Environmental Migration

Fleeing from climatic disasters

Human-Environment Hotspots

Conflicting zones between human activities & natural environments

Food Security

Providing culturally appropriate, healthy, & abundant food for every human being

Population & Built Environment/Infrastructure

Developing population-driven solutions to enhance resilience for critical interdependent infrastructures

Methodology

Using nontraditional data & innovative methods for studying socio-environmental systems

5
Continents being analyzed
10+
Long-term, active projects
200+
Publications

The Environmental Demography Network (EDeN) is a research group dedicated to understanding the complex interactions between humans and their environments. EDeN is founded and led by Dr. Guangqing Chi from The Pennsylvania State University.

The human system includes social, economic, political, and behavioral components; the environment is built, biological, geophysical, and chemical; and the interactions include dynamics, processes, and feedbacks.  

Our mission is to develop solutions—social, economic, institutional, infrastructural, ecological—to help all actors reduce their carbon emissions AND help a diverse range of populations become more resilient to environmental changes. Our EDeN team also develops and applies innovative spatial, qualitative, and big data methods to traditional and non-traditional data. 

Our People

Pursuing Opportunities for Long-term Arctic Resilience for Infrastructure and Society

This transdisciplinary project serves as a platform to integrate three convergent research pillars—human-environment hotspots, food security, and migration—with education, local community engagement and outreach, international comparison and collaboration, and external evaluation, in order to create resilient Arctic communities in the face of a changing environment.

POLARIS Project

Building a cyberinfrastructure to integrate and analyze big contextual and social media data and to generalize for social science research

Based on 60+ terabytes tweets, this project evaluates the (mis)representativeness of Twitter data and develops weights to generalize the data, which will create opportunities for social scientists to take advantage of the rich social media data.

Twitter Project

Spatial Regression Models for the Social Sciences provides comprehensive coverage of spatial regression methods for social scientists and introduces the methods in an easy-to-follow manner.

Space and geography are important aspects of social science research in fields such as criminology, sociology, political science, and public health. Many social scientists are interested in the spatial phenomena of various behaviors and events.

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