Deriving forest structure indices for assessing large-scale vegetation community condition using satellite imagery.

Student: Brittany Burnett

Faculty Mentor: Lisa Bentley

Biology

College of Science, Technology, and Business

The state of large-scale imaging technologies like satellite imagery and LiDAR has vastly expanded the field of remote sensing, or the ability to monitor change at the landscape level using spectral identifiers. One current limitation of this relatively new technology is a gap in analytical metrics that can be used to quickly and reliably identify vegetation threats through structural changes. Using publicly available satellite imagery from Sonoma and Marin counties, we will assess whether structural vegetation change and its abiotic drivers (disease, disturbance, etc.) can be determined using a suite of spectral identifiers. The ability to distinguish large-scale vegetation change is a growing application of this technology and has the potential to quickly and accurately triage sites for landscape restoration, wildfire mitigation, and climate change monitoring.