The complex human-environment systems (CHES) group is now an official institute at San Diego State University (SDSU) named the Center for Complex Human-Environment Systems. The CHES group aims to achieve better CHES understanding, envisioning, planning, and sustainability via a hybrid of data science, artificial intelligence, and spatial/applied statistics approach. 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, and other relevant disciplinary knowledge leverage theoretical and methodological support toward our CHES research. Our CHES research is currently applied to the following exemplar areas:
To handle CHES with such complexity features, we are developing a high performance enabled, big data friendly, 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 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.