Global change research requires models developed through careful study of local phenomena that can be extended to landscape, regional, and global scales. Unfortunately, environmental scientists have been limited in their ability to determine how factors that operate at different scales impact landscapes.

   Among the most important challenges in the study of global change is the ability to acquire high-resolution forest attribute data over extended regions. Such data could be used to understand what impact combinations of regional and local influences have on global ecosystems. For example, biodiversity of forests depends on how much sunlight is absorbed by the tree canopies, since sunlight plays an important role in competitive relationships among species. Prediction of future biodiversity depends on tree canopy data that are linked to individual growth performance.

   The Forestry Project is an interdisciplinary collaboration between Duke University's Center on Global Change, the Computer Vision Laboratory at the University of Massachusetts, Amherst, and the GeoProcessing Laboratory at Mount Holyoke College. The long-term of the research project is aimed to enhance the ability of biology and geoscience research programs to acquire, analyze, and distribute high-resolution GIS databases of important environmental attributes with regional coverage. The principal problem is to develop new techniques to extract forest attributes in the form of GIS databases from remotely sensed data collected by low cost instruments.

The computer science research will focus on building an aerial data acquisition system for collecting high quality, high-resolution digital images and other remote sensing data, and a suite of analysis tools for creating GIS databases of environmental attributes with sub-meter geo-registration and elevation accuracies.