LandABM

Scientific hypothesis

The same biofuel policies and market trends have different impacts on farmers’ decision making on crop choices in different geographic areas that are primarily characterized based on the percentage of farmer population and distance to biofuel facilities.

Approach

Agent-based modeling of farmers’ decision making on land use allocation to understand place-based impact of biofuel polices on such decision making.

Methods

  • Calibrate LandABM based on the spatial patterns of land use derived from remote sensing imagery;
  • Use machine learning techniques within ABM to characterize farmers’ learning about policies and market trends in their decision making on crop choices;
  • Synthetic spatiotemporal modeling of agent-environment interactions.

Case Study

  • Champaign county
  • Another county in Illinois

Progress

  • Conceptual design
  • Data preparation
  • Programming
  • Experiments

Code Location on SVN

https://svn.cigi.uiuc.edu/cigi/landuse/

Weekly Meetings

  • 3-4pm on every Thursday

Project Team: Anand Padmanabhan, Wenwu Tang, Shaowen Wang