Southern Africa Potential Vegetation Map, 5-Minute Resolution

Southern Africa's potential vegetation is mapped at a 5-minute spatial resolution, classifying natural vegetation into 15 distinct types. This dataset is derived primarily from the DISCover land cover data set, with gaps filled using the vegetation data set of Haxeltine and Prentice (1996). It models the vegetation that would most likely exist in the absence of current human activities, accounting for modern influences like fire suppression.

Use Cases

• Modeling baseline vegetation for climate change studies based on the 15-class potential vegetation classification.
• Comparing current land cover to potential natural vegetation using the DISCover-derived data.
• Informing regional conservation planning by identifying potential vegetation communities in southern Africa.
• Calibrating ecological succession models using the human-modified potential vegetation framework.

Strengths

• Provides a specific 15-class classification of potential vegetation types.
• Offers data at a consistent 5-minute spatial resolution for regional analysis.
• Derived from established sources like the DISCover land cover data set.

Limitations

• Metadata completeness is low: column names, row counts, and exact file sizes are unknown across all sources.
• Conflicting 'last updated' dates exist between platforms (1992 vs. 2026), creating uncertainty about data currency.
• Represents modeled potential vegetation, not necessarily historical pre-settlement conditions.

Provenance

Source

Navin Ramankutty and Jon Foley at the University of Wisconsin.

Collection Method

Derived mainly from the DISCover land cover data set, with regions dominated by land use filled using the vegetation data set of Haxeltine and Prentice (1996).

Freshness

2026-04-09 22:20:07.904477

Geography

Southern Africa