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EDS Seminar: Imaging Forest Function and Biodiversity with Hyperspectral Remote Sensing
Abstract
Imaging spectroscopy provides a powerful way to observe vegetation beyond canopy greenness, revealing variation in plant chemistry, functional traits, and species identity across landscapes. In this seminar, I will show how data from the National Ecological Observatory Network's Airborne Observation Platform (NEON AOP) can be used to connect these spectral measurements to forest function and biodiversity across ecosystems. First, I will examine how hyperspectral estimates of canopy nutrient composition help explain variation in autumn phenology across NEON forest sites. By linking airborne spectroscopy with phenological observations, we find that variation in foliar nutrient balance is associated with the timing of canopy senescence, providing a functional perspective on phenological variation beyond climate alone. I will then turn from plant function to species identity and show how NEON AOP hyperspectral imagery, combined with deep learning, can be used to classify tree species across heterogeneous forest landscapes. Together, these studies demonstrate how a standardized, continental-scale airborne observing system can support ecological questions ranging from plant function to biodiversity. I will conclude by discussing opportunities to integrate NEON AOP with satellite observations and emerging deep learning approaches to scale ecological inference from individual trees and canopies to regions and continents.
Speaker Bio
Tong Qiu is an Assistant Professor of Ecology at the Nicholas School of the Environment at Duke University. His research examines how climate, habitat, and biodiversity interact across spatial and temporal scales in forest, savanna, and urban ecosystems. His group combines advanced remote sensing, including LiDAR and imaging spectroscopy, with statistical and deep learning approaches to connect fine-scale ecological processes with landscape- to continental-scale observations and to better understand and predict ecosystem responses to environmental change.
This talk will not be recorded, so be sure to join us!