twin*
telluride wetlands inventory
telluride wetlands inventory
The TWIN* team investigates the impact of climate change on sensitive high-altitude wetlands--known as fens--through the innovative use of artificial intelligence (AI), drone technology (UAS), and high-speed computer clusters (supercomputers).
The team gratefully acknowledges the support of Arizona State University's HIRBI (Herberger Institute Research Building Investment) Seed Grant Program, ASU's Research Office, and the Telluride Institute.
Buckbean Fen. Image courtesy Evan Iverson.
*While the satellite and ground-based data utilized in this project are not "real time," our goal is to produce a data processing pipeline that rapidly processes "near real-time" data--especially from regularly scheduled data uploads from satellite based sensors. In this sense, the idea of a "digital twin" for planet earth is fast approaching reality. The acronymn"TWIN" is an allusion to this idea. Here is a working definition of the concept of a "digital twin":
A digital twin is a dynamic, virtual copy of a physical object, system, or process, using real-time data from sensors (IoT) to mirror its real-world counterpart's behavior, performance, and conditions throughout its lifecycle, enabling simulation, analysis, and better decision-making without touching the physical asset. It's a "living" model that evolves with live data, unlike static simulations, allowing for "what-if" scenarios, predictive maintenance, and optimized operations. --AI generated definition