My research focuses on the productivity of harvesting systems in Maine. This research generally includes on the ground observation and the conducting of time and motion studies. I recently started using agent based modelling as a tool to simulate the interaction of various machines and the change in productivity based on specific input variables.

Modeling land use change from smallholder agricultural intensification

Agricultural expansion in the rural tropics brings much needed economic and social development in developing countries. On the other hand, agricultural development can result in the clearing of biologically-diverse and carbon-rich forests. To achieve both development and conservation objectives, many government policies and initiatives support agricultural intensification, especially in smallholdings, as a way to increase crop production without expanding farmlands. However, little is understood regarding how different smallholders might respond to such investments for yield intensification. It is also unclear what factors might influence a smallholder’s land-use decision making process. In this proposed research, I will use a bottom-up approach to evaluate whether investments in yield intensification for smallholder farmers would really translate to sustainable land use in Indonesia. I will do so by combining socioeconomic and GIS data in an agent-based model (Land-Use Dynamic Simulator multi-agent simulation model). The outputs of my research will provide decision makers with new and contextualized information to assist them in designing agricultural policies to suit varying socioeconomic, geographic and environmental contexts.

I am broadly interested in using Agent-based Modelling, Microsimulation, Geosimulation or a hybrid of these approaches as methodology to investigate complex dynamics of systems in various domains. I am also interested in exploring the potential of simulation models as decision support and policy-informing tools.