Buffalo — Livestock units per agricultural land area by country
The Livestock Patterns domain of FAOSTAT contains data on livestock numbers, shares of major livestock species and densities of livestock units in the agricultural land area. Values are calculated using Livestock Units (LSU), which facilitate aggregating information for different livestock types. Data are available...
What the numbers show
Buffalo — Livestock units per agricultural land area is currently reported for 69 countries. The highest value is 0.62 LSU/ha in Pakistan; the lowest is 0 LSU/ha in USSR.
The median across all reporting countries is 0 LSU/ha, and the mean is 0.0478 LSU/ha.
Over the past decade 7 countries rose and 12 fell. The largest increase was in Iraq (up 100.0%), and the largest decrease in Singapore (down 75.0%).
Buffalo — Livestock units per agricultural land area: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Pakistan | 0.62 LSU/ha | 2023 | up 34.8% | volatile |
| 2 | Nepal | 0.41 LSU/ha | 2023 | down 36.9% | rising |
| 3 | Lao People's Democratic Republic | 0.37 LSU/ha | 2023 | up 2.8% | rising |
| 4 | India | 0.31 LSU/ha | 2023 | up 3.3% | rising |
| 5 | Timor-Leste | 0.28 LSU/ha | 2023 | up 27.3% | falling |
| 6 | Egypt | 0.25 LSU/ha | 2023 | down 65.8% | rising |
| 7 | Philippines | 0.15 LSU/ha | 2023 | down 6.2% | falling |
| 8 | Viet Nam | 0.12 LSU/ha | 2023 | down 29.4% | falling |
| 9 | Myanmar | 0.11 LSU/ha | 2023 | down 38.9% | rising |
| 10 | Cambodia | 0.08 LSU/ha | 2023 | down 11.1% | falling |
| 10 | Bangladesh | 0.08 LSU/ha | 2023 | unchanged | rising |
| 12 | Trinidad and Tobago | 0.07 LSU/ha | 2023 | unchanged | rising |
| 13 | China, Hong Kong SAR | 0.06 LSU/ha | 2023 | up 50.0% | volatile |
| 13 | Bhutan | 0.06 LSU/ha | 2023 | up 20.0% | volatile |
| 15 | Sri Lanka | 0.05 LSU/ha | 2023 | down 28.6% | falling |
| 15 | Brunei Darussalam | 0.05 LSU/ha | 2023 | down 58.3% | volatile |
| 17 | China, mainland | 0.04 LSU/ha | 2023 | unchanged | rising |
| 17 | China | 0.04 LSU/ha | 2023 | unchanged | rising |
| 19 | Thailand | 0.03 LSU/ha | 2023 | down 25.0% | volatile |
| 20 | Iraq | 0.02 LSU/ha | 2023 | up 100.0% | rising |
| 20 | Azerbaijan | 0.02 LSU/ha | 2023 | down 50.0% | falling |
| 20 | Italy | 0.02 LSU/ha | 2023 | unchanged | volatile |
| 20 | Micronesia (Federated States of) | 0.02 LSU/ha | 2023 | unchanged | rising |
| 24 | Georgia | 0.01 LSU/ha | 2023 | unchanged | flat |
| 24 | Singapore | 0.01 LSU/ha | 1991 | down 75.0% | volatile |
| 24 | Indonesia | 0.01 LSU/ha | 2023 | down 50.0% | falling |
| 24 | Malaysia | 0.01 LSU/ha | 2023 | unchanged | volatile |
| 28 | Slovakia | 0 LSU/ha | 2023 | — | flat |
| 28 | Serbia and Montenegro | 0 LSU/ha | 2005 | — | flat |
| 28 | OECD | 0 LSU/ha | 2023 | — | flat |
| 28 | Caribbean | 0 LSU/ha | 2023 | — | flat |
| 28 | Iran (Islamic Republic of) | 0 LSU/ha | 2023 | — | volatile |
| 28 | Russian Federation | 0 LSU/ha | 2023 | — | flat |
| 28 | Syrian Arab Republic | 0 LSU/ha | 2023 | — | flat |
| 28 | Türkiye | 0 LSU/ha | 2023 | — | volatile |
| 28 | China, Taiwan Province of | 0 LSU/ha | 2023 | — | volatile |
| 28 | Yugoslav SFR | 0 LSU/ha | 1991 | — | flat |
| 28 | Jordan | 0 LSU/ha | 2023 | — | flat |
| 28 | Albania | 0 LSU/ha | 2023 | — | flat |
| 28 | Armenia | 0 LSU/ha | 2023 | — | flat |
| 28 | Bulgaria | 0 LSU/ha | 2023 | — | volatile |
| 28 | Brazil | 0 LSU/ha | 2023 | — | flat |
| 28 | Colombia | 0 LSU/ha | 2023 | — | flat |
| 28 | Cyprus | 0 LSU/ha | 2023 | — | flat |
| 28 | Czechia | 0 LSU/ha | 2023 | — | flat |
| 28 | Germany | 0 LSU/ha | 2023 | — | flat |
| 28 | Denmark | 0 LSU/ha | 2023 | — | flat |
| 28 | Spain | 0 LSU/ha | 2023 | — | flat |
| 28 | Estonia | 0 LSU/ha | 2023 | — | flat |
| 28 | Finland | 0 LSU/ha | 2023 | — | flat |
| 28 | Greece | 0 LSU/ha | 2023 | — | volatile |
| 28 | Hungary | 0 LSU/ha | 2023 | — | flat |
| 28 | Ireland | 0 LSU/ha | 2023 | — | flat |
| 28 | Micronesia | 0 LSU/ha | 2023 | — | flat |
| 28 | Kazakhstan | 0 LSU/ha | 2023 | — | flat |
| 28 | Lithuania | 0 LSU/ha | 2023 | — | flat |
| 28 | Luxembourg | 0 LSU/ha | 2023 | — | flat |
| 28 | Latvia | 0 LSU/ha | 2023 | — | flat |
| 28 | North Macedonia | 0 LSU/ha | 2023 | — | flat |
| 28 | Malta | 0 LSU/ha | 2023 | — | flat |
| 28 | Mauritius | 0 LSU/ha | 2023 | — | flat |
| 28 | Poland | 0 LSU/ha | 2023 | — | flat |
| 28 | Portugal | 0 LSU/ha | 2023 | — | flat |
| 28 | Romania | 0 LSU/ha | 2023 | — | flat |
| 28 | Suriname | 0 LSU/ha | 2023 | — | flat |
| 28 | Slovenia | 0 LSU/ha | 2023 | — | flat |
| 28 | Sweden | 0 LSU/ha | 2022 | — | flat |
| 28 | Tajikistan | 0 LSU/ha | 2023 | — | flat |
| 28 | USSR | 0 LSU/ha | 1991 | — | flat |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Southern Asia 0.26 LSU/ha
- Asia 0.07 LSU/ha
- South-eastern Asia 0.06 LSU/ha
- Eastern Asia 0.03 LSU/ha
- World 0.02 LSU/ha
- Net Food Importing Developing Countries (NFIDCs) 0.02 LSU/ha
- Small Island Developing States (SIDS) 0.01 LSU/ha
- Least Developed Countries (LDCs) 0.01 LSU/ha
- Southern Europe 0.01 LSU/ha
- South America 0 LSU/ha
- Oceania 0 LSU/ha
- Northern Africa 0 LSU/ha
About this data
The Livestock Patterns domain of FAOSTAT contains data on livestock numbers, shares of major livestock species and densities of livestock units in the agricultural land area. Values are calculated using Livestock Units (LSU), which facilitate aggregating information for different livestock types. Data are available by country, with global coverage, for the period 1961 to the most recent year available with annual updates. This methodology applies the LSU coefficients reported in the "Guidelines for the preparation of livestock sector reviews" (FAO, 2011). From this publication, LSU coefficients are computed by livestock type and by country. The reference unit used for the calculation of livestock units (=1 LSU) is the grazing equivalent of one adult dairy cow producing 3000 kg of milk annually, fed without additional concentrated foodstuffs. FAOSTAT agri-environmental indicators on livestock patterns closely follow the structure of the indicators in EUROSTAT.