Statistical Methods for Recovering 3D Models of Trees from Sensor Data

Measuring the biological parameters of trees can be a time consuming process. Currently, there are two main choices: painstakingly count leaves and measure hundreds of branches by hand, or use rough approximations obtained from sensors like hemispherical cameras or airborne laser scans. We hope to find ways of reconstructing models of trees in greater detail, by collecting large amounts of sensor data at relatively close range and fitting a model to this data. Once the model is created, parameters such as branch lengths and approximate leaf areas can be automatically calculated. If we are able to successfully automate data collection and model reconstruction, the process of extracting tree parameters will become considerably easier and more accurate than current methods.