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This dataset is supplement to the following publication (please cite that when using the data): Kinnunen et al. 2020. Local food crop production can fulfil demand for less than one-third of the population. Nature Food 1: 229–237. http://doi.org/10.1038/s43016-020-0060-7 Data description Distance to food: Globally optimized distance between crop production and consumption. The optimization creates a theoretical food allocation set-up that minimizes travel time cost from crop production to consumption. Data is in two formats: NetCDF (dist_food_netcdf.zip) and multi-band geotiff (dist_food_tif.zip). The data includes: baseline scenario (dist_food_baseline.nc / .tif) and three other scenarios where food availability is changed by decreasing food waste by half (dist_food_halfLoss.nc / .tif) halving the yield gap (dist_food_halfYieldGap.nc / .tif) both of these measures together (dist_food_halfLoss_halfYielGap.nc / .tif) The data covers six crop functional types: maize, pulses, rice, temperate cereals, tropical cereals and tropical roots Dataset specifications: spatial extent: -180, 180, -90, 90 (xmin, xmax, ymin, ymax) spatial resolution: 0.5 degrees projection: long/lat WGS84 layers: 1: maize, 2: pulses, 3: rice, 4: temp_cereals, 5: trop_cereals, 6: trop_roots no data value: -999 unit: km Foodsheds: The data contains global foodsheds which are areas that are connected by food flows between raster cells. The food flows are from a theoretical food allocation set-up that minimizes travel time cost from crop production to consumption. In addition to normal foodsheds (values>0), there are two special cases: ridge-cells (value: -99) and unconnected single cells (value: -50). Ridge-cells are raster cells connected to multiple foodsheds, while being able to satisfy their own demand locally. Unconnected single cells are not connected to any other foodshed. Each positivie value is a crop specific id, signifying a connected foodshed area. Data is in two formats: NetCDF (foodsheds_netcdf.zip) and multi-band geotiff (foodsheds_tif.zip). The data includes: baseline scenario (foodsheds_baseline.nc / .tif) and three other scenarios where food availability is changed by decreasing food waste by half (foodsheds_halfLoss.nc / .tif) halving the yield gap (foodsheds_halfYieldGap.nc / .tif) both of these measures together (foodsheds_halfLoss_halfYielGap.nc / .tif) The data covers six crop functional types: maize, pulses, rice, temperate cereals, tropical cereals and tropical roots Dataset specifications: spatial extent: -180, 180, -90, 90 (xmin, xmax, ymin, ymax) spatial resolution: 0.5 degrees projection: long/lat WGS84 layers: 1: maize, 2: pulses, 3: rice, 4: temp_cereals, 5: trop_cereals, 6: trop_roots no data value: -999 unit: -
{"references": ["Kinnunen et al. 2020. Local food crop production can fulfil demand for less than one-third of population. Nature Food. http://doi.org/10.1038/s43016-020-0060-7"]}
Supplement to http://doi.org/10.1038/s43016-020-0060-7
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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