Global Food Supply Distance and Foodsheds for Six Crop Types

A 2020 study by Kinnunen et al. from Aalto University provides geospatial data on global food supply. The dataset includes globally optimized travel distances between crop production and consumption, as well as foodshed maps, for six crop functional types. It covers four scenarios analyzing the impact of reducing food waste and yield gaps.

Use Cases

• Modeling optimal food allocation networks based on travel time minimization described in the dataset.
• Analyzing the spatial connectivity of food supply areas using the foodsheds data.
• Assessing the potential impact of reducing food waste on supply distances using the 'halfLoss' scenario.
• Evaluating the effect of closing yield gaps on local food self-sufficiency using the 'halfYieldGap' scenario.
• Mapping theoretical food flows for specific crop types like maize, rice, or pulses.

Strengths

• Covers six major crop functional types: maize, pulses, rice, temperate cereals, tropical cereals, and tropical roots.
• Provides data for four distinct scenarios: a baseline, halving food waste, halving the yield gap, and a combined scenario.
• Offers global spatial coverage with a 0.5-degree resolution and uses the standard WGS84 projection.
• Data is available in two common geospatial formats: NetCDF and multi-band GeoTIFF.

Limitations

• Dataset specifications like row count, file size, and last update date are unknown.
• Column-level documentation is absent; field semantics must be inferred from the description or original publication.
• The data represents a theoretical optimization model; its direct applicability to real-world logistics may require validation.

Provenance

Source

Pekka Kinnunen, Aalto University, supplement to Kinnunen et al. 2020, Nature Food.

Collection Method

Globally optimized model minimizing travel time cost from crop production to consumption.

Geography

Global extent: -180 to 180 degrees longitude, -90 to 90 degrees latitude.