Dimension 4.3: Geospatial Data in Madagascar
Madagascar: Dimension 4.3: Geospatial Data was 0.22 in 2023. ◆ Volatile
Dimension 4.3: Geospatial Data in Madagascar, 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 Madagascar stood at 0.22. That is the highest value across all 9 years on record.
The figure is up 115.7% over ten years.
Over the whole period, dimension 4.3: geospatial data in Madagascar peaked at 0.22 in 2022 and was at its lowest, 0, in 2016.
Madagascar ranks 122nd of 180 countries on this measure, in the middle of the range.
Dimension 4.3: Geospatial Data in Madagascar, year by year
| Year | Value | Change |
|---|---|---|
| 2015 | 0.102 | — |
| 2016 | 0 | -100.0% |
| 2017 | 0 | — |
| 2018 | 0.039 | — |
| 2019 | 0.039 | +0.0% |
| 2020 | 0.211 | +441.0% |
| 2021 | 0.211 | +0.0% |
| 2022 | 0.22 | +4.3% |
| 2023 | 0.22 | +0.0% |
Madagascar compared with similar countries
- Madagascar's 0.22 is below the median for low income countries, which is 0.247, 89% of the median. (22 countries reporting)
- Madagascar's 0.22 is below the median for Sub-Saharan Africa, which is 0.253, 87% of the median. (44 countries reporting)
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 0.036 | 0 | 0.102 | 5 |
| 2020s | 0.2155 | 0.211 | 0.22 | 4 |
Countries ranked near Madagascar
- 119 Papua New Guinea 0.238 compare
- 120 Saudi Arabia 0.229 compare
- 121 Belgium 0.223 compare
- 122 Lebanon 0.22 compare
- 122 Mauritania 0.22 compare
- 122 Moldova 0.22 compare
- 122 Namibia 0.22 compare
More reference data data for Madagascar
- Emission Totals - Indirect emissions (N2O) - Manure applied to Soils 0.4459 (2050)
- Emission Totals - Indirect emissions (N2O) - Manure left on Pasture 4.82 (2050)
- Emission Totals - Indirect emissions (N2O) - IPCC Agriculture 5.9 (2050)
- Emission Totals - Indirect emissions (N2O) - Crop Residues 0.4503 (2050)
- Emission Totals - Indirect emissions (N2O) - Agricultural Soils 5.9 (2050)
- Emission Totals - Emissions (N2O) - Manure applied to Soils 1.5 (2050)
- Emission Totals - Emissions (N2O) - Manure Management 1.43 (2050)
- Emission Totals - Emissions (N2O) - Manure left on Pasture 26.56 (2050)
- Emission Totals - Emissions (N2O) - IPCC Agriculture 32.81 (2050)
- Emission Totals - Emissions (N2O) - Crop Residues 2.45 (2050)
Frequently asked questions
- What is dimension 4.3: geospatial data in Madagascar?
- Dimension 4.3: geospatial data in Madagascar was 0.22 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 Madagascar?
- The highest recorded value was 0.22 in 2022.
- What is the lowest dimension 4.3: geospatial data recorded in Madagascar?
- The lowest recorded value was 0 in 2016.
- How does Madagascar rank for dimension 4.3: geospatial data?
- Madagascar ranks 122nd out of 180 countries with data for 2023.
- Is dimension 4.3: geospatial data rising or falling in Madagascar?
- Over the last ten years it is up 115.7%. The long-run trend across the full record is volatile.
- Where does this Madagascar 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.