Forested Land Cover Data for Coastal Marten Connectivity Analysis in CA/OR/WA

A 30m resolution forested land cover raster derived from the Old-growth Structure Index (OGSI) parameter, which is based on the Gradient Nearest Neighbor (GNN) model. The dataset was created by the Department of the Interior for a landscape connectivity model focused on the coastal marten (Martes caurina humboldtensis). OGSI values from 0-100 were reclassified into 10 equal interval bins to represent forest habitat quality.

Use Cases

• Modeling landscape connectivity and resistance for the coastal marten based on forest structure.
• Assessing habitat quality for old-growth obligate species using the Old-growth Structure Index (OGSI).
• Conducting least-cost path or corridor analyses using the derived resistance surface components.
• Studying forest structure patterns across California, Oregon, and Washington using consistent, fine-scale data.

Strengths

• Spatial grain of 30m x 30m (900 m2) provides fine-scale detail.
• Covers a vast area spanning California, Oregon, and Washington with consistent methodology.
• Based on the Gradient Nearest Neighbor (GNN) model, which interpolates thousands of forest survey points using Landsat imagery, elevation, climate, and geology.

Limitations

• Non-forested land cover types (<10% tree cover) are excluded and addressed in a separate data layer.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Department of the Interior, using data from the LEMMA laboratory's Gradient Nearest Neighbor (GNN) model.

Collection Method

The Old-growth Structure Index (OGSI) parameter was extracted from the GNN dataset and reclassified into 10 equal interval bins.

Freshness

Last updated 2026-03-04 08:25:20.072694; freshness should be verified.

Geography

California, Oregon, and Washington, USA.