The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010
Open accessAbstract
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.
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Cites
High-Resolution Global Maps of 21st-Century Forest Cover Change
Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., Thau, D., Stehman, S. V., Goetz, S. J., Loveland, T. R., et al. (2013) · Science · doi:10.1126/science.1244693 · Cited by 11,704
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Global Trends in Antimicrobial Use in Food Animals from 2017 to 2030
Tiseo, K., Huber, L., Gilbert, M., Robinson, T. P., & Van Boeckel, T. P. (2020) · Antibiotics · doi:10.3390/antibiotics9120918 · Cited by 689
Self-citationDisentangling the numbers behind agriculture-driven tropical deforestation
Pendrill, F., Gardner, T. A., Meyfroidt, P., Persson, U. M., Adams, J., Azevedo, T., Bastos Lima, M. G., Baumann, M., Curtis, P. G., De Sy, V., et al. (2022) · Science · doi:10.1126/science.abm9267 · Cited by 572
Global trends in grassland carrying capacity and relative stocking density of livestock
Piipponen, J., Jalava, M., de Leeuw, J., Rizayeva, A., Godde, C., Cramer, G., Herrero, M., & Kummu, M. (2022) · Global Change Biology · doi:10.1111/gcb.16174 · Cited by 129
Zhou, Y., Yang, L., Han, X., Han, J., Hu, Y., Li, F., Xia, H., Peng, L., Boschiero, C., Rosen, B. D., et al. (2022) · Genome Research · doi:10.1101/gr.276550.122 · Cited by 89
Risk to rely on soil carbon sequestration to offset global ruminant emissions
Wang, Y., de Boer, I. J. M., Persson, U. M., Ripoll-Bosch, R., Cederberg, C., Gerber, P. J., Smith, P., & van Middelaar, C. E. (2023) · Nature Communications · doi:10.1038/s41467-023-43452-3 · Cited by 39
Metadata
- Authors
- Gilbert, M., Nicolas, G., Cinardi, G., Van Boeckel, T. P., Vanwambeke, S. O., Wint, G. R. W., & Robinson, T. P.
- Venue
- Scientific Data
- Published
- 2018-10-30
- Volume
- 5
- Issue
- 1
- Pages
- 180227-180227
- ISSN
- 2052-4463 (ISSN-L)
- OpenAlex
- W2899100088
- Cited by
- 732
- References
- 1
- Type
- data paper
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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