What was built A continuous raster map of above-ground vegetation carbon stock (tonnes per hectare) across Lane and Douglass Counties, Oregon — rendered as a red-to-green gradient from disturbed land to dense old-growth forest.
Who it was for Land managers and climate planners conducting carbon sequestration assessment and conservation prioritization at the county scale.
Why it mattered Aggregate carbon totals don't drive conservation decisions — spatial distribution does. This output shows where carbon is concentrated and where gaps exist, giving managers the geographic context that makes prioritization possible.

The Challenge

Carbon sequestration is a spatial problem. Forest cover isn't uniform — carbon stock concentrations vary dramatically based on vegetation type, stand age, and disturbance history. Knowing the aggregate carbon stored in a county is useful. Knowing where it's concentrated, and where gaps exist, is what drives conservation and land management decisions.

This analysis mapped above-ground vegetation carbon stock in tonnes per hectare across Lane and Douglass Counties in southern Oregon — a region with significant old-growth forest patches and active timber extraction. The red-to-green gradient makes the distribution legible at a glance: deep green for high-carbon forest zones, red for low-carbon or disturbed land.

The output supports carbon sequestration assessment and climate resilience planning at the county scale, giving land managers spatial context for conservation prioritization.

This work supports land management and conservation planning by identifying spatial patterns in carbon storage across the region.

Carbon Stock Gradient — Above-Ground Vegetation (t/ha)
Low — disturbed / cleared land High — dense old-growth forest

"Carbon sequestration is a spatial problem. This map makes the distribution visible — not just how much carbon is stored, but where."

Process

  1. 1
    Research Identified carbon stock dataset for Oregon; assessed appropriate spatial resolution for county-scale analysis.
  2. 2
    Data Prep Processed raster; established classification for continuous t/ha gradient output.
  3. 3
    GIS Work Applied symbolization; designed red-to-green gradient for carbon density visualization; verified spatial extent against county boundaries.
  4. 4
    Output Published raster map; supports land management and climate planning decisions.
Principle 01
Structure before software

Before choosing a classification scheme or color ramp, the analytical question has to be settled: are we showing discrete classes or a continuous distribution? Who is reading this map and what decisions will they make? The answer to those questions determines every downstream choice.