Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010
Autor: | Giuseppina Cinardi, Marius Gilbert, Sophie O. Vanwambeke, William Wint, Gaelle Nicolas, Timothy P. Robinson, Thomas P. Van Boeckel |
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Přispěvatelé: | UCL - SST/ELI/ELIC - Earth & Climate |
Jazyk: | angličtina |
Rok vydání: | 2018 |
Předmět: |
0301 basic medicine
Statistics and Probability Data Descriptor Livestock 010504 meteorology & atmospheric sciences Buffaloes Swine Species distribution Distribution (economics) Library and Information Sciences Decimal degrees 01 natural sciences Education Environmental impact 03 medical and health sciences Dasymetric map Agroecology Biogeography Risk factors Animals Horses Spatial analysis 0105 earth and related environmental sciences Population Density Sheep business.industry Goats Statistics Agriculture Sciences bio-médicales et agricoles Census Weighting Computer Science Applications 030104 developmental biology Geography Ducks Environmental chemistry Probability and Uncertainty Cattle Statistics Probability and Uncertainty business Cartography Chickens Information Systems |
Zdroj: | Scientific Data Scientific Data, Vol. 5, p. 180227 (2018) Scientific Data, 5 |
ISSN: | 2052-4463 |
Popis: | 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. SCOPUS: ar.j info:eu-repo/semantics/published |
Databáze: | OpenAIRE |
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