The complex human-environment systems (CHES) group aims to achieve better CHES understanding, envisioning, and planning for improved sustainability. We view human-environment systems as complex systems, which are often characterized by a variety of complexity features such as high dimensionality, hierarchical structure, heterogeneity, nonlinearity, feedback, path dependence, emergence, and multi-finality. Complexity theory, landscape ecology, geographic information science, cyberinfrastructure theory and technology, (big) data science, and other relevant domain knowledge (e.g., sociology, demography, economics) leverage theoretical and methodological support toward our CHES research. We also aim to advance the theory, methodology, and applications in these disciplines. Our CHES research is currently applied to the following exemplar areas:
To handle CHES with such complexity features, we are developing a digital, high performance (e.g., big data friendly, parallel/clouds computing enabled, web-based), and 4-D holographic methodology for landscape representation, interdisciplinary and inter-scale integration, and systems modeling. Our CHES methodology focuses on digital representation, geovisualization and representation, animation, space-time analysis, micro-level modeling, and 4-dimensional (x, y, z, time) simulation of various landscape and human processes.
Below are a few exemplar models, demos, or movies (note: for test purpose only; the final versions will come up soon): Web-Based Model and Street Pedestrian Demo
This project seeks to advance the understanding of the impact of payments for ecosystem services (PES), a global conservation approach that incentivizes users of essential natural resources to protect the related ecosystems.
The goal of this project, is to compare the effects of food policies and programs on cardiovascular disease (CVD)-related outcomes and health care costs for adults.
This project will evaluate the interactions and feedbacks in coupled human and natural systems, and how these interactions and feedbacks affect the invasion of an exotic plant species in the community forests.