Data concerning dynamic geographic processes are commonly captured and stored as discrete temporal snapshots. Snapshot data often requires 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 with basic transformations in mind rather than any particular underlying geographic process that might be driving the change (e.g. wildfire). This paper describes a means for making the interpolation between two snapshots more effective and efficient by including process-informed rules to guide the tweening process. Background is presented on geographic transformations, map animation, and tweening classifications . A rule-based tweening procedure is presented that is based on a set of deformation rules including a case study for wildfire snapshots. A hybrid approach using a rule-based and medial axis transformation is introduced. The paper concludes with a discussion of the strengths and limitations of the approaches.
Temporal data visualization: Kim and Cova REF introduced a rule-based grammar for interpolating between discrete temporal snapshots of geographic processes.
Tweening grammars: Deformation rules for representing change between discrete geographic entities
Comput. Environ. Urban Syst.
Comput. Environ. Urban Syst.
Geography Computer Science