作用。不幸的是，没有办法在大陆尺度上直接测量这些过程，这限制了我们预测未来气候甚至短期天气的能力。美国收集的地球观测卫星几乎每天都能提供全球生物圈的完整视图，但这些图像非常粗糙，很难解释。该研究人员的实验室已经开发出一种技术，利用树木投射的阴影，从粗略的卫星图像中推断树木的大小和数量。这个概念是大树和茂密的森林投下更大的阴影，这可以使森林看起来更暗。该算法，即用于解释卫星数据的定义良好的指令列表，主要取决于典型森林林分的树冠大小和树木密度之间的关系。美国林务局已经为美国大陆的森林按物种收集了一个非凡的树木结构（大小和形状）数据集，但缺乏世界其他地区的数据，特别是热带地区。夏威夷的这项研究将使用最先进的机载系统激光系统来测量树冠，从而极大地扩展我们对热带地区森林结构的了解。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，以改进天气和气候预报，并监测森林生物量的大规模变化。这项研究将促进与其他研究该主题的小组的合作。

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.