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GCRI · Space and Earth Observation

Geospatial governance

Geospatial data on boundaries, addresses, land, buildings and infrastructure underpin government, markets and risk management. National spatial data infrastructures, standards, licensing and rules on privacy and security decide whether that data is available, trusted and reusable. This page sets out how geospatial information is governed, how maturity is assessed, and what evidence serves the mapping agencies and institutions responsible.

01Register

Geospatial governance on the record.

02The question

Geospatial governance: how the risk develops.

Licensing, privacy and data quality. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.

Mechanism

Authoritative data need custodians

Someone must be responsible for each fundamental dataset, such as addresses or cadastres, keeping it current and correct.

Mechanism

Standards make data combine

Common reference frames, formats and catalogues let data from different agencies be overlaid and shared.

Mechanism

Licensing shapes use

Open licences increase reuse; restrictive or unclear licences limit it, even for publicly funded data.

Mechanism

Some data are sensitive

Detailed maps of infrastructure, people or protected sites raise privacy and security concerns that governance must weigh against openness.

03Geography

Earth observation in the Arctic.

Night lights, land cover and population density over the Arctic, from NASA GIBS. Each layer carries its own date.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 3

Earth observation, for this page

About this layer
Evidence
Observed
Source
VIIRS NOAA-20 corrected reflectance (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite image
Newest at build
2026-10-14
Resolution
about 250 m grid
Uncertainty
Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed
Source
VIIRS Black Marble (VNP46A2) (NASA LAADS DAAC)
Provider
NASA LAADS DAAC
Licence
NASA open data
Vintage
daily; Satellite radiance, corrected for moonlight and atmosphere
Newest at build
2026-10-12
Resolution
about 500 m grid
Uncertainty
Satellite night-time radiance for the date shown; lights are a proxy for electricity use and outages, not a measurement of supply or access.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Modelled (latest year GIBS publishes)
Source
MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
Provider
NASA LP DAAC
Licence
NASA open data
Vintage
yearly; Satellite classification; latest year GIBS publishes
Newest at build
2024-01-01
Resolution
about 500 m grid
Uncertainty
Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Estimated
Source
Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
Provider
NASA SEDAC (CIESIN, Columbia University)
Licence
CC BY 4.0
Vintage
null; Census-based estimate, static (2020)
Resolution
about 1 km grid
Uncertainty
Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed (clouds leave gaps)
Source
MODIS Terra EVI (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite index; clouds leave gaps
Newest at build
2026-10-13
Resolution
about 250 m grid
Uncertainty
Satellite vegetation index for the 8 days to the date shown, a habitat condition indicator; not a measure of species or biodiversity.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed (clouds leave gaps)
Source
MODIS Terra NDVI (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite index; clouds leave gaps
Newest at build
2026-10-13
Resolution
about 250 m grid
Uncertainty
Satellite greenness index over the 8 days to the date shown; an indicator of crop and pasture condition, not a yield estimate or a food security warning.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map

Latest available

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth

Loading the latest NASA imagery.

Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.

Earth observation, framed on the Arctic.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · U.S. Geological Survey · NASA JPL OPERA DIST-ALERTSources and licences

  • We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
  • ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
  • Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
  • © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
  • Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
  • Live: NASA EONET Events are indicative, not authority warnings.
  • Live: U.S. Geological Survey Events are indicative, not authority warnings.
  • Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
  • NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
  • Past year, daily temperature and sunshine (NASA POWER): These data were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program..
  • Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
  • Optional layers (11 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.

Layers and dates

  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
  • Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • Enhanced vegetation index, rolling 8 days: MODIS Terra EVI, NASA LANCE · 13 Oct 2026
  • Vegetation greenness (NDVI), rolling 8 days: MODIS Terra NDVI, NASA LANCE · 13 Oct 2026

04Across the domains

Geospatial governance decides who can use maps in every domain.

05Monitor

Space safety console.

The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.

Space safety console

Geospatial governance · Orbit shell 550 km · Week 23

Conjunction above thresholdGCRI · Space and Earth Observation

Conjunctions

CJ-3383SAT-3 vs debris2440.00040Monitor
CJ-8940SAT-1 vs SAT-x4820.000009None
CJ-0105SAT-4 vs debris460.0007Manoeuvre

Manoeuvre plan

Delta-v
0.07 m/s
Window
T-13 h
Fuel left
45 pct
Decision
operator
Space safety console: the screen’s structure, terms and states for Geospatial governance.Example names and illustrative values; a design, not a record or a live system.
06Indicators

What is measured, and how well.

Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.

IndicatorUnitCadenceSource typeLabel
Fundamental geospatial data themes availablecount of themesper assessmentUN-GGIM and national assessmentsPublished statistics
Geodetic reference frame adoptionstatusper assessmentNational geodetic agency recordsPublished statistics
Datasets with open licencespercent of national geospatial datasetsper assessmentCatalogue analysisOBSERVED
Metadata compliance with standardspercent of datasetsper assessmentCatalogue analysisOBSERVED
Address coveragepercent of dwellings with a registered addressper assessmentAddress registersPublished statistics
Cadastral coveragepercent of parcels registeredper assessmentLand administration recordsPublished statistics
07Simulator

Stocks, flows, delays and a tipping threshold.

Two stocks, pressure and adaptive capacity, joined by a reinforcing growth loop, a delayed balancing response and damage when pressure outruns capacity; past the threshold the system can tip. Teaching model with stated illustrative values, not a prediction. The map on this page shows The Arctic; the model itself is not tied to a place.

Controls

Growth of pressure
6.0% a year
Efficacy of capacity in reducing pressure
4.0% a year
Investment response to perceived pressure
20%
Perception delay
4.0 years
Tipping threshold of pressure
60 index
Amplification past the threshold
2.0 times
Years simulated
50 years

Readouts

Peak pressure
113 index
Capacity at the end
186 index
Years over the threshold
15.8 years
Numbers, methods and sources
YearPressureCapacityPerceived
020.050.020.0
423.344.921.2
827.242.224.0
1231.742.327.7
1636.845.532.2
2042.351.537.2
2447.960.342.6
2853.271.348.0
3257.884.353.1
3666.498.458.4
4082.7115.969.7
4497.8139.783.8
48109.1169.497.3

Methods

  1. System dynamics Forrester (1961), Industrial Dynamics, MIT Press; Sterman (2000), Business Dynamics
  2. Critical transitions and tipping points Scheffer and others (2009), Early-warning signals for critical transitions, Nature 461
  3. Causal loop diagram Sterman (2000), Business Dynamics, McGraw-Hill
  4. Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
  5. One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley

Data

No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme’s own evidence.

Stocks, flows, delays and a tipping threshold. Illustrative teaching model: it runs on the values set by the controls, not on measured data. Methods: System dynamics (Forrester (1961), Industrial Dynamics, MIT Press; Sterman (2000), Business Dynamics); Critical transitions and tipping points (Scheffer and others (2009), Early-warning signals for critical transitions, Nature 461); Causal loop diagram (Sterman (2000), Business Dynamics, McGraw-Hill).
08Sources

Where the evidence comes from.

Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.

SourceWhat it givesLicence class
UN-GGIM Integrated Geospatial Information Framework documentsFramework and implementation guidePublic, UN terms of use
UN-GGIM global fundamental geospatial data themesThemes considered fundamental for national dataPublic, UN terms of use
OGC standardsInteroperability standards for geospatial data and servicesPublic, OGC terms
National mapping agency cataloguesAvailable datasets and licencesLicence per agency
World Bank and FIG land administration studiesCadastre and land registration statusPublic, terms per publisher
09Twin and cascade simulator

Model geospatial governance as a system. Run the cascade.

Assembled from the Nexus Standards area profile Climate risk standards: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.

Hazards

  • Sea-level rise
  • Coastal flood (set off downstream)
  • Storm surge (set off downstream)
  • High-tide flooding (set off downstream)
  • Coastal erosion (set off downstream)
  • Saltwater intrusion (set off downstream)
  • Estuary flood (set off downstream)
  • Coastal habitat squeeze (set off downstream)
  • Wetland loss (set off downstream)
  • Mangrove loss (set off downstream)
  • Groundwater flood (set off downstream)
  • Climate-driven migration and relocation (set off downstream)
  • Mass displacement (set off downstream)

Controls

  • NS-0 Constitution and principles
  • NS-1 The UNI and the artefact catalogue (grammar v0.2: domain, sector, region and environment segments)
  • NS-3 Risk record UNIs (grammar, legacy crosswalk, allocation authority)
  • NS-3b Dataset and product metadata profile (STAC, DCAT, PROV-O)
  • NS-9 Contextual UNIs (deployments, instances, programme instances)
  • NS-11 Verification and monitoring (evidence, attestations, zero-trust conformance observation)
  • NS-14 Conformance and crosswalk to external standards
  • NRS-H65 Hazard family: Planetary boundary transgressions (NHS-1 planet.boundary)
  • NRS-H62 Hazard family: Compound and multi-hazard events (NHS-1 sys.compound)
  • NRS-H71 Hazard family: Deep-time and cosmic catastrophes (NHS-1 planet.deep-time)
  • NRS-H79 Hazard family: Mental health crises (NHS-1 health.mental)
  • NRS-H75 Hazard family: Climate-sensitive illness (NHS-1 health.climate-sensitive)
  • NRS-H7 Hazard family: Large-scale circulation anomalies (NHS-1 atmo.climate-mode)

Observation

  • ERA5 reanalysis (Copernicus Climate Data Store) (listed for reference)
  • CMIP6 climate projections (Copernicus Climate Data Store) (listed for reference)
  • NGFS Scenario Explorer (listed for reference)
  • INFORM Risk Index (listed for reference)
  • Number of deaths, missing persons and directly affected persons attributed to disasters per 100,000 population
  • Total greenhouse gas emissions per year
  • Direct economic loss attributed to disasters in relation to global GDP

Example geography

  • Pacific Island states: 150 hexagonal cells
  • Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
  • Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
  • Rain rate, last half hour (IMERG), NASA GIBS
  • Vegetation disturbance alerts, 30 m (OPERA DIST-ALERT), NASA GIBS
10Decisions

Who decides, and what the evidence serves.

Space and Earth Observation prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.

Who decidesThe questionEvidence this page serves
National mapping and cadastral agenciesWhich datasets to prioritise and how to publish themMaturity reviews; gap analyses
GovernmentsHow to fund and govern national geospatial informationFramework evidence
Security and privacy authoritiesWhich geospatial data need restrictionsSensitive data evidence

Outputs this topic produces

  • Geospatial data infrastructure maturity reviews
  • Licence and metadata audits
  • Fundamental data gap analyses
  • Evidence notes on sensitive data policy
11Methods and evidence

How geospatial governance is modelled, measured and tested.

The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.

Earth observation chain

How a satellite or sensor record becomes evidence on geospatial governance, and where each step adds uncertainty.

  1. 01 · Acquireorbit, sensor and revisitUncertainty: gaps from cloud and orbit
  2. 02 · Calibrateradiometric and geometricUncertainty: sensor drift
  3. 03 · Correctatmosphere and terrainUncertainty: aerosol and slope assumptions
  4. 04 · Retrieve or classifythe variable or the classUncertainty: model and training error
  5. 05 · Validateagainst ground truthUncertainty: sample design and size
  6. 06 · Publishwith error bars and lineageUncertainty: stated, never hidden
Processing chain in the CEOS Analysis Ready Data sense; each step records its uncertainty before a figure is drawn. A generic structure, not results.
FAIR guiding principles · GO FAIR and FORCE11W3C PROV · World Wide Web ConsortiumGuidance on consistent treatment of uncertainties · IPCCCEOS Analysis Ready Data · Committee on Earth Observation Satellites
12Core questions

What experts ask.

Specialists in geospatial governance work on questions of rights, rules and quality.

  • How do licensing regimes govern satellite operation, data distribution and resolution?
  • What privacy risks arise from fine-resolution and frequently repeated imagery, and how can they be limited?
  • How should data quality, provenance and uncertainty be documented for decision use?
  • How can open data be balanced with security, commercial and community interests?
  • What evidence standards apply when satellite data is used in disputes or enforcement?
13Mechanisms and drivers

Capability outpaces rules.

Commercial constellations now offer imagery at resolutions and revisit frequencies once limited to a few governments. Combining imagery with other data, such as mobile location or social media, can reveal patterns of individual behaviour. Licensing regimes, privacy law and data-protection rules were mostly written before these capabilities existed and vary between jurisdictions.

Quality is a governance question too. Products are reused far from their original purpose, often without their validation or licence conditions. Open data policies have greatly expanded use, but openness without documentation can spread errors. Communities whose lands are mapped may have their own views on how such data is used, overlapping with the principles of data sovereignty.

14Methods and data

How the evidence is built, and where it stops.

  1. 01

    Legal and policy analysis

    Comparing licensing, privacy and data law across jurisdictions. Rules change quickly and differ in practice from text.

  2. 02

    Metadata and provenance standards

    Documenting source, processing and accuracy with geospatial information systems standards. Metadata is often incomplete.

  3. 03

    Privacy risk assessment

    Evaluating re-identification risk of imagery and derived data. Combined datasets create risks that single datasets do not.

  4. 04

    Quality frameworks

    Assessing fitness for purpose using statistical validation. Different uses need different standards.

16Where this page’s references

Where this page’s references lead.

The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.

17Questions

Questions and answers.

What is a spatial data infrastructure?
The policies, technology, standards and people that let geospatial data be found, shared and used across organisations.
What is the IGIF?
The Integrated Geospatial Information Framework, developed by UN-GGIM with the World Bank, to help countries strengthen national geospatial information management.
Why are fundamental datasets important?
Because themes such as addresses, boundaries, elevation and transport networks are the base on which other data and services are built.
Can satellites identify individuals?
Current civil satellites generally cannot identify people directly, but fine-resolution imagery combined with other data can reveal information about individuals and homes. That is why privacy safeguards matter.
Is open satellite data free of conditions?
Not always. Open data often carries licence conditions such as attribution. Documentation of quality and limits should travel with the data.
Does the platform set licensing rules?
No. GCRI does not regulate. The platform publishes analysis and evidence that authorities and providers can use.
ReportsContribute

Contribute evidence from this page.

Reports is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

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