We use and develop spatial data for livestock, nutrient production, and agricultural systems at multiple resolutions and spatial extent (regional, national, and global). Spatial data are important to us because they help us better understand the drivers of agriculture at the local and global scale. Spatial data analysis is a principal component of many of our projects that address decision making at multiple locations.
|Dataset download link||Description||Reference|
|Livestock production systems||Biologically consistent, spatially disaggregated global livestock datasets for eight livestock production systems for four animal species (cattle, small ruminants, pigs, and poultry). These datasets contain information on biomass use, production, feed efficiency, excretion, and greenhouse gas emissions.||Herrero et al. (2013)|
|Global gridded maps of nutrient production and nutrient diversity for different farm sizes. The collection includes data for production levels of 41 major crops, seven livestock, and 14 aquaculture and fish products and vitamin A, vitamin B₁₂, folate, iron, zinc, calcium, calories, and protein as well as food production diversity indices; the Shannon diversity index [H], the Modified Functional Attribute Diversity (MFAD), and species richness [S].||Herrero et al. (2017)|
|Multiple cropping systems of the world||Global gridded datasets of physical cropland of different single and multiple cropping systems composed of 25 different rainfed and irrigated annual crops. The collection includes different levels of aggregation, from individual crops to crop groups and overall cropping intensity.||Waha et al. (2020)|