Dimension 4.3: Geospatial Data in Democratic Republic of Congo
Democratic Republic of Congo: Dimension 4.3: Geospatial Data was 0.241 in 2023. ▼ Falling
Dimension 4.3: Geospatial Data in Democratic Republic of Congo, 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 Democratic Republic of Congo is 0.241, measured in 2023.
Compared with earlier readings it is down 12.7% over ten years.
Over the whole period, dimension 4.3: geospatial data in Democratic Republic of Congo peaked at 0.285 in 2016 and was at its lowest, 0.24, in 2017.
Democratic Republic of Congo ranks 116th of 180 countries on this measure, in the middle of the range.
Dimension 4.3: Geospatial Data in Democratic Republic of Congo, year by year
| Year | Value | Change |
|---|---|---|
| 2015 | 0.276 | — |
| 2016 | 0.285 | +3.3% |
| 2017 | 0.24 | -15.8% |
| 2018 | 0.261 | +8.8% |
| 2019 | 0.261 | +0.0% |
| 2020 | 0.262 | +0.4% |
| 2021 | 0.262 | +0.0% |
| 2022 | 0.241 | -8.0% |
| 2023 | 0.241 | +0.0% |
Democratic Republic of Congo compared with similar countries
- Democratic Republic of Congo's 0.241 is below the median for low income countries, which is 0.247, 98% of the median. (22 countries reporting)
- Democratic Republic of Congo's 0.241 is below the median for Sub-Saharan Africa, which is 0.253, 95% of the median. (44 countries reporting)
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 0.2646 | 0.24 | 0.285 | 5 |
| 2020s | 0.2515 | 0.241 | 0.262 | 4 |
Countries ranked near Democratic Republic of Congo
More reference data data for Democratic Republic of Congo
- Emission Totals - Emissions (N2O) - Manure Management 1.44 (2050)
- Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Enteric 3,057 (2050)
- Emission Totals - Emissions (N2O) - Manure left on Pasture 6.66 (2050)
- Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Burning - Crop 235.34 (2050)
- Emission Totals - Emissions (CO2eq) (AR5) - Manure left on Pasture 1,764 (2050)
- Emission Totals - Emissions (N2O) - Crop Residues 1.82 (2050)
- Emission Totals - Emissions (CO2eq) (AR5) - Manure Management 601.15 (2050)
- Emission Totals - Emissions (CH4) - IPCC Agriculture 140.16 (2050)
- Emission Totals - Emissions (N2O) - IPCC Agriculture 11.56 (2050)
- Emission Totals - Emissions (CO2eq) (AR5) - Manure applied to Soils 313.43 (2050)
Frequently asked questions
- What is dimension 4.3: geospatial data in Democratic Republic of Congo?
- Dimension 4.3: geospatial data in Democratic Republic of Congo was 0.241 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 Democratic Republic of Congo?
- The highest recorded value was 0.285 in 2016.
- What is the lowest dimension 4.3: geospatial data recorded in Democratic Republic of Congo?
- The lowest recorded value was 0.24 in 2017.
- How does Democratic Republic of Congo rank for dimension 4.3: geospatial data?
- Democratic Republic of Congo ranks 116th out of 180 countries with data for 2023.
- Is dimension 4.3: geospatial data rising or falling in Democratic Republic of Congo?
- Over the last ten years it is down 12.7%. The long-run trend across the full record is falling.
- Where does this Democratic Republic of Congo 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.