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Scientific Data· 2018Q1

Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010

Marius Gilbert, Gaëlle Nicolas, Giusepina Cinardi, Thomas P. Van Boeckel et al.

Short summary

A new version of the Gridded Livestock of the World (GLW 3) database provides global population densities for eight key livestock species for the year 2010 at a 10 km resolution.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Presents the Gridded Livestock of the World (GLW 3) database, a new version of global subnational livestock distribution data for 2010.
  • Includes population densities for cattle, buffaloes, horses, sheep, goats, pigs, chickens, and ducks.
  • Data is provided at a spatial resolution of approximately 10 km.
  • Offers two versions of species distribution: dasymetric weighting and areal weighting.

AI-generated from the title and abstract; the full text is not read.

Abstract

Global data sets on the geographic distribution of livestock are essential for diverse applications in agricultural socio-economics, food security, environmental impact assessment and epidemiology. We present a new version of the Gridded Livestock of the World (GLW 3) database, reflecting the most recently compiled and harmonized subnational livestock distribution data for 2010. GLW 3 provides global population densities of cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in each land pixel at a spatial resolution of 0.083333 decimal degrees (approximately 10 km at the equator). They are accompanied by detailed metadata on the year, spatial resolution and source of the input census data. Two versions of each species distribution are produced. In the first version, livestock numbers are disaggregated within census polygons according to weights established by statistical models using high resolution spatial covariates (dasymetric weighting). In the second version, animal numbers are distributed homogeneously with equal densities within their census polygons (areal weighting) to provide spatial data layers free of any assumptions linking them to other spatial variables.

The authors' abstract, as published at the source. Scientific Data, 2018 · DOI ↗

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Field: Agronomy and Crop Science

Agronomy and Crop ScienceAgricultural and Biological Sciences