Dimension 4.3: Geospatial Data in Papua New Guinea
Papua New Guinea: Dimension 4.3: Geospatial Data was 0.238 in 2023. ▼ Falling
Dimension 4.3: Geospatial Data in Papua New Guinea, 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 Papua New Guinea stood at 0.238.
That represents a change of up 11.7% over ten years.
Over the whole period, dimension 4.3: geospatial data in Papua New Guinea peaked at 0.279 in 2016 and was at its lowest, 0.093, in 2020.
That places Papua New Guinea 119th out of 180 countries with data for 2023, putting it in the middle of the range.
Dimension 4.3: Geospatial Data in Papua New Guinea, year by year
| Year | Value | Change |
|---|---|---|
| 2015 | 0.213 | — |
| 2016 | 0.279 | +31.0% |
| 2017 | 0.22 | -21.1% |
| 2018 | 0.198 | -10.0% |
| 2019 | 0.198 | +0.0% |
| 2020 | 0.093 | -53.0% |
| 2021 | 0.093 | +0.0% |
| 2022 | 0.238 | +155.9% |
| 2023 | 0.238 | +0.0% |
Papua New Guinea compared with similar countries
- Papua New Guinea's 0.238 is below the median for lower middle income countries, which is 0.268, 89% of the median. (46 countries reporting)
- Papua New Guinea's 0.238 is below the median for East Asia & Pacific, which is 0.3355, 71% of the median. (26 countries reporting)
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 0.2216 | 0.198 | 0.279 | 5 |
| 2020s | 0.1655 | 0.093 | 0.238 | 4 |
Countries ranked near Papua New Guinea
- 116 Angola 0.241 compare
- 116 Belize 0.241 compare
- 116 Democratic Republic of Congo 0.241 compare
- 120 Saudi Arabia 0.229 compare
- 121 Belgium 0.223 compare
- 122 Lebanon 0.22 compare
- 122 Madagascar 0.22 compare
- 122 Mauritania 0.22 compare
- 122 Moldova 0.22 compare
- 122 Namibia 0.22 compare
More reference data data for Papua New Guinea
- Emission Totals - Indirect emissions (N2O) - Manure applied to Soils 0.2042 (2050)
- Emission Totals - Indirect emissions (N2O) - Manure left on Pasture 0.0498 (2050)
- Emission Totals - Indirect emissions (N2O) - IPCC Agriculture 0.3515 (2050)
- Emission Totals - Indirect emissions (N2O) - Crop Residues 0.0007 (2050)
- Emission Totals - Indirect emissions (N2O) - Agricultural Soils 0.3515 (2050)
- Emission Totals - Emissions (N2O) - Manure applied to Soils 0.6846 (2050)
- Emission Totals - Emissions (N2O) - Manure Management 0.5295 (2050)
- Emission Totals - Emissions (N2O) - Manure left on Pasture 0.2811 (2050)
- Emission Totals - Emissions (N2O) - IPCC Agriculture 1.89 (2050)
- Emission Totals - Emissions (N2O) - Crop Residues 0.0038 (2050)
Frequently asked questions
- What is dimension 4.3: geospatial data in Papua New Guinea?
- Dimension 4.3: geospatial data in Papua New Guinea was 0.238 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 Papua New Guinea?
- The highest recorded value was 0.279 in 2016.
- What is the lowest dimension 4.3: geospatial data recorded in Papua New Guinea?
- The lowest recorded value was 0.093 in 2020.
- How does Papua New Guinea rank for dimension 4.3: geospatial data?
- Papua New Guinea ranks 119th out of 180 countries with data for 2023.
- Is dimension 4.3: geospatial data rising or falling in Papua New Guinea?
- Over the last ten years it is up 11.7%. The long-run trend across the full record is falling.
- Where does this Papua New Guinea 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.