Salvage Assessment

Post-fire timber salvage viability is assessed by computing time-since-fire, deterioration stages, and grade impacts for each plot to generate a ranked priority list. This process uses JSON resources for deterioration and market factors to produce viability scores for harvest sequencing.

Timber deterioration and salvage windows are determined by species, mortality levels, and access conditions combined with market factors. The assessment applies JSON-based deterioration data to calculate timing and grade impacts that guide the urgency of harvest planning.

Yes, harvest planning for multi-plot burn sites is prioritized by evaluating varying species, mortality, access, and market conditions. The assessment generates a ranked list with viability scores and urgency labels to allocate resources effectively across different plots.

Salvage assessment scoring works by applying JSON resources for deterioration, market factors, and viability to compute plot-specific scores. These scores rank harvest priorities and produce actionable recommendations for field teams managing timber recovery.

No external Python dependencies are required for the post-fire timber salvage evaluation. The skill operates using a Python-based implementation with internal JSON resources to handle deterioration modeling, market factor analysis, and viability scoring.

Limitations in estimating salvage value for burned timber plots include reliance on predefined JSON deterioration and market factors. Accuracy depends on the quality of input data for species, mortality, and access conditions across the evaluated multi-plot burn sites.