Montenegro vs South Sudan: Dimension 4.3: Geospatial Data

Montenegro
0.021
in 2023
South Sudan
0
in 2023
Montenegro rank
171st
South Sudan rank
174th

Dimension 4.3: Geospatial Data over time

  • Montenegro
  • South Sudan
00.10.20.3201520192023

How they compare

Montenegro currently reports 0.021 against 0 in South Sudan, a difference of 0.021.

The two have swapped places 1 time across 9 shared years of data; in 2015 it was South Sudan ahead.

Montenegro ranks 171st and South Sudan ranks 174th of 177 countries.

South Sudan has averaged higher in every one of the 2 decades both report.

Head to head by decade

Decade Montenegro South Sudan Difference Ahead
2010s 0.0902 0.239 0.1488 South Sudan
2020s 0.021 0.0315 0.0105 South Sudan

Averages of every year both report within each decade.

Frequently asked questions

Which has higher dimension 4.3: geospatial data, Montenegro or South Sudan?
Montenegro, at 0.021 against 0 in South Sudan as of 2023.
What is the difference in dimension 4.3: geospatial data between Montenegro and South Sudan?
0.021, with Montenegro ahead.
How many years of comparable data are there for Montenegro and South Sudan?
9 years are reported by both, from 2015 to 2023.
How do Montenegro and South Sudan rank globally for dimension 4.3: geospatial data?
Montenegro ranks 171st and South Sudan ranks 174th of 177 countries.
Where does this data come from?
Statistical Performance Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/statistical-performance-indicators), published as Dimension 4.3: Geospatial Data. Statizoid refreshes it automatically from the source and publishes the full history for both places.

Individual pages

About this data

Indicator
Dimension 4.3: Geospatial Data
Source
Statistical Performance Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/statistical-performance-indicators)
Licence
CC BY 4.0 (World Bank Open Data)
Coverage
179 places, 1,551 data points, 2015–2023
Last refreshed

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.