Tweening grammars: Deformation rules for representing change between discrete geographic entities

Data concerning dynamic geographic processes are commonly captured and stored as discrete temporal snapshots. Snapshot data often require interpolation to compensate for large data collection intervals. Metamorphosis (morphing or tweening) is the study of how an object changes over time. Tweening was developed to perform basic transformations rather than to represent a particular geographic process that might be informing the change (e.g., wildfire). This paper describes a means for making the interpolation between two snapshots more effective and efficient by introducing process-informed rules to guide the tweening. Tweening grammars are devised to enable dynamic deformation between source and target shapes. A hybrid approach using a semi-automated correspondence rule and medial axis transformation is explored, followed by a case study of tweening an actual wildfire and an example of validating a set of tweening rules.