In order to join virtual sessions, you must be registered and logged-in(Were you registered for the in-person meeting in Denver? if yes, just log in.) 
Note: All session times are in Mountain Daylight Time.

Assessing the sustainability of Coupled Natural-Human systems using coupled differential equations

Authors: Kenan Li*, University of Southern California, Nina Lam, Louisiana State University, Heng Cai, Texas A&M University, Lei Zou, Texas A&M University, John Wilson, University of Southern California
Topics: Coupled Human and Natural Systems, Land Use and Land Cover Change, Hazards and Vulnerability
Keywords: Sustainability, Couple Natural-Human Systems, Geographically Weighted Elastic Net, Dynamic-Time-Warping Self-Organizing Map
Session Type: Paper
Presentation File: No File Uploaded

This study examines approaches to deriving coupled ordinary differential equations to quantitatively depict a coupled natural-human (CNH) system and assess its sustainability. We used population as the indicator of the human system and land loss as the indicator of the natural system in the southeastern region of Louisiana, also known as the Lower Mississippi River Basin. We used Geographically Weighted Elastic Net (GWEN) to select the predictors from a large set of socioeconomic, environmental, demographical, and ecological variables, and to derive the coupled ordinary differential equations between population and land loss for the study area which has high vulnerability to coastal hazards. Then, we used the coupled equations to project the future population and land loss as time series. Finally, we used the Dynamic-Time-Warping Self-Organizing Map (DTW-SOM) to cluster the times series and assess the sustainability of the region. This study proposes a framework of using two novel approaches previously developed by our research group (GWEN and DTW-SOM) to study the sustainability of CNH systems in a quantitative way.

Abstract Information

This abstract is already part of a session. View the session here.

To access contact information login