Annual Woody Vegetation Change Classes from Landsat Imagery

Vegetation change products identify transitions in perennial woody cover between forest, sparse woody, and non-woody classifications. Landgate produces these annual datasets using 30-meter resolution Landsat imagery. Change classes include no change, non-woody to sparse, non-woody to forest, sparse to non-woody, forest to non-woody, and forest to sparse.

Use Cases

• Analyze forest to non-woody change classes to quantify deforestation trends.
• Map transitions from non-woody to sparse woody classifications for land rehabilitation monitoring.
• Track sparse to non-woody change over time to assess vegetation loss.
• Use annual change products to model long-term shifts between the three primary cover classifications.

Strengths

• Annual production provides consistent time-series data.
• Based on 30-meter ground pixel resolution Landsat imagery.
• Distinguishes six specific change classes including bidirectional transitions.

Limitations

• Specific spatial coverage (geography) and temporal range are not detailed in the input.
• Data volume (row/column counts) and sample size are unknown.
• Access is via WMS and ArcGIS services, which may limit direct analytical use for some ML workflows.

Provenance

Source

Landgate

Collection Method

Derived from Landsat imagery (30m ground pixel) vegetation cover datasets.

Time Range

Annual products; specific start/end years not fully specified (mentions 2010-2011).

Freshness

Last updated March 2026, suggesting ongoing maintenance.

Geography

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