Scaling of inter- and intra-annual variation in foliar traits derived from imaging spectroscopy

A common assumption in remote sensing is that a constituent map made from imagery in one year is representative of constituents in subsequent years. This assumption has been partially supported using ground collected data, but it has never been formally tested using multiple images. The purpose of this project is to determine whether maps of foliar traits, as determined through imaging spectroscopy, scale inter- and intra-annually, and to determine the conditions under which these traits do not scale. We will create trait maps collected over Madison, WI using existing imagery from multiple years collected at multiple time points within each year. We will then examine pixel by pixel variation in the traits derived from the multiple images to test the assumption that traits scale across and within years.

Lab Members:  Ryan Sword, Aditya Singh