Dimension 4.3: Geospatial Data in Venezuela
Venezuela: Dimension 4.3: Geospatial Data was 0.021 in 2023. ▼ Falling
Dimension 4.3: Geospatial Data in Venezuela, 2015–2023
Source: Statistical Performance Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/statistical-performance-indicators).
Analysis
The most recent figure for dimension 4.3: geospatial data in Venezuela is 0.021, measured in 2023. That is the lowest value across all 9 years on record.
Compared with earlier readings it is down 89.6% over ten years.
Over the whole period, dimension 4.3: geospatial data in Venezuela peaked at 0.258 in 2016 and was at its lowest, 0.021, in 2022.
Venezuela ranks 174th of 180 countries on this measure, in the bottom quarter.
Dimension 4.3: Geospatial Data in Venezuela, year by year
| Year | Value | Change |
|---|---|---|
| 2015 | 0.201 | — |
| 2016 | 0.258 | +28.4% |
| 2017 | 0.164 | -36.4% |
| 2018 | 0.164 | +0.0% |
| 2019 | 0.164 | +0.0% |
| 2020 | 0.164 | +0.0% |
| 2021 | 0.164 | +0.0% |
| 2022 | 0.021 | -87.2% |
| 2023 | 0.021 | +0.0% |
Venezuela compared with similar countries
- Venezuela's 0.021 is below the median for lower middle income countries, which is 0.268, 8% of the median. (46 countries reporting)
- Venezuela's 0.021 is below the median for Latin America & Caribbean, which is 0.253, 8% of the median. (28 countries reporting)
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 0.1902 | 0.164 | 0.258 | 5 |
| 2020s | 0.0925 | 0.021 | 0.164 | 4 |
Countries ranked near Venezuela
- 174 Guyana 0.021 compare
- 174 Montenegro 0.021 compare
- 177 Haiti 0
- 177 Luxembourg 0 compare
- 177 South Sudan 0 compare
- 177 Turkmenistan 0 compare
More reference data data for Venezuela
- Emission Totals - Indirect emissions (N2O) - Crop Residues 0.2667 (2050)
- Emission Totals - Indirect emissions (N2O) - Agricultural Soils 10.29 (2050)
- Emission Totals - Indirect emissions (N2O) - Manure left on Pasture 6.85 (2050)
- Emission Totals - Indirect emissions (N2O) - IPCC Agriculture 10.29 (2050)
- Emission Totals - Indirect emissions (N2O) - Manure applied to Soils 1.34 (2050)
- Emission Totals - Emissions (CO2eq) (AR5) - Crop Residues 384.74 (2050)
- Emission Totals - Emissions (CO2eq) from N2O (AR5) - Manure applied 1,190 (2050)
- Emission Totals - Emissions (CO2eq) from N2O (AR5) - IPCC Agriculture 14,168 (2050)
- Emission Totals - Direct emissions (N2O) - Manure left on Pasture 31.16 (2050)
- Emission Totals - Emissions (N2O) - Agricultural Soils 51.45 (2050)
Frequently asked questions
- What is dimension 4.3: geospatial data in Venezuela?
- Dimension 4.3: geospatial data in Venezuela was 0.021 in 2023, according to Statistical Performance Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/statistical-performance-indicators).
- What is the highest dimension 4.3: geospatial data recorded in Venezuela?
- The highest recorded value was 0.258 in 2016.
- What is the lowest dimension 4.3: geospatial data recorded in Venezuela?
- The lowest recorded value was 0.021 in 2022.
- How does Venezuela rank for dimension 4.3: geospatial data?
- Venezuela ranks 174th out of 180 countries with data for 2023.
- Is dimension 4.3: geospatial data rising or falling in Venezuela?
- Over the last ten years it is down 89.6%. The long-run trend across the full record is falling.
- Where does this Venezuela data come from?
- The figures come from Statistical Performance Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/statistical-performance-indicators), published as part of Dimension 4.3: Geospatial Data. Statizoid updates them automatically from the source API.
Download this data
CSV · JSON — 9 observations, free to reuse under CC BY 4.0 (World Bank Open Data).
About this data
Geospatial data available at 1st Admin Level. We recognize that this data source provides only limited coverage but consider that it does at least provide some indication of the ability of the national statistical system to produce geospatial data. A major research and data collection effort is needed via GGIM to fill in this information, so that a more comprehensive picture of geospatial data capability at the national level can be produced. Until this is done, it we cannot even assess the scale of the data gaps in a comparable way.