Gridded livestock density (Global - 2010 - 10 km) - GLW3

This dataset contains the most up to date version of GLW 4 for the reference year 2015 for the following species: cattle, sheep, goats, buffaloes, horses, pigs, chicken and ducks. The individual species datasets are available at global extent and 5 minutes of arc resolution (approx. 10 km at the equator). The fourth version of GLW, compared to the previous ones, reflects the most recently compiled and harmonized subnational livestock distribution data and much more detailed metadata. The layers contain the density of animals per pixel, with weight estimated by the Random Forest model. The livestock species modelled include: buffaloes, cattle, chickens, ducks, goats, horses, pigs and sheep. All datasets are licensed through a Creative Commons Attribution 4.0 International License. **References** - Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010 - Income Disparities and the Global Distribution of Intensively Farmed Chicken and Pigs - Using Random Forest to Improve the Downscaling of Global Livestock Census Data **Data creation:** 2022-05-06 **Supplemental Information:** Unit: head/km² or birds/km² Data type: Float64 No data value: -9999 Spatial resolution: Approximately 10km (0.08333 degrees) Spatial extent: World Spatial Reference System (SRS): EPSG:4326 - WGS84 - Geographic Coordinate System (lat/long) **Contact points:** Resource Contact: [Dominik Wisser (FAO-NSAL)](mailto:Dominik.Wisser@fao.org) Metadata Contact: [Giuseppina Cinardi (FAO-NSAL)](mailto:giuseppina.cinardi@fao.org) **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International licence (CC-BY-4.0) **Online resources:** Animal density labels for WMTS Download: Gridded Livestock of the World – 2015 (GLW 4)

This dataset contains the most up to date version of GLW 4 for the reference year 2020 for the following species: buffalo, cattle, sheep, goats, pigs and chicken. The individual species datasets are available at global extent and 5 minutes of arc resolution (approx. 10 km at the equator).   The fourth version of GLW, compared to the previous ones, reflects the most recently compiled and harmonized subnational livestock distribution data and much more detailed metadata.   The layers contain the density of animals per km², with weight estimated by the Random Forest model. The livestock species modelled include: buffaloes, cattle, chickens, goats, pigs and sheep

This dataset contains the most up to date version of GLW 4 for the reference year 2020 for the following species: buffalo, cattle, sheep, goats, pigs and chicken. The individual species datasets are available at global extent and 5 minutes of arc resolution (approx. 10 km at the equator). The layers contain the density of animals per km², with weight estimated by the Random Forest model. The livestock species modelled include: buffaloes, cattle, chickens, goats, pigs and sheep

This dataset contains the most up to date version of GLW 4 for the reference year 2020 for the following species: buffalo, cattle, sheep, goats, pigs and chicken,at the resolution of 0.05 ×0.05 ,  The fourth version of GLW, compared to the previous ones, reflects the most recently compiled and harmonized subnational livestock distribution data

Estimated density of people per grid-cell, approximately 1km (0.008333 degrees) resolution. The units are number of people per Km² per pixel, expressed as unit: "ppl/Km²". The mapping approach is Random Forest-based dasymetric redistribution. The WorldPop project was initiated in October 2013 to combine the AfriPop, AsiaPop and AmeriPop population mapping projects. It aims to provide an open access archive of spatial demographic datasets for Central and South America, Africa and Asia to support development, disaster response and health applications. The methods used are designed with full open access and operational application in mind, using transparent, fully documented and peer-reviewed methods to produce easily updatable maps with accompanying metadata and measures of uncertainty. Acknowledgements information at https://www.worldpop.org/acknowledgements **Data revision:** 2018-10-24 **Supplemental Information:** - Data Type: "Float32" - No Data value: -9999 **Citation:** For all WorldPop datasets, please cite the WorldPop website as the source: www.worldpop.org. Additionally, the following academic publications should be cited for the specific datasets listed: - Americas population data: Alessandro Sorichetta, Graeme M. Hornby, Forrest R. Stevens, Andrea E. Gaughan, Catherine Linard, Andrew J. Tatem, 2015, High-resolution gridded population datasets for Latin America and the Caribbean in 2010, 2015, and 2020, Scientific Data, doi:10.1038/sdata.2015.45 - Africa population count data: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. - Asia population count data: Gaughan AE, Stevens FR, Linard C, Jia P and Tatem AJ, 2013, High resolution population distribution maps for Southeast Asia in 2010 and 2015, PLoS ONE, 8(2): e55882. **Contact points:** Metadata Contact: [Population Counts](mailto:info@worldpop.org) Resource Contact: [WorldPop](mailto:info@worldpop.org) **Online resources:** Download the data from Google Cloud Storage Download data from the Worldpop official website

The raster dataset consists of a 1 km score grid for slaughterhouse industry facilities, produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The analysis is based on livestock production potential using proximity to cities, crop production, and aggregated average weighted density of cattle, goats, sheep and pigs. Animal weight: Goat 30kg (X0.09); Sheep 30kg (X0.09); Cattle 210kg (X0.63), Pig 63kg (X0.19). The score is achieved by processing sub-model outputs that characterize logistical factors: 1. Supply - Feed and livestock distribution. 2. Infrastructure - Transportation network (accessibility). 3. Atlas AI Asset Wealth Index. It consists of an arithmetic weighted sum of normalized grids (0 to 100): (”Livestock Density” * 0.4) + ("Asset Wealth" * 0.3) + (“Major Cities Accessibility” * 0.2) + ("Crop Production" * 0.1). **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:nelson.rosasribeirofilho@fao.org) **Data lineage:** lineage statement Major data sources, FAO GIS platform Hand-in-Hand and OpenStreetMap (open data) including the following datasets 1. Human Population Density 2020 – WorldPop2020 - Estimated total number of people per grid-cell 1km. 2. GLW Gridded Livestock of the World - Gridded Livestock of the World (GLW 3 and GLW 2). 3. IFPRI MapSPAM crop production. 4. OpenStreetMap. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Download Kenya location score TIF (zip) dataset