Build a satellite wildfire alert workflow as a candidate-detection and triage system, not as an automatic fire-confirmation or safety service. NASA FIRMS distributes MODIS and VIIRS active-fire and thermal-anomaly data; global near-real-time data are generally available within three hours of observation, while real-time availability is offered for detections in the United States and Canada. That service timing is not an end-to-end delivery guarantee for your own alerts. See the NASA FIRMS service overview.
What a satellite alert can—and cannot—tell you
A FIRMS point means a sensor detected a thermal anomaly at a particular place and observation time. It is a lead to assess, not proof of a wildfire. It can represent other heat sources, including agricultural burning, and a plotted pixel describes an approximate sensor footprint rather than a precise fire boundary. NASA’s FIRMS map disclaimer says: “Do not use for the preservation of life or property. Satellite-derived active fire / thermal anomalies have limited accuracy.”
A missing point is not proof that no fire exists. Cloud, heavy smoke, tree canopy, or a fire that begins and ends between satellite overpasses can prevent detection. Keep both false alerts and missed detections in mind when deciding how much weight to give a feed.
Choose feeds for your coverage area and response time
Compare candidate sources on resolution, observation frequency, distribution latency, geographic coverage, confidence-field meaning, and processing maturity. NASA’s fires overview and product descriptions document complementary sources:
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| Feed | Spatial detail | Timing and availability | Key trade-off |
|---|---|---|---|
| MODIS active-fire products | Approximately 1 km sensor resolution. | FIRMS says global near-real-time data are generally available within three hours of observation. Its MODIS description lists a 1–30 minute ultra/real-time latency range for the United States and Canada. | Coarser footprint than VIIRS. The MODIS confidence field is experimental; interpret it cautiously and do not treat it as a universal probability. |
| VIIRS active-fire products | 375 m active-fire product resolution. | FIRMS near-real-time distribution is generally within three hours globally; real-time availability applies to U.S. and Canada detections. | More responsive to smaller fires than approximately 1 km products, but the pixel is still not a fire perimeter or precise location of every burning point. |
| Geostationary active-fire detections, such as GOES-West in FIRMS | Substantially coarser than MODIS and VIIRS; the cited product description does not state a single comparable pixel dimension. | Repeat observations at sub-hourly intervals can help show developing activity. | FIRMS describes the product as provisional/beta; coarser resolution and possible false detections require corroboration. |
Sources: NASA FIRMS MODIS product description, NASA VIIRS active-fire products, and NASA FIRMS GOES-West product description. Latency figures describe published service or product information, not the performance of an independently built pipeline.
For a global monitoring workflow, plan around the stated near-real-time distribution window. If monitoring in the United States or Canada, check which real-time products are available for the area and sensor you intend to use. A geostationary feed may add more frequent looks, but should complement—not replace—finer-resolution detections and independent context.
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Build the workflow in seven steps
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Define the operating area and responsibility
Specify the geography, coverage hours, intended recipients, and the person or team authorized to review and escalate a candidate. Establish what the workflow is for—such as situational awareness or prioritizing analyst review—and do not use satellite detections alone to make decisions intended to preserve life or property.
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Select and access the feeds
Start with FIRMS MODIS and VIIRS active-fire data. Use the available alert, map, or download/service access path that fits your system; NASA’s FIRMS overview describes these access options. Add a geostationary product only if its more frequent observations are useful for your monitoring purpose and you can account for its provisional status and coarser detail.
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Ingest records with their provenance
For each record, retain the observation or acquisition time in UTC, coordinates, sensor and platform, any confidence field, product or processing version, and the source identifier. Add your own ingestion timestamp as well. Those separate times let you distinguish when the satellite observed an anomaly from when your system received it, and help review delay or later product changes. The MODIS product description documents product fields, while NASA’s 2025 FIRMS Q&A discusses data access and formats.
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Normalize, deduplicate, and cluster
Standardize timestamps and coordinate handling before comparing observations. Deduplicate repeated records, then group nearby detections over a defined time window so repeat observations do not create a separate message for every point. Choose clustering distance and time rules for your region and use case; the NASA sources describe the data and repeated observations but do not prescribe a universal radius or window.
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Rank candidates using multiple signals
Prioritize review using a combination of sensor, confidence field, viewing geometry, persistence across observations, proximity to assets or communities, and independent weather, fire-agency, or field information. Do not interpret the MODIS confidence percentage as a universal probability of fire: NASA describes the field as based on algorithm intermediates and warns that its meaning may vary by region. See the MODIS field description and FIRMS map disclaimer.
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Route alerts with explicit status
Make each alert understandable without requiring the recipient to open a map first. Include the source, sensor, observation time, coordinates or mapped location, and current review status. A useful internal status flow is “satellite detection,” “under review,” “corroborated,” and “closed/false positive.” Assign consequential reports to an accountable human reviewer and provide a route to the relevant local authority when appropriate. Record the outcome so it can inform later tuning.
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Validate and tune locally
Compare detections and non-detections with verified incident records where available. Track false alerts, missed fires, delivery delays, and how often a candidate is corroborated; review results by sensor and geographic context before changing thresholds. NASA’s Fire Alert Notes describes detection limitations, and the product documentation cautions against reading confidence fields as universal accuracy measures.
Design alerts for fast, careful review
Separate what the satellite observed from what a person or another source has established. An alert should be labeled “satellite detection” or “thermal anomaly” until corroborated, and should not assert that a wildfire is confirmed. Include the observation time—not just the message receipt time—because an alert can arrive after the satellite pass and distribution delay.
- Show the sensor and product, observation time in UTC, location, source record, and ingestion time.
- Make the review state visible, including whether corroboration is pending.
- Link or provide access to independent context, such as local fire-agency information or field reports, rather than treating the satellite point as the final authority.
- Keep a record of analyst disposition and escalation so false positives and missed detections can be evaluated.
A clear status and human handoff are workflow design choices, not guarantees provided by FIRMS. The same is true of local clustering rules and ranking thresholds: set and validate them for the coverage area instead of assuming one configuration works everywhere.
Interpret resolution, timing, and confidence together
VIIRS’s 375 m product is more responsive to smaller fires than approximately 1 km products, but neither pixel size should be read as the outline of a fire. More frequent geostationary observations can reveal changes between polar-orbiting observations, while their coarser footprint and provisional status make corroboration important. A confidence value is also product-specific; it cannot remove uncertainty caused by geography, viewing conditions, or the algorithm.
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