My interests are in the area of remote sensing, particularly remote sensing of forests and natural vegetation. Working in this area has led to a variety of research. On the theory end, I have been interested in the interaction of light with plant canopies, and models of that process, and how they can be used to recover the properties of vegetation canopies from remote measurements. Similarly, the spatial organization of landscapes, and the resulting spatial properties of images is a primary interest. From a more practical perspective I am interested in monitoring environmental change, both in terms of human impacts on environments and in terms of succession and climate change. In terms of methodology, I maintain active interests in both geographic information systems and digital image processing.
Landsat Science Team: As a member of NASA's Landsat Science Team I am developing methods to monitor change in temperate conifer forests using data from the Landsat 7 satellite. The intent is to be able to provide annual estimates of change in the area covered by conifer forests at the continental scale.
NASA Land-Use and Land-Cover Change Program: For this program, I am part of a team working on the socio-economic drivers of land-use change in Southern China. My role is primarily to provide estimates of rates of land-use change (primarily forest and agriculture converted to developed land) for different townships over the past 25 years from historical satellite images.
Snowmelt Modeling in Forested Landscapes: For this project, I work on providing the radiation inputs to snowpacks below forest canopies to improve models of snowmelt. A key component of this research concerns how to parameterize our radiation models over entire landscapes and to model snowmelt for entire drainage basins.
Neural Networks and Land-Cover Change: For this project, I am working on developing advanced tools for detecting land-cover change in satellite images based on artificial neural networks.
