Landsat and Shuttle Radar Topography Mission (SRTM) imagery have recently been used to identify broad-scale floristic units in Neotropical rain forests, corresponding to geological formations and their edaphic properties. Little is known about the structural and functional variation between these floristic units, however, and Landsat and SRTM data lack the spectral and spatial resolution needed to provide this information. Imaging spectroscopy and LiDAR (Light Detection and Ranging) have been used to measure canopy structure and function in a variety of ecosystems, but the ability of these technologies to measure differences between compositionally-distinct but otherwise uniform tropical forest types remains unknown. We combined 16 tree inventories from central Panama with imaging spectroscopy and LiDAR elevation data from the Carnegie Airborne Observatory to test our ability to identify patterns in plant species composition, and to measure the spectral and structural differences between adjacent closed-canopy tropical forest types. We found that variations in spectroscopic imagery and LiDAR data were strong predictors of spatial turnover in plant species composition. We also found that these compositional, chemical, and structural patterns corresponded to underlying geological formations and their geomorphological properties. We conclude that imaging spectroscopy and LiDAR data can be used to interpret patterns identified in lower resolution sensors, to provide new information on forest function and structure, and to identify underlying determinants of these patterns.
