Geospatial science
Almost every risk question has a where: where hazards strike, where people and assets are, where services can be reached and where dependencies run. Geospatial science brings Earth observation, geographic information systems (GIS) and spatial statistics together to answer it. The Global Centre for Risk and Innovation (GCRI) uses geospatial methods with care for their limitations: coordinate systems, scale, data gaps and the way boundaries can change a result. This page is part of science and methods.
- 01In briefThe short answer
- 02MethodsThe geospatial toolkit
- 03LimitationsWhere geospatial results can mislead
- 04PracticeHow GCRI keeps spatial work checkable
- 05Key termsTerms used on this page
- 06RelatedConnected pages
GCRI · Institution · service level R0
The short answer.
Geospatial science brings Earth observation, geographic information systems and spatial statistics together to answer where hazards strike, where people and assets are, where services can be reached and where dependencies run. GCRI uses it with care for coordinate systems, scale, data gaps and the ease with which maps persuade.
Land surface in the Colorado River Basin.
Surface classes an Earth-observation programme reads: ranges, deserts, glaciers, lakes and reefs, shown for the Colorado River Basin as an example geography for this subject.
The geospatial toolkit.
Geospatial work combines observation, mapping and statistics. Each method has its own assumptions, and results are reported with the choices made.
Mapping and overlay
Combining hazard, exposure and service layers with geospatial information systems.
Spatial patterns
Clustering, interpolation and spatial dependence with spatial statistics and geostatistics.
Networks and reach
Travel time to hospitals, shelters and markets over real road and transport networks.
Where geospatial results can mislead.
Maps persuade easily, which is why their limits are stated beside them.
- Scale and aggregation: the same data grouped into different areas can show different patterns
- Boundaries: administrative units rarely match watersheds, grids or labour markets
- Distance is not access: straight-line buffers can misstate how far people really are from services
- Data gaps: informal settlements, rural areas and recent change are often missing from base maps
- Interpolation: surfaces built from sparse samples carry uncertainty that must be shown
How GCRI keeps spatial work checkable.
- 01
State the coordinate reference system
So layers align and distances are correct.
- 02
Test sensitivity to scale
Results are checked at more than one level of aggregation.
- 03
Validate spatially
Models are tested on places they were not trained on.
- 04
Respect sensitivity
Restricted infrastructure locations and protected community sites are never published.
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 |
|---|---|
| Coordinate reference system | The definition that ties coordinates to locations on Earth, catalogued with EPSG codes. |
| Modifiable areal unit problem | The change in statistical results that comes from how areas are drawn and aggregated. |
| Spatial autocorrelation | The tendency of nearby places to have similar values, which statistical tests must account for. |
| Geospatial information | Data that describes the location and attributes of features on the Earth, the basis on which the UN Integrated Geospatial Information Framework asks countries to build national systems. |
Questions and answers.
Are GCRI maps official?
How are boundaries shown?
Can I get GIS layers?
Why does scale matter so much?
Can communities contribute local mapping?
Around GCRI.
Start with an enquiry.
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.