Artificial intelligence has been increasingly used to support the study of coupled land systems, which are complex adaptive spatial systems driven by land use and land cover change. These artificial intelligence approaches comprise:
1) Machine learning (e.g., artificial neural networks, decision trees),
2) Evolutionary computation (e.g., genetic algorithms, evolutionary algorithms),
3) Distributed artificial intelligence (e.g., agent-based models, cellular automata, and swarm intelligence).
Recent developments in deep learning together with big data represent unique opportunities for using artificial intelligence to further advance spatiotemporally explicit land change modeling. However, applications of these cutting-edge artificial intelligence approaches into the study of land use and land cover change to tackle the associated spatiotemporal complexity pose grand challenges.
This special issue aims to explore various applications of artificial intelligence approaches to the study of land use and land cover change, including but not limited to
1) Natural resource management
2) Agricultural land management
3) Urban development
5) Public health
The special issue will focus on investigating how cutting-edge artificial intelligence approaches advance the spatiotemporally explicit land change modeling and associated knowledge in these domain studies. This investigation will provide insights into the complexity of related processes and thus the sustainability of coupled land systems.
The special issue is open to submission right now, and the submission deadline is: January 31st, 2019.
For more information, please refer to this link: http://www.mdpi.com/journal/sustainability/special_issues/Land_Use_and_Land_Cover_Change