Statistics Colloquium: Connecting the dots: a statistical framework for land change science using dense satellite time series

Presented by: Zhe Zhu, Associate Professor of Remote Sensing, Department of Natural Resources & the Environment, University of Connecticut

Date: Friday, September 5, 2025, 10:00 AM, AUST 247

Meeting Link: Link

Coffee will be available at 9:30 in the Noether Lounge (AUST 326)

Abstract:

Remote sensing data are noisy, which makes land change detection challenging, particularly for changes that are subtle, gradual, or transient. By connecting the dense time series observation “dots”, we can better model the land surface characteristics, and therefore, detect and attribute land changes that are usually “invisible” in multitemporal satellite images. Moreover, the use of dense time series satellite observations and time series modeling creates new change products that if well-connected can provide a multifaceted view of land change. Finally, I will use the derived multifaceted land change products as the dots and connect them to demystify the changing land disturbance regimes, diminishing coastal tidal wetlands, and shifting human activity at continental and global scales.