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Ming Xu

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My research focuses on developing and applying computational and data-enabled methodology in the broader area of sustainability. Main thrusts are as follows:

1. Human mobility dynamics. I am interested in mining large-scale real-world travel trajectory data to understand human mobility dynamics. This involves the processing and analyzing travel trajectory data, characterizing individual mobility patterns, and evaluating environmental impacts of transportation systems/technologies (e.g., electric vehicles, ride-sharing) based on individual mobility dynamics.

2. Global supply chains. Increasingly intensified international trade has created a connected global supply chain network. I am interested in understanding the structure of the global supply chain network and economic/environmental performance of nations.

3. Networked infrastructure systems. Many infrastructure systems (e.g., power grid, water supply infrastructure) are networked systems. I am interested in understanding the basic structural features of these systems and how they relate to the system-level properties (e.g., stability, resilience, sustainability).

A network visualization (force-directed graph) of the 2012 US economy using the industry-by-industry Input-Output Table (15 sectors) provided by BEA. Each node represents a sector. The size of the node represents the economic output of the sector. The size and darkness of links represent the value of exchanges of goods/services between sectors. An interactive version and other data visualizations are available at http://complexsustainability.snre.umich.edu/visualization

A network visualization (force-directed graph) of the 2012 US economy using the industry-by-industry Input-Output Table (15 sectors) provided by BEA. Each node represents a sector. The size of the node represents the economic output of the sector. The size and darkness of links represent the value of exchanges of goods/services between sectors. An interactive version and other data visualizations are available at complexsustainability.snre.umich.edu/visualization

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Bill Currie

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Dr. Currie develops ecosystem process models to simulate biogeochemical cycling and plant community ecology in wetlands, forests, mixed-use and human-dominated landscapes.  He models social and ecological interactions that relate to sustainability in the environment and society’s use of natural resources.  He uses statistical modeling, including structural equation modeling, to study landscape-scale patterns in forest fragmentation and tree cover.  He is interested in transdisciplinary research, model ontologies and model linkages across fields.

Percent tree cover, at 1 km resolution, across the US portion of the Great Lakes basin

Percent tree cover, at 1 km resolution, across the US portion of the Great Lakes basin

 

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Daniel Brown

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Research interests focus on land use change and its effects on ecosystems and on human vulnerability. This work connects simulation (e.g., agent-based modeling) of land-use-change processes with GIS and remote sensing based data on historical patterns of landscape change and social surveys. We are also working to understand the ways in which land-use decisions are made and to evaluate consequences of change.