The system has three components: two indices — one daily, one seasonal — and the
satellite detection record that tests them against the ground.
Sources and standards
Index: Van Wagner, C.E. (1987), Development and Structure of the Canadian Forest Fire
Weather Index System, Canadian Forestry Service, Forestry Technical Report 35 — implementation
verified against the official Canadian system package (CFFDRS). Danger classes: EFFIS, European
Commission. Meteorology: Open-Meteo (global models + ERA5 reanalysis), each province's historical
fire zones (FIRMS 2012–2024), with 92 days of spin-up for the drought codes. Hotspots: NASA FIRMS / VIIRS (375 m). Provincial
boundaries: IGN. Validation: 2019–2023 daily series for the Paraná Delta cross-checked against
historical detections. GeoFuego Index (GFI): ONI (NOAA/CPC) × FIRMS detections 2001–2025
(MODIS + VIIRS, intra-sensor anomalies); drought term: DC code (CFFDRS) over ERA5/Open-Meteo
reanalysis 2012→today, across 116 fire zones derived from the FIRMS archive.
Antecedent: Chen, Y. et al. (2011), Forecasting Fire Season Severity in South
America Using Sea Surface Temperature Anomalies, Science 334, 787–791
(doi:10.1126/science.1209472).
Published method
The full GeoFuego Index (GFI) method is published and verifiable:
technical note, frozen calibration (v2.2.0), classification engine byte-identical to production,
derivation and verification scripts, and the manuscript figures
(submitted to Natural Hazards and Earth System Sciences, NHESS).
Prospective registry: every level published since deployment (2026-09-27)
is out of sample and publicly inspectable; the calibration is frozen between seasons.
Another region, another country?
The method is portable: the data sources (NASA FIRMS, ERA5, ONI) are global
and the architecture is not tied to Argentina. For each country or region, its own fire zones are derived
from the local satellite archive and the index is calibrated against its history — the same published
pipeline, with a tailored calibration. The ENSO signal on fire is documented for all of South America
(Chen et al. 2011, Science).
Interested in the system for your country, state or region?
Write to us: [email protected]
This index is a danger signal for prevention —
it is not an official alert and does not replace Argentina's National Fire Management Service
(SNMF) or civil-defense authorities. For an active fire, call 100 (Firefighters) or 911.
GEOFUEGO · satellite monitoring — a product by AgentNEO.
The daily index: Fire Weather Index (FWI)
The FWI (Fire Weather Index) is the meteorological fire-danger index of the Canadian
CFFDRS (Canadian Forest Fire Danger Rating System; Van Wagner, 1987).
It is the de facto international standard: adopted by the European EFFIS system, by the global
GWIS, and part of the same family of meteorological indices with which Argentina's National Fire
Management Service produces the national danger map. It does not detect fire: it quantifies the
moisture state of vegetation fuels and the propagation conditions — that is, the probability of
ignition and the expected fire behaviour given an ignition source.
System structure: fuel moisture codes
The system updates once a day with four meteorological variables observed at
12:00 local time — temperature, relative humidity, wind speed and 24-hour accumulated
precipitation — which drive three fuel moisture codes. Each code models a fuel stratum with a
distinct time constant:
FFMC (Fine Fuel Moisture Code) — fine surface fuels: litter, cured grass, fine
vegetal material. Time constant on the order of 16 hours: it responds to the day's weather and
governs ignition probability. DMC (Duff Moisture Code) — decomposing organic matter in the top
centimetres of the soil. Time constant on the order of 12 days. DC (Drought Code) — deep, compact organic layer. Time constant on the order of
52 days: it integrates the seasonal water deficit, so an isolated rainfall during a prolonged
drought lowers it only slightly.
This structure gives the index memory on three time scales.
The codes combine into two sub-indices — the ISI (Initial Spread Index), which integrates
the FFMC with wind and estimates the initial rate of spread, and the BUI (Buildup Index),
which integrates DMC and DC and estimates the total fuel available — and from both comes the FWI:
a dimensionless magnitude that grows non-linearly with the expected intensity of the fire front.
Computation point: the index is computed with the meteorology of
each province's historical fire zones — the points where the FIRMS 2012–2024 archive
concentrates fire activity (detection-weighted clustering; the same 116 zones of the GeoFuego Index).
The provincial light takes the worst of its zones, not an average: danger is not averaged.
The method is spatially scalable: the same engine can incorporate additional
weather stations or grid points, densifying the index down to locality or property level.
Three-day projection: the map card accompanies the day's value with
a projection: the same computation, fed with forecast meteorology (Open-Meteo). The standing value of
the index is always the observed day's.
Today's data
Loading today's data…
Classification levels
The class thresholds are the official EFFIS thresholds (European Commission) for the FWI,
adopted without modification.
Class
FWI
Interpretation
Low
< 11.2
Sustained ignition unlikely
Moderate
11.2 – 21.3
Ignitions possible; limited spread
High
21.3 – 38
Easy spread in dry fine fuels
Very high
38 – 50
Conditions favour high-intensity fire
Extreme
50 – 70
Range associated with major fires
Very extreme
≥ 70
Exceptional conditions
Validation against fire records
Before scaling the computation nationwide, the implementation was validated in
the Paraná Delta: the daily FWI was reconstructed for 2019–2023 and cross-checked against
7,117 satellite hotspot detections from the same period.
The frequency of days with significant fire activity grows monotonically with FWI class:
3% of days in the Low class, versus 83% in the 50–70 range (Extreme). The three major
summer burning episodes of the period (December 2021, January 2022, January 2023) occurred with
FWI between 36 and 66 — all above the 95th percentile of the local historical series, whose
five-year maximum was 66.3.
The validation also revealed the index's limit. The Delta's fire regime is bimodal:
besides the meteorological summer fires, there is a late-winter mode (July–September) — burning of
frost-cured grassland — that occurs at low FWI (8–16). The days with the most detections in the whole
series (August 2021, August 2022) belong to that regime. This is a documented structural limitation of
the FWI in wetlands: its fuel model, derived from the Canadian boreal forest, does not represent cured
fine biomass that burns over wet soil. Hence the system has two axes: the meteorological index
anticipates the summer regime, and near-real-time satellite detection captures what the index does not
model.
GEOFUEGO applies that same engine — verified against the official CFFDRS
implementation — to the country's 24 jurisdictions, with the computation point described above.
The FWI expresses potential danger; hotspot detections express observed occurrence. They
are complementary magnitudes, not interchangeable ones.
Satellite hotspot detection
The points on the map are thermal anomalies detected by NASA's
VIIRS active-fire product (nominal resolution 375 m). The algorithm compares each
pixel's radiance in the mid-infrared (~4 µm) — the band where flaming combustion at
600–1000 °C emits most intensely — against its surrounding pixels; a sufficient contrast is classified
as a hotspot. Because it operates in the thermal infrared, detection also works at night and through
smoke.
A hotspot is not the same as a confirmed fire. False positives occur through
specular reflection: surfaces such as solar panels or metal roofs can reflect direct sunlight
toward the sensor, and the algorithm labels those cases as low confidence. And there are real
thermal sources that are not fires: a refinery flare, for example, produces recurrent detections at a
fixed position.
Applied treatment: low-confidence detections are discarded; each hotspot is assigned to its
jurisdiction using the official IGN boundaries; and every point keeps its overpass time,
satellite, radiative power and a verification link to NASA's FIRMS viewer. Sources: S-NPP,
NOAA-20 and NOAA-21 satellites (VIIRS sensor, 375 m), with under 3 hours of latency. Night-time
detections are free of solar-reflection false positives, and coincident detection by two
independent satellites constitutes cross-confirmation.
Counting criteria: the national total is the sum of the 24 jurisdictions; the satellite feed
also carries neighbouring countries and border or coastal detections with no assignable jurisdiction,
which are excluded from the counts. A declared methodological difference between the two series: the
historical archive excludes static thermal sources (industrial, volcanic and offshore); the
near-real-time series does not carry that classification — NASA adds it only when reprocessing
the data to science quality, published in the archive with a 2–3 month delay — so the recent
tail runs with a slight positive bias and is retrospectively consolidated with the archive version.
The calendar: the 2012–2025 series comes from the FIRMS archive with a single sensor
(S-NPP), which ensures year-to-year comparability. The 2026·live row integrates three
satellites — greater detection capacity by construction — with January–September completed from the
archive. A continuous series, with no gaps. The colour scale is not proportional to the count: it
applies a power transform (exponent 0.45) to preserve contrast in low-activity months, which a linear
scale would compress against the historical maximum.
Detection limit: a hotspot is a 375 m pixel with a thermal anomaly.
Low-intensity fires, fires under dense cloud cover or between successive overpasses may go undetected.
Absence of detection does not imply absence of fire.
The seasonal index: GeoFuego Index (GFI)
The GeoFuego Index (GFI) is GEOFUEGO's own seasonal index; its public reading is the
Seasonal Fire Risk scale (LOW/MEDIUM/HIGH). It complements the FWI on
the time axis: the FWI quantifies the danger of the day; this index, the seasonal risk,
on a three-level scale — LOW / MEDIUM / HIGH. It combines two measured signals: the phase of
ENSO (El Niño–Southern Oscillation), the planet's leading mode of interannual
climate variability, which modulates South America's precipitation regime and, with it, the
accumulation and curing of vegetation fuel; and the accumulated drought of each province's
fire zones. The direct scientific antecedent is
Chen
et al. (Science, 2011), who proposed forecasting South American fire-season
severity from sea-surface-temperature anomalies; the index carries that approach into an operational
indicator, regionally calibrated with Argentine data.
Index structure: ENSO phase and regional calibration
The input is the ONI (Oceanic Niño Index, NOAA/CPC): the
three-month running mean of the sea-surface-temperature anomaly in the Niño 3.4 region of the
equatorial Pacific. By convention, ONI ≥ +0.5 °C defines an El Niño phase,
ONI ≤ −0.5 °C a La Niña phase, and the range in between a neutral phase.
The calibration crosses 25 seasons of satellite detections (2001–2025, MODIS + VIIRS,
intra-sensor anomalies) with each season's ENSO phase and estimates, region by region, the
severity distribution conditional on the phase. The level expresses where analogous seasons
stood relative to their region's median.
The signal is regional, and the index preserves that structure instead of averaging it: in
the north, the most severe seasons are associated with La Niña; in the center the
relationship inverts — El Niño's precipitation increases the fine biomass that later cures and
burns —; in Patagonia no significant signal is detected and local variability governs. The
index is computed per region and expressed by province.
The drought term is measured over 116 fire zones derived from 13 years of satellite
archive: the places where each province actually burns. Each zone carries its accumulated-drought
index (DC, the drought code of the Canadian system, computed over meteorological reanalysis
2012→today) and its own historical threshold for each month. The rule is direct: if any zone of a
province exceeds its historical 90th percentile of accumulated drought, the provincial risk steps up
one level and the card states it — naming the driver and the zone that triggers it. A danger
notice is not averaged: one dry zone is enough.
Each province's season is defined by its own archive: the level considers the window of the
next four months of the hotspot climatology, with weight decaying forward — the current month's fire
weighs more than the horizon's. When that window is light and the current month contributes less than
8 % of the province's annual fire, the area is out of season and the level is LOW. That is
why in September the Litoral is in full season while Chubut — whose fire concentrates in summer —
rests. Accumulated drought escalates in any state: dry terrain out of season is precisely the early
signal.
The country level aggregates by extent: Argentina steps up one level when zonal
drought reaches two-thirds of the provinces (16 of 24) in the same month — continental-scale
drought, not local episodes. Over the 2012–2024 record that condition occurs about two months per
year and coincided with country fire activity above the median in ~9 of every 10 cases.
Scope: the index is a probabilistic risk factor, estimated over
25 seasons — of which ~6 correspond to La Niña episodes. Its statement is a statistical expectation:
analogous seasons showed higher activity. The day's danger is quantified by the FWI; operational
alerting is the responsibility of official agencies.
Today's data
Loading today's ENSO state…
Classification levels
Three levels per province. The ENSO phase sets the base level according to where analogous
historical seasons stand relative to the regional median; accumulated drought steps it up one level
when any fire zone exceeds its 90th percentile. On the map, each level ships with a one-line
statement declaring the driver — ENSO phase, drought, or both — and the zone that triggers it.
Level
Criterion
Interpretation
Low
No ENSO or drought signal above normal, or outside the area's fire season
Attenuated seasonal expectation
Medium
Within the normal range of the area
Local climatology sets the expectation
High
ENSO phase above the historical median and/or accumulated drought above the 90th percentile of any zone
Maximum seasonal signal; the statement declares the driver and where
Hindcast: the calendar × GFI
The map's calendar includes the × GFI view: for each month since 2012, the level the
system would have shown with the ONI phase current at that time (the latest trimester published by
that month) and the accumulated drought of the fire zones at that month's end, overlaid on the
observed hotspot count. It is an exercise in coherence over the calibration period — the model
is evaluated on the same years it was built with, so it constitutes retrospective fit, not independent
verification. The record since deployment is out of sample: every new season tests the index
prospectively.
Declared limitations
Validation in progress. The hindcast is computed over the same period
the index was calibrated on: it measures internal coherence, and that character is declared. The
independent validation is the prospective record accumulating since deployment, season by
season, in plain sight.
The index adds signals. Accumulated drought raises the level; wet ground leaves it at its
base level. When the La Niña phase raises the risk while drought stays within its normal range, the
card qualifies it: it declares the phase as the only driver, and drought stays out of the statement.
Hydrological amplifiers. Episodes like the Paraná low-water stand — which leaves the
wetland's fuel exposed and continuous — belong to the index's next layer: integrating them with the
corridor's hydrometry is the declared line of work.
Resolution in wetlands. The DC models the forest soil of the
Canadian system, and the meteorology comes from 25 km reanalysis cells. In wetlands, the value works
as a regional drought tendency — a useful approximation, read alongside the satellite detection that
captures what the model does not represent.
