Project roadmap

The present site represents an intermediate stage in a larger line of work. The central conceptual claim is already in place: measured WUI boundary length is best understood not as a single scalar, but as a scale-conditioned quantity L_d(epsilon) that depends on both delineation choice and measurement scale. The synthetic demonstrations, analytical scaffold, and narrative website were developed to make that claim visible and testable.

The next stages of the project extend that framework outward. One stage concerns reproducibility: making the prompt-driven and code-driven workflow easier for other researchers to inspect and repeat. Another concerns empirical substance: replacing purely synthetic boundary objects with real settlement and vegetation data for small test regions. A third concerns communication: enriching the site with visual figures that clarify the theory and support interpretation.

This roadmap is therefore less a list of disconnected tasks than a description of how the project matures. The synthetic scaffold becomes a real-data pipeline. The website becomes a more complete scientific companion. The prompts become a more explicit research method. Each stage preserves the original question while making the answer more concrete.

Staged development path

The conceptual scaffold stage remains foundational: synthetic geometry continues to provide the cleanest environment for understanding why L_d(epsilon) varies and for checking whether interpretation and implementation remain aligned. During this stage, clarity and reproducibility are prioritized over spatial realism.

The real-data pilot stage extends that scaffold into one small test region with explicit settlement and vegetation inputs. The practical purpose is not immediate generalization, but disciplined pipeline maturation: acquisition conventions, preprocessing decisions, and boundary construction assumptions become inspectable and revisable.

The visual enrichment stage strengthens communication by pairing generated outputs with conceptual figures that make scale logic legible to a broader scientific audience. In this stage, manually uploaded figures and code-generated graphics are curated together so that interpretation and evidence stay closely linked.

The broader empirical comparison stage follows only after the pilot workflow is stable, at which point additional regions, alternative data products, and cross-sensor comparisons can be added without losing traceability back to the original analytical claim.