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.
