Dimension 4.3: Geospatial Data in South Sudan
South Sudan: Dimension 4.3: Geospatial Data was 0 in 2023. ◆ Volatile
Dimension 4.3: Geospatial Data in South Sudan, 2015–2023
Source: Statistical Performance Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/statistical-performance-indicators).
Analysis
In 2023, dimension 4.3: geospatial data in South Sudan stood at 0. That is the lowest value across all 9 years on record.
That represents a change of down 100.0% over ten years.
Over the whole period, dimension 4.3: geospatial data in South Sudan peaked at 0.276 in 2015 and was at its lowest, 0, in 2022.
South Sudan ranks 177th of 180 countries on this measure, in the bottom quarter.
Dimension 4.3: Geospatial Data in South Sudan, year by year
| Year | Value | Change |
|---|---|---|
| 2015 | 0.276 | — |
| 2016 | 0.276 | +0.0% |
| 2017 | 0.181 | -34.4% |
| 2018 | 0.231 | +27.6% |
| 2019 | 0.231 | +0.0% |
| 2020 | 0.063 | -72.7% |
| 2021 | 0.063 | +0.0% |
| 2022 | 0 | -100.0% |
| 2023 | 0 | — |
South Sudan compared with similar countries
- South Sudan's 0 is below the median for low income countries, which is 0.247. (22 countries reporting)
- South Sudan's 0 is below the median for Sub-Saharan Africa, which is 0.253. (44 countries reporting)
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 0.239 | 0.181 | 0.276 | 5 |
| 2020s | 0.0315 | 0 | 0.063 | 4 |
Countries ranked near South Sudan
- 174 Guyana 0.021 compare
- 174 Montenegro 0.021 compare
- 174 Venezuela 0.021 compare
- 177 Haiti 0
- 177 Luxembourg 0 compare
- 177 Turkmenistan 0 compare
More reference data data for South Sudan
- Emission Totals - Indirect emissions (N2O) - Manure left on Pasture 7 (2019)
- Emission Totals - Indirect emissions (N2O) - Manure applied to Soils 0.3667 (2019)
- Emission Totals - Indirect emissions (N2O) - Agricultural Soils 7.41 (2019)
- Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Enteric 19,422 (2019)
- Emission Totals - Emissions (CO2eq) (AR5) - Manure Management 684.53 (2019)
- Emission Totals - Emissions (CO2eq) (AR5) - Manure applied to Soils 325.82 (2019)
- Emission Totals - Emissions (CO2eq) (AR5) - Manure left on Pasture 8,797 (2019)
- Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Burning - Crop 6.36 (2019)
- Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Manure Management 577.67 (2019)
- Emission Totals - Emissions (CH4) - IPCC Agriculture 944.75 (2019)
Frequently asked questions
- What is dimension 4.3: geospatial data in South Sudan?
- Dimension 4.3: geospatial data in South Sudan was 0 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 South Sudan?
- The highest recorded value was 0.276 in 2015.
- What is the lowest dimension 4.3: geospatial data recorded in South Sudan?
- The lowest recorded value was 0 in 2022.
- How does South Sudan rank for dimension 4.3: geospatial data?
- South Sudan ranks 177th out of 180 countries with data for 2023.
- Is dimension 4.3: geospatial data rising or falling in South Sudan?
- Over the last ten years it is down 100.0%. The long-run trend across the full record is volatile.
- Where does this South Sudan 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.