Dr. Arika Ligmann-Zielinska

Arika  Ligmann-Zielinska
  • Associate Professor
  • Geography, Environment, and Spatial Sciences
  • Geography Building
  • 673 Auditorium Road, Room 121
  • East Lansing, MI 48824
  • 517-432-4749


Spatial analysis and coupled human-environment modeling. Agent-based models.


Arika Ligmann-Zielinska got her doctoral degree from a Joint Doctoral Program in Geography at San Diego State University and University of California Santa Barbara in 2008. Her doctoral specialty was spatial decision support, spatial analysis and modeling and her dissertation focused on “Exploring Normative Scenarios of Land-Use Development Decisions with an Agent-Based Simulation Laboratory” completed under the supervision of Professor Piotr Jankowski, Ph.D. Prior to that, she studied environmental geography in her home country Poland. She obtained her undergraduate and graduate MS degree (summa cum laude) from the Department of Geography and Geology, Adam Mickiewicz University, Poznan, Poland.


Arika’s research encompasses a broad range of modeling approaches that capture the dynamic relationships within coupled human and natural systems. Specifically, she uses agent-based models as computational laboratories allowing for exploration and scenario building of complex system characteristics such as the interrelationships between societies and their landscapes, the dependence of system trajectories on human decisions made in the past, and the acknowledgment of human decision making heterogeneity. To-date her core research has focused on spatiotemporal sensitivity analysis of model output for spatial decision support. While random events like earthquakes and tornadoes are unavoidable, we can still address large portions of uncertainty in modeling geographic processes by providing tools to explore the temporal and spatial dynamics of human-natural interactions. She utilizes a sensitivity analysis method that breaks down the variability of model output like alternative land development maps and distributing it among the uncertain model inputs like land characteristics, human behavior, and preferences for specific sites. This method allows for a thorough inspection of behavioral and environmental uncertainties related to the linkages among individual choices, landscape changes, and the emerging land development patterns.