Spatial Dynamic Models for Inclusive Cities: A Brief Concept of Cellular Automata (CA) and Agent- based model (ABM)

Urban areas in the developing countries experience a rapid urban growth. Current practices in urban modelling employ demographic and social data as the inputs for urban models. These practices occur as a result of data scarcity in the developing countries. These models are static in which only captures the shapes of a city at the selected time. They have limitation in presenting the sequence of simulations over a series of time. Another limitation of static models is the use of administrative boundary as their unit of analysis, which often less accurate for large regions. When facing with a mounting complexity of a city, the decision makers need to obtain as much as information to guide their decisions. They need to know how big the magnitude of urban problems could have, and where exactly the policy should be implemented. They also need to know how different stakeholders influence the spaces in the cities. Cellular Automata (CA) and Agent-based Model (ABM) are the two prominent dynamic models occupying a large portion of spatial discussions in the last two decades. In the context of research in Indonesia, they are less recognized, and have less contribution to many urban applications. This article aims to briefly introduce the concept of CA and ABM in spatial context, in particular land use land cover changes in urban areas. Examples and potential application for inclusive cities are given in the last part of the discussion.