Spatial statistics and geostatistics
Spatial statistics and geostatistics analyse data that vary across space, accounting for spatial dependence. They estimate values at unsampled locations and test for spatial patterns. Space and Earth Observation stewards this page for the Nexus Consortium.
- 01In briefThe short answer
- 02The methodWhat spatial statistics and geostatistics covers
- 03Reference practiceSpatial statistics supports mapping and small-area estimation
- 04In systemic risk workWhere, with what uncertainty
- 05Applied inPlatforms that apply this method
- 06StewardshipWho maintains this page
- 07Key termsTerms used on this page
GCRI · Institution · service level R0
The short answer.
Spatial statistics and geostatistics analyse data that vary across space, accounting for spatial dependence. Spatial statistics produce continuous hazard and exposure surfaces with uncertainty. In the Nexus Consortium, Space and Earth Observation stewards its canonical page, and 7 other platforms apply it, including Water Nexus and Food Nexus.
Energy demand and corridors in Western Europe.
Where demand concentrates in cities and the rail, road and port corridors that move fuel and equipment, shown for Western Europe as an example geography for this subject.
What spatial statistics and geostatistics covers.
- 01
Core methods
kriging; variogram analysis; spatial autocorrelation tests; point process modelling; spatial regression; hotspot analysis.
- 02
Data and instruments
monitoring station networks; georeferenced surveys; remote sensing products; administrative area statistics; point event records.
- 03
Validation
Predictions are tested using spatial cross-validation that respects dependence. Uncertainty maps are compared with independent observations.
- 04
Limits
Results depend on the scale and zoning of analysis. Sparse or clustered sampling limits prediction in unsampled areas.
- 05
Use in risk decisions
Spatial statistics produce continuous hazard and exposure surfaces with uncertainty. They reveal geographic clustering of risks and vulnerabilities across sectors.
Spatial statistics supports mapping and small-area estimation.
| Reference | What it sets |
|---|---|
| Geostatistics (kriging) | Interpolation with uncertainty |
| Small-area estimation | Subnational estimates from surveys |
| WorldPop and GHSL | Gridded population |
Where, with what uncertainty.
Risk maps interpolate between observations and disaggregate statistics. Spatial statistics provides uncertainty maps alongside estimates, which is essential when targeting resources: a district that looks high-risk may simply be data-poor.
- Publish uncertainty maps with estimates.
- Account for spatial autocorrelation in inference.
- Check gridded population against census.
- Applications on Space and Earth Observation and Food Nexus.
Platforms that apply this method.
Who maintains this page.
Space and Earth Observation stewards spatial statistics and geostatistics: it keeps this description current and reviews how the method is applied across the platforms.
Terms used on this page.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Geocoding | Converting addresses or place descriptions into geographic coordinates that can be matched to map layers. |
| Spatial correlation | The tendency of values at nearby locations to be similar, which concentrates losses. |
| Kriging | A geostatistical interpolation method that predicts values at unmeasured locations from nearby observations, weighted by a model of spatial correlation, and returns an estimation variance. |
| Variogram | A function describing how the difference between two measurements grows with the distance between them, the basis of kriging. |
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.
Where this page leads across the Consortium.
- Spatial statistics for water dataGCRIApplied in Water Nexus.
- Spatial statistics for food securityGCRIApplied in Food Nexus.
- Spatial statistics for biodiversityGCRIApplied in Biodiversity Nexus.
- Spatial statistics for hazardsGCRIApplied in Climate and Hazards.
- Spatial statistics for citiesGCRIApplied in Cities and Built Environment.
- Spatial statistics for EOGCRIApplied in Space and Earth Observation.
- Spatial statistics for social dataGCRIApplied in Society and Human Development.
- Spatial statistics and geostatistics for climate and nature financial riskGRAApplied in Climate and Nature Financial Risk.
Questions and answers.
Why does one institution host every method page?
How do I suggest a correction to a method page?
Around GCRI.
Start with an enquiry.
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