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Why Coarse Data is Ruining Your Silviculture Budgets

Silviculture budgets are built on assumptions. When those assumptions come from coarse sample data, costs escalate.

For example, survey data may suggest a block is tracking toward establishment. Resources get allocated elsewhere. Two years later, follow-up reveals significant regeneration gaps. Treatment costs have multiplied. When staff gets redeployed and timelines shift, those are real unplanned costs landing on operational budgets.

This pattern repeats because sampled data can't capture comprehensive block conditions. You're making resource allocation decisions based on statistical probability rather than actual inventory. When the probability is wrong, you find out late and pay more to fix it.

That's why Flash Forest launched Forest Intelligence Service to bring precision to early assessment and make budgets predictable.

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