Multi-Scale Spatio-Temporal Modeling
Interactions between the systems are typically dynamic, non-linear and nested. Understanding the dynamics of coupled natural and human (CNH) systems is critical for evaluating resilience and sustainability of social and eco-systems. To this end, we apply artificial intelligence (AI) and geosimulation to model dynamic interactions in CNH systems. Such models have been used to predict land cover change, population movement and eco-system degradation in scenarios of natural disasters and climate change.
Relevant Publications
- Qiang,
Y. and Lam, N., (2016) “The Impact of Hurricane Katrina on Urban Growth
in Louisiana: An Analysis Using Data Mining and Simulation Approaches”, International Journal of Geographical
Information Science. vol:30(9). [pdf]
- Qiang,
Y. and Lam, N., (2015) “Modeling Land Use and Land Cover Changes in a
Vulnerable Coastal Region Using Artificial Neural Networks and Cellular
Automata”, Environmental Monitoring and
Assessment. vol:187(3).
DOI:10.1007/s10661-015-4298-8 [pdf]
- Lam, NSN., Xu, Y.J.,
Liu, K., Dismukes, D.E., Reams, M., Pace, R.K., Qiang, Y., Narra, S., Li, K., Bianchette, T.A., Cai, H., Zou, L.,
Mihunov, V. (2018).
“Understanding the Mississippi River Delta as a Coupled Natural-Human System:
Research Methods, Challenges, and Prospects.” Water. vol: 10(8). [access].