Agent-based land change modeling driven by artificial intelligence

Keywords: Agent-based Model, Artificial Intelligence, Land Use and Land Cover Change
Abstract Type: Paper Abstract

Abstract

Agent-based models have been extensively applied in the study of land use and land cover change. Complex system behavior and dynamics can be represented using agent-based modeling as a spatiotemporal simulation approach. The objective of this study is to investigate the role of geospatial artificial intelligence in agent-based land change modeling. Geospatial artificial intelligence has gained increasing recognition in the study of geospatial systems. However, the application of geospatial artificial intelligence in agent-based modeling of complex land systems is still in its early stage. We will present a case study in which an agent-based land change model driven by geospatial artificial intelligence is developed to (better) understand the space-time complexity of land systems.