Dimension 4.3: Geospatial Data in Latvia

Latvia: Dimension 4.3: Geospatial Data was 0.084 in 2023. ◆ Volatile

Latest (2023)
0.084
Change on year
unchanged
World rank
160th
of 180 countries
All-time high
0.357
in 2016
All-time low
0.022
in 2017
Years of data
8
2016–2023

Dimension 4.3: Geospatial Data in Latvia, 2016–2023

00.10.20.30.42016201920232016: 0.3572017: 0.0222018: 0.1212019: 0.1212020: 0.1052021: 0.1052022: 0.0842023: 0.084

Source: Statistical Performance Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/statistical-performance-indicators).

Analysis

Latvia recorded 0.084 for dimension 4.3: geospatial data in 2023.

That represents a change of down 76.5% over ten years.

Latvia ranks 160th of 180 countries on this measure, in the bottom quarter.

Dimension 4.3: Geospatial Data in Latvia, year by year

Annual values for Dimension 4.3: Geospatial Data in Latvia, 2016 to 2023.
Year Value Change
2016 0.357 —
2017 0.022 -93.8%
2018 0.121 +450.0%
2019 0.121 +0.0%
2020 0.105 -13.2%
2021 0.105 +0.0%
2022 0.084 -20.0%
2023 0.084 +0.0%

Latvia compared with similar countries

  • Latvia's 0.084 is below the median for high income countries, which is 0.334, 25% of the median. (57 countries reporting)
  • Latvia's 0.084 is below the median for Europe & Central Asia, which is 0.298, 28% of the median. (50 countries reporting)

Averages by decade

DecadeAverage LowestHighest Years
2010s 0.1552 0.022 0.357 4
2020s 0.0945 0.084 0.105 4

Countries ranked near Latvia

  1. 158 Turkey 0.104 compare
  2. 158 United Kingdom 0.104 compare
  3. 160 Guinea-Bissau 0.084 compare
  4. 160 Tajikistan 0.084 compare
  5. 163 Cyprus 0.072 compare
  6. 163 Eswatini 0.072 compare
  7. 163 Libya 0.072 compare

See the full ranking of 180 places →

More reference data data for Latvia

All data for Latvia →

Frequently asked questions

What is dimension 4.3: geospatial data in Latvia?
Dimension 4.3: geospatial data in Latvia was 0.084 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 Latvia?
The highest recorded value was 0.357 in 2016.
What is the lowest dimension 4.3: geospatial data recorded in Latvia?
The lowest recorded value was 0.022 in 2017.
How does Latvia rank for dimension 4.3: geospatial data?
Latvia ranks 160th out of 180 countries with data for 2023.
Is dimension 4.3: geospatial data rising or falling in Latvia?
Over the last ten years it is down 76.5%. The long-run trend across the full record is volatile.
Where does this Latvia 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.

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CSV · JSON — 8 observations, free to reuse under CC BY 4.0 (World Bank Open Data).

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Dimension 4.3: Geospatial Data in Latvia. Statizoid, drawing on Statistical Performance Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/statistical-performance-indicators). Retrieved 24 September 2026, from https://reference.statizoid.com/stat/dimension-4-3-geospatial-data/latvia/

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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
180 places, 1,560 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.