AGENT-BASED MODELING OF URBAN TROPICAL GREEN INFRASTRUCTURE INVESTMENT

This document describes a conceptual methodology to investigate the dynamics of “bottom-up” green infrastructure (GI) investment in tropical urban areas. This approach seeks to develop a methodology of study to understand what policies may lead to more efficient investment policies that lead to a sustainable urban setting. Agent-based Modeling (ABM) was used to replicate a stylized tropical urban environment setting and employed to investigate the emergent patterns of increased GI and greenspace through investments at the local level. Initial modeling results illustrate the generalized methodology developed produces outputs consistent with expectations, thus validating the approach. Further, modeling output illustrates typical policies and conditions necessary to produce a sustainable tropical urban setting using the “Green City” metric. Current modeling efforts employed a stylized spatial setting and synthetic behavioral data for agents and their environment. Similarly, the modeling presented in this paper is not temporally-dynamic. The ability to transfer findings from this research is limited by the conceptual nature of the modeling. Findings from the work is applicable to the development of future modeling efforts employing real-world spatial data, economic behavioral rules based upon literature or surveys, and temporal dynamism reflecting realistic urban growth and investment. Increasing greenspace in urban settings improves the health, well-being and economic condition for tropical urban dwellers. Further, investments in GI can have direct benefits to air and water quality, particularly in addressing impacts from uncontrolled stormwater runoff. To date, no other efforts have been found to study private investment in green infrastructure using an ABM approach.