EO Capability Benefits
Agent-based modelling (ABM) of urban growth allows urban planners to visualise likely development scenarios reflective of a changing environment or of certain policy decisions, such as comparing the horizontal and vertical expansion of a city under a policy of densification through rigorous development control to a hands-off policy resulting in urban sprawl. In this way, optimal locations for certain land uses (residential, commercial, industrial or mixed) can be identified based on accessibility, suitability and demographic trends. In contexts of weak development control, ABM also allows policy makers to envision, decades into the future, likely growth scenarios resulting from major infrastructure investments.
EO Capability Description
Many EO Capabilities are, by their very nature, retrospective: they visualise events or phenomena which have taken place in the recent past. When multiple of these past snapshots are arranged in a timeseries, we can observe trends which can be linearly projected into the future to serve as a reasonable guess at a future trajectory. A more sophisticated approach for a wide range of questions, however, is to model how human “agents” interact with environmental systems based on a set of predefined “rules”: for instance, we know that middle and high-income populations tend to not settle in areas within the boundaries of a previous Flood Extent or near landfills as they have the means to settle elsewhere, whereas low-income populations do not. Similarly, we know that new development tends to occur near major links in a Transport Network but tends to avoid steep slopes (identified through Digital Elevation Models). In an ABM, the nature and weight of these rules controlling the behavior of “agents” in the system can be adjusted to reflect a particular scenario. Policies and development plans can then be adjusted to reflect the most desirable outcome.
