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Matthew Rossi is a geomorphologist who recently joined the Earth Lab team as a Post-Doctoral Research Scholar in the research area of Erosion. He received his B.S. in Geology from the College of William and Mary (2003) and his Ph.D. in Geological Sciences from Arizona State University (2014). He came to CU-Boulder from Northwestern University where he served as a Visiting Assistant Professor in the Program in Environmental Sciences. His research focuses on developing quantitative understanding of the processes and process interactions that control the shape of Earth’s surface and is motivated by a desire to explain how landscapes record and respond to climatic and tectonic forcing. Toward this end, his research at Earth Lab examines the roles of soil production, vegetation dynamics, and hydrometeorology on the pace and pattern of debris flows and flooding. To do this work, he integrates space-borne and air-borne remote sensing with ground-based observations and numerical modeling.

Project Land Surface Change focuses on how water, sediment, and nutrients cycle through natural and managed systems. We use technological innovations in observation (e.g., drones; airborne lidar) and advances in numerical modeling of Earth surface dynamics to understand and predict land surface response to climatic and tectonic forcing.
Damage from natural hazards is increasing despite the growing ability of the geo-sciences to delineate where and when extreme events will occur. We show that decades of risky development has increased exposure to the most damaging natural hazards.
Environmentally, what is extreme? What can we do to mitigate their impacts? Our research aims to answer these questions and brings an interdisciplinary, big-data perspective to risk assessment.
The Climate Coupling project seeks to measure the strength of coupling between climate drivers and social-environmental systems and to explain those measurements as a function of management interventions.
At Earth Lab, we often use data from diverse sources to facilitate inquiry, from the more conventional remote sensing datasets such as multispectral satellite imagery and radar backscatter, airborne lidar data, and high-resolution UAV imagery, to the less traditional datasets such as social media feeds, housing layers, and event databases.
Rossi