Long-run burned-area and MODIS-context period.
Ghana Fire Observatory
Methodology
How spatial units, time periods, satellite observations and data-quality controls are structured for transparent fire analysis
Scope
A concise account of the analytical framework
The methodology is organised around three requirements: a stable spatial framework, explicit temporal support and honest interpretation of satellite products. This page describes the analytical design.
Spatial framework
National, agro-climatic-zone and district reporting
The district framework contains 260 harmonised units. Each district is assigned to the agro-climatic zone with which it has the greatest spatial overlap, providing a stable nested structure for national, zone and district analysis.
| Zone | Code | Districts |
|---|---|---|
| Sudan Savannah | SS | 20 |
| Guinea Savannah | GS | 45 |
| Transition | TZ | 27 |
| Forest | FZ | 110 |
| Coastal | CZ | 58 |
| Total | 260 | |
- Define unitsEstablish the national district universe and zone geometries.
- Measure overlapCalculate each district’s spatial overlap with the five zones.
- Assign contextAllocate each district to the zone with the greatest overlap.
- Keep stable identifiersUse the same district–zone relationship across the monthly panel.
Temporal framework
A complete monthly spine with product-specific support
The panel spans January 2001 to December 2024, giving 288 monthly positions for every district and zone. Product values are populated only where the source and analytical design support them.
Comparison window used for MODIS–VIIRS mismatch analysis; January 2012 is excluded.
Full-calendar-year summaries for overlap-era analyses.
Structural missingness: months outside a product’s valid support period remain explicitly unavailable. They are not converted to zero, because zero means a supported observation with no detected event.
Sensor roles
Fire impact and fire activity are analysed separately
MODIS MCD64A1 burned area
Mapped burned area is used to characterise the land surface affected by fire. Monthly metrics include burned area, burned-pixel counts and normalised burned-area measures where valid denominators are available.
MODIS and VIIRS active fire
Thermal detections are used to characterise observed fire activity. Metrics include detection counts, active days and fire-radiative-power summaries within the appropriate support periods.
Agreement between products is informative, but disagreement is also scientifically meaningful. Product resolution, detection opportunity, cloud and smoke effects, overpass timing and the physical distinction between activity and impact can all contribute to mismatch.
Analysis
Methods used for long-run and overlap-era assessment
Methods are applied only where their assumptions and product support are appropriate.
Seasonality
Monthly climatologies and dry- versus wet-season summaries characterise recurring annual fire patterns.
Trend analysis
Mann–Kendall tests and Sen’s slope estimates assess monotonic change without assuming normally distributed observations.
Sensor mismatch states
Overlap-era unit-months are classified into both-zero, active-fire-only, burned-area-only and both-positive states.
Association
Spearman rank correlation evaluates monotonic association without treating unlike raw sensor counts as equivalent.
Spatial concentration
Hotspot and spatio-temporal clustering methods identify concentrations that depart from the broader background pattern.
Contextual comparison
District profiles are compared with agro-climatic-zone and national baselines to expose local departures.
Data quality
Controls applied before interpretation
Canonical unit–month spine
Every expected district–month and zone–month key is represented once, which makes missing support visible and permits complete key auditing.
Source and support flags
Source-presence, structural-missingness and overlap-support flags preserve the distinction between absent source coverage and valid measurements.
Denominator controls
Normalised measures are calculated only where the relevant land or burnable-area denominator is valid.
Audit and manifest files
Key audits, file manifests, schema records and merge summaries provide an explicit provenance trail for the released panel.
Interpretation limits
Satellite products do not observe every fire, and district aggregation does not represent address-level hazard. The current public panel is suited to fire-regime and comparative analysis; the 30 m susceptibility framework is a separate ongoing study and its results are not included here.