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Gridded livestock density for 2020 (GLW4)

Food and Agriculture Organization of the United Nations

Part of: Gridded Livestock of the World (GLW)

licenseCC-BY-4.0updated2026-06-23
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Metadata
Raw record (JSON)STAC Collection ↗Suggest an edit ↗Report a problem ↗

Gridded Livestock of the World, version 4 (GLW 4) maps modelled densities of six livestock species: buffalo, cattle, sheep, goats, pigs, and chickens. This data is for the 2020 reference year. Densities are estimated with a Random Forest model that downscales harmonized subnational census counts onto a regular grid, so the values represent modelled distributions rather than direct observations. All of the values are number of animals per km^2

#gridded#modelled#exposureanimal husbandry ↗

Important note

Values are densities (head/km²), so individual pixel values are valid anywhere. However, the data are distributed in lat/long (EPSG:4326), where pixel ground area shrinks toward the poles. A standard lat/long map visually over-represents high-latitude densities, and naive spatial aggregation (totals, means, zonal statistics) assuming equal-area pixels will be biased. Reproject to an equal-area projection or weight by true pixel area for visualization and area-based analysis.

Quick start

Python
import xarray as xr

url = "https://digital-atlas.s3.amazonaws.com/cdh/data/glw4-2020/glw4-2020.zarr"
ds = xr.open_zarr(url)

import rioxarray

url = "https://digital-atlas.s3.amazonaws.com/cdh/data/glw4-2020/cog/glw4-2020-buffalo.tif"
da = rioxarray.open_rasterio(url, masked=True)

Full access details and endpoints

Intended uses

  • global and regional analysis of livestock distribution
  • livestock exposure layers for hazard, disease, and emissions assessment
  • spatial targeting at national and sub-national scale

Not recommended for

exact livestock counts

Why: values are spatially modeled estimates derived from census and other data

Use instead: official livestock census counts where available

Commodities

Water Buffalo ↗Cattle ↗Chickens ↗Goats ↗Swine ↗Sheep ↗

Variables

VariableTypeUnitDescription
Livestock Densityfloat32{head}/km-1Number of livestock per km2

Dimensions

Axes of the cube — spatial, temporal, and domain axes.

speciesspecies

The livestock species for which the data is provided

buffalocattlechickengoatpigsheep

Access & use

Cloud-optimised distributions — read just the window you need directly from object storage.

Machine-readable file index: STAC Collection

Data

zarr31.1 MB

Zarr store of GLW 4 2020

Format: Zarr — best for cloud-native analysis, reading just the slices you need from the full cube

No Data: NaN

Access the data

https://digital-atlas.s3.amazonaws.com/cdh/data/glw4-2020/glw4-2020.zarr

Other access methods
S3:s3://digital-atlas/cdh/data/glw4-2020/glw4-2020.zarr

zarr — usage examples

Python
import xarray as xr

url = "https://digital-atlas.s3.amazonaws.com/cdh/data/glw4-2020/glw4-2020.zarr"
ds = xr.open_zarr(url)

# Clip a window (East Africa) — subsets every variable in the store
window = ds.sel(x=slice(28, 52), y=slice(18, -12))

# ...or sample a single point
point = ds.sel(x=36.8, y=-1.3, method="nearest")
cogs

Cloud-optimized GeoTIFFs of GLW 4 2020

Format: Cloud-Optimized GeoTIFF — best for single-file downloads, visualisation, and traditional GIS tools

No Data: -3.4028235e+38

Access a specific fileDownload

https://digital-atlas.s3.amazonaws.com/cdh/data/glw4-2020/cog/glw4-2020-buffalo.tif

Other access methods

File pattern: glw4-2020-{species}.tif

HTTPS directory:https://digital-atlas.s3.amazonaws.com/cdh/data/glw4-2020/cog/
S3 directory:s3://digital-atlas/cdh/data/glw4-2020/cog/

cogs — usage examples

Python
import rioxarray

url = "https://digital-atlas.s3.amazonaws.com/cdh/data/glw4-2020/cog/glw4-2020-buffalo.tif"
da = rioxarray.open_rasterio(url, masked=True)

# Clip a window (East Africa)
window = da.rio.clip_box(
    minx=28, miny=-12, maxx=52, maxy=18
)

# ...or sample a single point
point = da.sel(x=36.8, y=-1.3, method="nearest")

Technical metadata

The full spatial, temporal, and modelling detail behind the summaries elsewhere on this page.

Spatial

CRS
EPSG:4326
Extent (W S E N)
[-180, -90, 180, 90]
Coverage
World
Resolution (xy)
5 arc-minutes (~10km at equator)

Temporal

Reference date
2020

Record

Resource type
dataset
Created
2026-06-23
Updated
2026-06-23

Provenance

Ordered processing steps, from source to publication.

  1. source2024-07-15

    Original GLW 4 release

    Derived from: GLW 4 2020

  2. cloud-optimize2026-06-23

    Optimize data for cloud storage

    code: https://github.com/CGIAR-Climate-Data-Hub/cdh-data-pipeline/blob/main/recipes/glw4.py @ 885ed96

How to cite

Please cite the dataset and any associated peer-reviewed publications.

Food and Agriculture Organization of the United Nations (2024). GLW 4: Gridded Livestock Density (Global - 2020 - 10 km) [Data set]. FAO Agro-Informatic Data Catalog. https://data.apps.fao.org/catalog/dataset/9d1e149b-d63f-4213-978b-317a8eb42d02 Accessed through the CGIAR Climate Action Data Hub, https://cgiar-climate-data-hub.github.io/catalog/glw4-2020/.

Contacts

Who produced this dataset, and who to reach about it.

Brayden YoungbergHub custodian
Alliance of Bioversity International and CIAT
Processor
b.youngberg@cgiar.org
Food and Agriculture Organization of the United NationsLicensor
ProducerProcessor
www.fao.org/home/en/ ↗
Dominik Wisser
Food and Agriculture Organization of the United Nations
Point of contact
Dominik.Wisser@fao.org
Giuseppina Cinardi
Food and Agriculture Organization of the United Nations
Point of contact
giuseppina.cinardi@fao.org
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