Forest Diagnostics Phase Delivered

What was missing before diagnostics

Tree scatter quality was difficult to debug because failures were mostly visual and late. We lacked fast visibility into where candidates were lost and how biome filters affected output.

This phase introduced direct instrumentation so placement behavior can be inspected rather than guessed.

• Forest factor heatmap overlay for spatial validation.
• Per stage counters from candidate generation to final placement.
• Coverage metrics including density, patch count, and balance.

How diagnostics changed iteration

With stage level counters in place, we can identify whether losses happen in thresholds, SDF filtering, caps, or final dedupe. This shortens triage dramatically.

Heatmaps make it clear when algorithmic intent does not match spatial reality on the map.

• Parameter tuning now starts with evidence from stage deltas.
• Regression checks can compare current metrics against known good baselines.
• Biome specific anomalies are detectable without manual flythrough only.

Foundation for later phases

Diagnostics made the quick wins and structural phases possible because each change could be measured immediately. This reduced risk while tree count and complexity increased.

The same instrumentation now supports release gates and long term maintenance.

• Enabled safe threshold relaxation and separation experiments.
• Provided objective signals for quota and patch model tuning.
• Feeds into final validation documentation and checklists.

Key metrics snapshot

Diagnostics data is now structured so failures can be localized to a specific stage instead of treated as a single aggregate outcome.

This has become the baseline telemetry set for all tree pipeline tuning.

• Candidate -> placement -> SDF -> caps -> final counters.
• Forest-factor overlay coverage for spatial sanity checks.
• Patch statistics and quadrant-balance drift tracking.
• Regression alerts when stage conversion deviates from baseline.

Next Steps