Overview

WorldPop is a global population mapping initiative that produces high-resolution, gridded estimates. The constrained top-down approach disaggregates census totals to ~100 m grids but only within cells mapped as settlements or buildings. This improves alignment with where people actually live.

Methodology & Spatial Characteristics

• Settlement mask: Allocation restricted to cells with mapped buildings/built areas.

• Machine learning: Random Forest models use census + covariates (satellite, land cover, infrastructure).

• Resolution: ~3 arc-seconds (~100 m).

• Normalization: Totals aligned to census aggregates.

Strengths & Use Cases

• Settlement alignment: Maps residential distribution accurately.

• Higher resolution: Finer than LandScan’s ~1 km.

• Reduced misallocation: Prevents population in empty zones.

Limitations & Caveats

• Settlement detection: Missing or misclassified dwellings lead to underestimates.

• Input census quality: Errors propagate.

• Comparability: Diverges from ambient-use datasets like LandScan.

Related Resources

• LandScan Deep Dive

• LandScan vs WorldPop: What Changes & Why It Matters

• Learn more about census data

• Learn how to measure population across the globe

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