Modeling structural change in spatial system dynamics: A Daisyworld example

TL;DR

This paper introduces a Python-based method to integrate system dynamics with GIS for modeling spatial structural changes, demonstrated through a Daisyworld example, highlighting the importance of spatio-temporal feedbacks.

Contribution

It presents a novel coupling of SD software with GIS to simulate structural changes in spatial system dynamics, extending beyond traditional diffusion models.

Findings

Spatial simulations reveal significant feedback effects.

Coupled SD-GIS approach enhances modeling of structural change.

Application potential in agriculture and disaster management.

Abstract

System dynamics (SD) is an effective approach for helping reveal the temporal behavior of complex systems. Although there have been recent developments in expanding SD to include systems' spatial dependencies, most applications have been restricted to the simulation of diffusion processes; this is especially true for models on structural change (e.g. LULC modeling). To address this shortcoming, a Python program is proposed to tightly couple SD software to a Geographic Information System (GIS). The approach provides the required capacities for handling bidirectional and synchronized interactions of operations between SD and GIS. In order to illustrate the concept and the techniques proposed for simulating structural changes, a fictitious environment called Daisyworld has been recreated in a spatial system dynamics (SSD) environment. The comparison of spatial and non-spatial simulations emphasizes the importance of considering spatio-temporal feedbacks. Finally, practical applications of structural change models in agriculture and disaster management are proposed.