In 2024, there were a total of 64,897 wildland fires recorded in the United States. This represents an increase of roughly 14 percent from the previous year. That year, California was the state with the highest number of wildfires in the United States.

First, we would like to thank the wildland fire advisory group. Their wisdom and guidance helped us build the dataset as it currently exists. This dataset is comprised of two different zip files. Zip File 1: The data within this zip file are composed of two wildland fire datasets. (1) A merged dataset consisting of 40 different wildfire and prescribed fire layers. The original 40 layers were all freely obtained from the internet or provided to the authors free of charge with permission to use them. The merged layers were altered to contain a consistent set of attributes including names, IDs, and dates. This raw merged dataset contains all original polygons many of which are duplicates of the same fire. This dataset also contains all the errors, inconsistencies, and other issues that caused some of the data to be excluded from the combined dataset. Care should be used when working with this dataset as individual records may contain errors that can be more easily identified in the combined dataset. (2) A combined wildland fire polygon dataset composed of both wildfires and prescribed fires ranging in years from mid 1800s to the present that was created by merging and dissolving fire information from 40 different original wildfire datasets to create one of the most comprehensive wildfire datasets available. Attributes describing fires that were reported in the various sources are also merged, including fire names, fire codes, fire IDs, fire dates, fire causes. Zip File 2: The fire polygons were turned into 30 meter rasters representing various summary counts: (a) count of all wildland fires that burned a pixel, (b) count of wildfires that burned a pixel, (c) the first year a wildfire burned a pixel, (d) the most recent year a wildfire burned a pixel, and (e) count of prescribed fires that burned a pixel.

These data were used to examine how post-fire sedimentation might change in western USA watersheds with future fire from the decade of 2001-10 through 2041-50. The data include previously published projections (Hawbaker and Zhu, 2012a, b) of areas burned by future wildfires for several climate change scenarios and general circulation models (GCMs) that we summarized for 471 watersheds of the western USA. The data also include previously published predictions (Miller et al., 2011) of first year post-fire hillslope soil erosion from GeoWEPP that we summarized for 471 watersheds of the western USA. We synthesized these summarized data in order to project sediment yield from future fires for 471 watersheds through the year 2050 at the hydrologic unit 8 (HUC8) scale. The detailed methods, results, and original data sources (i.e.: Hawbaker and Zhu, 2012a, b; Miller et al., 2011) were reported in the manuscript.

Oregon saw the largest area burned by wildfires across the United States in 2024. That year, about 2,232 individual wildfires burned in the northwestern state, ravishing almost 1.89 million acres. Texas followed second, with roughly 1.3 million acres burned due to wildfires that year. Fire season 2021 and California’s wildfire suppression costs As one of the most wildfire-prone states in the country, California spends a significant amount of money on their suppression. Estimates suggest wildfire suppression expenditure in California climbed to 1.2 billion U.S. dollars in the fiscal year ending June 2022. The fiscal year, which includes the summer and fall months of 2021, was among the most devastating fire seasons on record, with that year’s Dixie fire becoming the second-largest California wildfire by acres burned. The Dixie fire was responsible for over 963,000 acres burned across the state that year. Wildfire causes Wildfires are uncontrolled fires burning across any type of combustible vegetation such as grass- and brushland, forests, and agricultural fields. They are also referred to as wildland fires, forest fires, or bushfires, with the latter term particularly common in Australia. Wildfires regularly occur on all continents of the world, except for Antarctica, but are particularly common in dry regions with dense vegetation. As the rise in average global temperatures is changing weather patterns and resulting in more and more countries being affected by dry, hot weather conditions, the severity and rapid spread of wildfires have increased in recent years. The most common causes of wildfires are natural phenomena such as lightning strikes as well as human activity. The area burned due to human-caused wildfires in the U.S. surpassed 1.5 million acres in 2023.

Get data on forest fires, compiled annually for the National Forestry Database The National Forestry Database includes national forest data and forest management statistics to seve as a credible, accurate and reliable source of information on forest management and its impact on the forest resource. Forest fire data is grouped into eight categories, which are further broken down by geographic location. These include: * number of fires by cause class and response category * area burned by cause class and response category * number of fires by month and response category * area burned by month and response category * number of fires by fire size class and response category * area burned by fire size class and response category * area burned by productivity class, stocking class, maturity class and response category * other fire statistics, such as property losses

The increase in wildfires, particularly in the western U.S., represents one of the greatest threats to multiple native ecosystems. Despite this threat, there is currently no central repository to store both past and current wildfire perimeter data. Currently, wildfire boundaries can only be found in disparate local or national datasets. These datasets are generally restricted to specific locations, fire sizes, or time periods. Our objective was to create a comprehensive national wildfire perimeter dataset by combining all freely available wildfire datasets that we could download. We combined and dissolved individual wildfire polygons from multiple datasets if they were in the same year and overlapped each other or were within 1km of the fire boundary. This combined dataset includes spatial summary statistics such as number of times burned, earliest fire of record, and most recent fire of record.

Wildfire activity in the United States saw a significant increase in 2024, with approximately *** million acres burned. This marks a more than ********* increase from the previous year. Such development boosts the concerning upward trend in wildfire damage across the country that has developed in the past half a century. Humans or lightning? A wildfire can start by natural causes. In 2024, Oregon and Arizona were the states most affected, each with more than *** cases recorded. Nevertheless, human-caused wildfires continue to play a significant role in the overall landscape. In 2024, over ****** wildfires in the U.S. were attributed to human activity, resulting in more than *** million acres burned. Wildfire suppression The financial burden of wildfire suppression remains substantial. The estimated costs of wildfire suppression in the U.S. stood at almost *** million U.S. dollars in 2023, a 13-fold increase in comparison to 1985. As climate change continues to alter weather patterns and create more favorable conditions for wildfires, the need for effective prevention, management, and suppression strategies is becoming increasingly critical.

The data included in this publication depict components of wildfire risk specifically for populated areas in the United States. These datasets represent where people live in the United States and the in situ risk from wildfire, i.e., the risk at the location where the adverse effects take place.National wildfire hazard datasets of annual burn probability and fire intensity, generated by the USDA Forest Service, Rocky Mountain Research Station and Pyrologix LLC, form the foundation of the Wildfire Risk to Communities data. Vegetation and wildland fuels data from LANDFIRE 2020 (version 2.2.0) were used as input to two different but related geospatial fire simulation systems. Annual burn probability was produced with the USFS geospatial fire simulator (FSim) at a relatively coarse cell size of 270 meters (m). To bring the burn probability raster data down to a finer resolution more useful for assessing hazard and risk to communities, we upsampled them to the native 30 m resolution of the LANDFIRE fuel and vegetation data. In this upsampling process, we also spread values of modeled burn probability into developed areas represented in LANDFIRE fuels data as non-burnable. Burn probability rasters represent landscape conditions as of the end of 2020. Fire intensity characteristics were modeled at 30 m resolution using a process that performs a comprehensive set of FlamMap runs spanning the full range of weather-related characteristics that occur during a fire season and then integrates those runs into a variety of results based on the likelihood of those weather types occurring. Before the fire intensity modeling, the LANDFIRE 2020 data were updated to reflect fuels disturbances occurring in 2021 and 2022. As such, the fire intensity datasets represent landscape conditions as of the end of 2022. The data products in this publication that represent where people live, reflect 2021 estimates of housing unit and population counts from the U.S. Census Bureau, combined with building footprint data from Onegeo and USA Structures, both reflecting 2022 conditions.The specific raster datasets included in this publication include:Building Count: Building Count is a 30-m raster representing the count of buildings in the building footprint dataset located within each 30-m pixel.Building Density: Building Density is a 30-m raster representing the density of buildings in the building footprint dataset (buildings per square kilometer [km²]).Building Coverage: Building Coverage is a 30-m raster depicting the percentage of habitable land area covered by building footprints.Population Count (PopCount): PopCount is a 30-m raster with pixel values representing residential population count (persons) in each pixel.Population Density (PopDen): PopDen is a 30-m raster of residential population density (people/km²).Housing Unit Count (HUCount): HUCount is a 30-m raster representing the number of housing units in each pixel.Housing Unit Density (HUDen): HUDen is a 30-m raster of housing-unit density (housing units/km²).Housing Unit Exposure (HUExposure): HUExposure is a 30-m raster that represents the expected number of housing units within a pixel potentially exposed to wildfire in a year. This is a long-term annual average and not intended to represent the actual number of housing units exposed in any specific year.Housing Unit Impact (HUImpact): HUImpact is a 30-m raster that represents the relative potential impact of fire to housing units at any pixel, if a fire were to occur. It is an index that incorporates the general consequences of fire on a home as a function of fire intensity and uses flame length probabilities from wildfire modeling to capture likely intensity of fire.Housing Unit Risk (HURisk): HURisk is a 30-m raster that integrates all four primary elements of wildfire risk - likelihood, intensity, susceptibility, and exposure - on pixels where housing unit density is greater than zero.Additional methodology documentation is provided with the data publication download. (https://www.fs.usda.gov/rds/archive/catalog/RDS-2020-0060-2).Note: Pixel values in this image service have been altered from the original raster dataset due to data requirements in web services. The service is intended primarily for data visualization. Relative values and spatial patterns have been largely preserved in the service, but users are encouraged to download the source data for quantitative analysis.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

This archive contains the data and code used to produce the Western United States Large Forest-Fire Stochastic Simulator (WULFFSS), version 1.0, which is a monthly gridded forest-fire model using interpretable statistics. The WULFFSS operates at 12-km resolution and calculates monthly probabilities of forest fires ≥100 ha as well as the area burned per fire. The model is forced by variables related to vegetation, topographic, anthropogenic, and climate factors, organized into three indices representing spatial, annual-cycle, and lower frequency temporal domains. These indices can interact, so variables promoting fire in one domain amplify fire-promoting effects in another. The fire probability and size modules use multiple logistic and linear regression, respectively, and can be easily updated as new data or ideas emerge. During its training period of 1985–2024, WULFFSS captures >70% and >80% of observed interannual variability in western US forest-fire frequency and area, respect..., , # The western United States large forest-fire stochastic simulator (WULFFSS) 1.0: A monthly gridded forest-fire model using interpretable statistics

Dataset DOI: 10.5061/dryad.63xsj3vdb

Description of the data and file structure

This repository contains the data and code used to produce version 1.0 of the Western United States Large Forest-Fire Stochastic Simulator (WULFFSS), as well as the equations that comprise the model and code to run the model. The WULFFSS simulates the probabilities and sizes of forest fires at least 1 km2 in size every month across forested areas of the western US on a 12-km resolution grid. The model is forced by variables related to vegetation, topographic, anthropogenic, and climate factors, organized into three indices representing spatial, annual-cycle, and lower frequency temporal domains. These indices can interact, so variables promoting fire in one domain amplify fire-promoting effects in another. Fire probability and si...,

Globally, ************ hectares of tree cover were lost to wildfires in 2023. During the same year, the total area of tree cover loss caused by fires in general (wildfires and other fire events like clearing for agriculture) amounted to ************ hectares.

National burn probability (BP) and conditional fire intensity level (FIL) data were generated for the conterminous United States (US) using a geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. [2011]). The FSim system includes modules for weather generation, wildfire occurrence, fire growth, and fire suppression. FSim is designed to simulate the occurrence and growth of wildfires under tens of thousands of hypothetical contemporary fire seasons in order to estimate the probability of a given area (i.e., pixel) burning under current landscape conditions and fire management practices. The data presented here represent modeled BP and FIL for the conterminous US at a 270-meter grid spatial resolution. The six FILs correspond to flame-length classes as follows: FIL1 = < 2 feet (ft); FIL2 = 2 < 4 ft.; FIL3 = 4 < 6 ft.; FIL4 = 6 < 8 ft.; FIL5 = 8 < 12 ft.; FIL6 = 12+ ft. Because they indicate conditional probabilities (i.e., representing the likelihood of burning at a certain intensity level, given that a fire occurs), the FIL*_20160830 data must be used in conjunction with the BP_20160830 data for risk assessment.

This filtered version of the layer represents all IRWIN-tracked fires that originated in California or are are less than 100% contained.This layer presents the best-known point and perimeter locations of wildfire occurrences within the United States over the past 7 days. Points mark a location within the wildfire area and provide current information about that wildfire. Perimeters are the line surrounding land that has been impacted by a wildfire.Consumption Best Practices:As a service that is subject to very high usage, ensure peak performance and accessibility of your maps and apps by avoiding the use of non-cacheable relative Date/Time field filters. To accommodate filtering events by Date/Time, we suggest using the included "Age" fields that maintain the number of days or hours since a record was created or last modified, compared to the last service update. These queries fully support the ability to cache a response, allowing common query results to be efficiently provided to users in a high demand service environment.When ingesting this service in your applications, avoid using POST requests whenever possible. These requests can compromise performance and scalability during periods of high usage because they too are not cacheable.Source:  Wildfire points are sourced from Integrated Reporting of Wildland-Fire Information (IRWIN) and perimeters from National Interagency Fire Center (NIFC). Current Incidents: This layer provides a near real-time view of the data being shared through the Integrated Reporting of Wildland-Fire Information (IRWIN) service. IRWIN provides data exchange capabilities between participating wildfire systems, including federal, state and local agencies. Data is synchronized across participating organizations to make sure the most current information is available. The display of the points are based on the NWCG Fire Size Classification applied to the daily acres attribute.Current Perimeters: This layer displays fire perimeters posted to the National Incident Feature Service. It is updated from operational data and may not reflect current conditions on the ground. For a better understanding of the workflows involved in mapping and sharing fire perimeter data, see the National Wildfire Coordinating Group Standards for Geospatial Operations.Update Frequency:  Every 15 minutes using the Aggregated Live Feed Methodology based on the following filters:Events modified in the last 7 daysEvents that are not given a Fire Out DateIncident Type Kind: FiresIncident Type Category: Prescribed Fire, Wildfire, and Incident ComplexArea Covered: United StatesWhat can I do with this layer? The data includes basic wildfire information, such as location, size, environmental conditions, and resource summaries. Features can be filtered by incident name, size, or date keeping in mind that not all perimeters are fully attributed.Attribute InformationThis is a list of attributes that benefit from additional explanation. Not all attributes are listed.Incident Type Category: This is a breakdown of events into more specific categories.Wildfire (WF) -A wildland fire originating from an unplanned ignition, such as lightning, volcanos, unauthorized and accidental human caused fires, and prescribed fires that are declared wildfires.Prescribed Fire (RX) - A wildland fire originating from a planned ignition in accordance with applicable laws, policies, and regulations to meet specific objectives.Incident Complex (CX) - An incident complex is two or more individual incidents in the same general proximity that are managed together under one Incident Management Team. This allows resources to be used across the complex rather than on individual incidents uniting operational activities.IrwinID: Unique identifier assigned to each incident record in both point and perimeter layers.Acres: these typically refer to the number of acres within the current perimeter of a specific, individual incident, including unburned and unburnable islands.Discovery: An estimate of acres burning upon the discovery of the fire.Calculated or GIS:  A measure of acres calculated (i.e., infrared) from a geospatial perimeter of a fire.Daily: A measure of acres reported for a fire.Final: The measure of acres within the final perimeter of a fire. More specifically, the number of acres within the final fire perimeter of a specific, individual incident, including unburned and unburnable islands.Dates: the various systems contribute date information differently so not all fields will be populated for every fire.FireDiscovery: The date and time a fire was reported as discovered or confirmed to exist. May also be the start date for reporting purposes. Containment: The date and time a wildfire was declared contained. Control: The date and time a wildfire was declared under control.ICS209Report: The date and time of the latest approved ICS-209 report.Current: The date and time a perimeter is last known to be updated.FireOut: The date and time when a fire is declared out.ModifiedOnAge: (Integer) Computed days since event last modified.DiscoveryAge: (Integer) Computed days since event's fire discovery date.CurrentDateAge: (Integer) Computed days since perimeter last modified.CreateDateAge: (Integer) Computed days since perimeter entry created.GACC: A code that identifies one of the wildland fire geographic area coordination centers. A geographic area coordination center is a facility that is used for the coordination of agency or jurisdictional resources in support of one or more incidents within a geographic coordination area.Fire Mgmt Complexity: The highest management level utilized to manage a wildland fire event.Incident Management Organization: The incident management organization for the incident, which may be a Type 1, 2, or 3 Incident Management Team (IMT), a Unified Command, a Unified Command with an IMT, National Incident Management Organization (NIMO), etc. This field is null if no team is assigned.Unique Fire Identifier: Unique identifier assigned to each wildland fire. yyyy = calendar year, SSUUUU = Point Of Origin (POO) protecting unit identifier (5 or 6 characters), xxxxxx = local incident identifier (6 to 10 characters)RevisionsJan 4, 2021: Added Integer fields 'Days Since...' to Current_Incidents point layer and Current_Perimeters polygon layer. These fields are computed when the data is updated, reflecting the current number of days since each record was last updated. This will aid in making 'age' related, cache friendly queries.Mar 12, 2021: Added second set of 'Age' fields for Event and Perimeter record creation, reflecting age in Days since service data update.Apr 21, 2021: Current_Perimeters polygon layer is now being populated by NIFC's newest data source. A new field was added, 'IncidentTypeCategory' to better distinguish Incident types for Perimeters and now includes type 'CX' or Complex Fires. Five fields were not transferrable, and as a result 'Comments', 'Label', 'ComplexName', 'ComplexID', and 'IMTName' fields will be Null moving forward.Apr 26, 2021: Updated Incident Layer Symbology to better clarify events, reduce download size and overhead of symbols. Updated Perimeter Layer Symbology to better distingish between Wildfires and Prescribed Fires.May 5, 2021: Slight modification to Arcade logic for Symbology, refining Age comparison to Zero for fires in past 24-hours.Aug 16, 2021: Enabled Time Series capability on Layers (off by default) using 'Fire Discovery Date' for Incidents and 'Creation Date' for Perimeters.This layer is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

The FirePerimeter polygon layer represents daily and final mapped wildland fire perimeters. Incidents of 10 acres or greater in size are expected. Incidents smaller than 10 acres in size may also be included. Data are maintained at the Forest/District level, or their equivalent, to track the area affected by wildland fire. Records in FirePerimeter include perimeters for wildland fires that have corresponding records in FIRESTAT, which is the authoritative data source for all wildland fire reports. FIRESTAT, the Fire Statistics System computer application, required by the USFS for all wildland fire occurrences on National Forest System Lands or National Forest-protected lands, is used to enter and maintain information from the Individual Fire Report (FS-5100-29).National USFS fire occurrence final fire perimeters where wildland fires have historically occurred on National Forest System Lands and/or where protection is the responsibility of the US Forest Service. Knowing where wildland fire events have happened in the past is critical to land management efforts in the future.This data is utilized by fire & aviation staffs, land managers, land planners, and resource specialists on and around National Forest System Lands.*This data has been updated to match 2021 National GIS Data Dictionary Standards.Metadata and DownloadsThis record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService CSV Shapefile GeoJSON KML For complete information, please visit https://data.gov.

Wildfires resulted in *** deaths in the United States in 2023. This has been the highest figure since 1990, mostly related to the Maui wildfires in Hawaii. There have been more than *** wildfire-related deaths in the U.S. since 1990.

Historic Fire Perimeter Dataset Feedback (arcgis.com)

Current criteria for data collection are as follows:

CAL FIRE (including contract counties) submit perimeters ≥10 acres in timber, ≥50 acres in brush, or ≥300 acres in grass, and/or ≥3 impacted residential or commercial structures, and/or caused ≥1 fatality.

All cooperating agencies submit perimeters ≥10 acres.

Version update:

Firep24_1 was released in April 2025. Five hundred forty-eight fires from the 2024 fire season were added to the database (2 from BIA, 56 from BLM, 197 from CAL FIRE, 193 from Contract Counties, 27 from LRA, 8 from NPS, 55 from USFS and 8 from USFW). Six perimeters were added from the 2025 fire season (as a special case due to an unusual January fire siege). Five duplicate fires were removed, and the 2023 Sage was replaced with a more accurate perimeter. There were 900 perimeters that received updated attribution (705 removed “FIRE” from the end of Fire Name field and 148 replaced Complex IRWIN ID with Complex local incident number for COMPLEX_ID field). The following fires were identified as meeting our collection criteria but are not included in this version and will hopefully be added in a future update: Addie (2024-CACND-002119), Alpaugh (2024-CACND-001715), South (2024-CATIA-001375). One perimeter is missing containment date that will be updated in the next release.

Cross checking CALFIRS reporting for new CAL FIRE submissions to ensure accuracy with cause class was added to the compilation process. The cause class domain description for “Powerline” was updated to “Electrical Power” to be more inclusive of cause reports.

Includes separate layers filtered by criteria as follows:

California Fire Perimeters (All): Unfiltered. The entire collection of wildfire perimeters in the database. It is scale dependent and starts displaying at the country level scale.

Recent Large Fire Perimeters (≥5000 acres): Filtered for wildfires greater or equal to 5,000 acres for the last 5 years of fires (2020-January 2025), symbolized with color by year and is scale dependent and starts displaying at the country level scale. Year-only labels for recent large fires.

California Fire Perimeters (1950+): Filtered for wildfires that started in 1950-January 2025. Symbolized by decade, and display starting at country level scale.

Detailed metadata is included in the following documents:

Wildland Fire Perimeters (Firep24_1) Metadata

See more information on our Living Atlas data release here:

CAL FIRE Historical Fire Perimeters Available in ArcGIS Living Atlas

For any questions, please contact the data steward:

Kim Wallin, GIS Specialist

CAL FIRE, Fire & Resource Assessment Program (FRAP)

kimberly.wallin@fire.ca.gov

This dataset is composed of 97 Differenced Normalized Burn Ratio (dNBR) images. Each dNBR represents a rough measure of fire-related vegetation change for wildfires (>400 ha) that occurred in the Sky Island Mountains within the Madrean Archipelago Ecoregion of the United States and Northern Mexico. These fires occurred between 2011 and 2017 and were mapped using Landsat 7 and 8 satellite imagery.

INVESTIGATIVE WILDFIRE DATA FOR TURKEY/ NASA

BE CAREFUL OF THE FILE NAMES.

IT CONTAINS THE DATA NEEDED TO RESEARCH LATEST FOREST FIRES IN TURKEY.

PAY ATTENTION TO THE DATE INTERVALS. THESE ARE 7-11 DAILY DATA OF LAST TIMES.

• fire _ nrt _ M _ C61 _ 212465 _ all _ countries.csv

This file is important for all countries becuase it contains fire data of last 11 days for all around the world

Content

Data on recent forest fires in Turkey, published with permission from NASA Portal. The data was created based on the hotspots and obtained from the satellite.

3 SEPARATE SATELLITE DATA:

• MODIS C6.1
• SUOMI VIIRS C2
• J1 VIIRS C1

GENERAL ATTRIBUTES

• Latitude Center of nominal 375 m fire pixel

• Longitude Center of nominal 375 m fire pixel

• Bright_ti4 (Brightness temperature I-4) VIIRS I-4: channel brightness temperature of the fire pixel measured in Kelvin.

• Scan (Along Scan pixel size) The algorithm produces approximately 375 m pixels at nadir. Scan and track reflect actual pixel size.

• Track (Along Track pixel size) The algorithm produces approximately 375 m pixels at nadir. Scan and track reflect actual pixel size.

• Acq_Date (Acquisition Date) Date of VIIRS acquisition.

• Acq_Time (Acquisition Time) Time of acquisition/overpass of the satellite (in UTC).

• Satellite N Suomi National Polar-orbiting Partnership (Suomi NPP)

• Confidence This value is based on a collection of intermediate algorithm quantities used in the detection process. It is intended to help users gauge the quality of individual hotspot/fire pixels. Confidence values are set to low, nominal and high. Low confidence daytime fire pixels are typically associated with areas of sun glint and lower relative temperature anomaly (15K) temperature anomaly in either day or nighttime data. High confidence fire pixels are associated with day or nighttime saturated pixels.

Please note:

• Low confidence nighttime pixels occur only over the geographic area extending from 11° E to 110° W and 7° N to 55° S. This area describes the region of influence of the South Atlantic Magnetic Anomaly which can cause spurious brightness temperatures in the mid-infrared channel I4 leading to potential false positive alarms. These have been removed from the NRT data distributed by FIRMS.

• Version Version identifies the collection (e.g. VIIRS Collection 1) and source of data processing: Near Real-Time (NRT suffix added to collection) or Standard Processing (collection only).

"1.0NRT" - Collection 1 NRT processing.

"1.0" - Collection 1 Standard processing.

• Bright_ti5 (Brightness temperature I-5) I-5 Channel brightness temperature of the fire pixel measured in Kelvin.

• FRP (Fire Radiative Power) FRP depicts the pixel-integrated fire radiative power in MW (megawatts). Given the unique spatial and spectral resolution of the data, the VIIRS 375 m fire detection algorithm was customized and tuned in order to optimize its response over small fires while balancing the occurrence of false alarms. Frequent saturation of the mid-infrared I4 channel (3.55-3.93 µm) driving the detection of active fires requires additional tests and procedures to avoid pixel classification errors. As a result, sub-pixel fire characterization (e.g., fire radiative power [FRP] retrieval) is only viable across small and/or low-intensity fires. Systematic FRP retrievals are based on a hybrid approach combining 375 and 750 m data. In fact, starting in 2015 the algorithm incorporated additional VIIRS channel M13 (3.973-4.128 µm) 750 m data in both aggregated and unaggregated format.

Satellite measurements of fire radiative power (FRP) are increasingly used to estimate the contribution of biomass burning to local and global carbon budgets. Without an associated uncertainty, however, FRP-based biomass burning estimates cannot be confidently compared across space and time, or against estimates derived from alternative methodologies. Differences in the per-pixel FRP measured near-simultaneously in consecutive MODIS scans are approximately normally distributed with a standard deviation (ση) of 26.6%. Simulations demonstrate that this uncertainty decreases to less than ~5% (at ±1 ση) for aggregations larger than ~50 MODIS active fire pixels. Although FRP uncertainties limit the confidence in flux estimates on a per-pixel basis, the sensitivity of biomass burning estimates to FRP uncertainties can be mitigated by conducting inventories at coarser spatiotemporal resolutions.

http://cedadocs.ceda.ac.uk/770/1/SEVIRI_FRP_documentdesc.pdf

• Type (Inferred hot spot type) 0 = presumed vegetation fire

1 = active volcano

2 = other static land source

3 = offshore detection (includes all detections over water)

• DayNight (Day or Night)

D= Daytime fire

N= Nighttime fire

The Wildland Fire Interagency Geospatial Services (WFIGS) Group provides authoritative geospatial data products under the interagency Wildland Fire Data Program. Hosted in the National Interagency Fire Center ArcGIS Online Organization (The NIFC Org), WFIGS provides both internal and public facing data, accessible in a variety of formats.This service includes perimeters for wildland fire incidents that meet the following criteria:Categorized in the IRWIN (Integrated Reporting of Wildland Fire Information) integration service as a Wildfire (WF) or Prescribed Fire (RX) recordFire Discovery Date is in the year 2025Is Valid and not "quarantined" in IRWIN due to potential conflicts with other recordsAttribution of the source polygon is set to a Feature Access of Public, a Feature Status of Approved, and an Is Visible setting of YesPerimeters are not available for every incident. For a complete set of features that meet the same IRWIN criteria, see the 2025 Wildland Fire Incident Locations to Date service.No "fall-off" rules are applied to this service. Criteria were determined by an NWCG Geospatial Subcommittee task group. Data are refreshed every 5 minutes. Changes in the perimeter source may take up to 15 minutes to display.Perimeters are pulled from multiple sources with rules in place to ensure the most current or most authoritative shape is used.Attributes and their definitions can be found below. More detail about the NWCG Wildland Fire Event Polygon standard can be found here.Attributes:poly_SourceOIDThe OBJECTID value of the source record in the source dataset providing the polygon.poly_IncidentNameThe incident name as stored in the polygon source record.poly_MapMethodThe mapping method with which the polygon was derived.poly_GISAcresThe acreage of the polygon as stored in the polygon source record.poly_CreateDateSystem generated date for the date time the source polygon record was created (stored in UTC).poly_DateCurrentSystem generated date for the date time the source polygon record was last edited (stored in UTC).poly_PolygonDateTimeRepresents the date time that the polygon data was captured.poly_IRWINIDIRWIN ID stored in the polygon record.poly_FORIDFORID stored in the polygon record.poly_Acres_AutoCalcSystem calculated acreage of the polygon (geodesic WGS84 acres).poly_SourceGlobalIDThe GlobalID value of the source record in the source dataset providing the polygon.poly_SourceThe source dataset providing the polygon.attr_SourceOIDThe OBJECTID value of the source record in the source dataset providing the attribution.attr_ABCDMiscA FireCode used by USDA FS to track and compile cost information for emergency initial attack fire suppression expenditures. for A, B, C & D size class fires on FS lands.attr_ADSPermissionStateIndicates the permission hierarchy that is currently being applied when a system utilizes the UpdateIncident operation.attr_ContainmentDateTimeThe date and time a wildfire was declared contained. attr_ControlDateTimeThe date and time a wildfire was declared under control.attr_CreatedBySystemArcGIS Server Username of system that created the IRWIN Incident record.attr_IncidentSizeReported for a fire. The minimum size is 0.1.attr_DiscoveryAcresAn estimate of acres burning upon the discovery of the fire. More specifically when the fire is first reported by the first person that calls in the fire. The estimate should include number of acres within the current perimeter of a specific, individual incident, including unburned and unburnable islands.attr_DispatchCenterIDA unique identifier for a dispatch center responsible for supporting the incident.attr_EstimatedCostToDateThe total estimated cost of the incident to date.attr_FinalAcresReported final acreage of incident.attr_FFReportApprovedByTitleThe title of the person that approved the final fire report for the incident.attr_FFReportApprovedByUnitNWCG Unit ID associated with the individual who approved the final report for the incident.attr_FFReportApprovedDateThe date that the final fire report was approved for the incident.attr_FireBehaviorGeneralA general category describing the manner in which the fire is currently reacting to the influences of fuel, weather, and topography. attr_FireBehaviorGeneral1A more specific category further describing the general fire behavior (manner in which the fire is currently reacting to the influences of fuel, weather, and topography). attr_FireBehaviorGeneral2A more specific category further describing the general fire behavior (manner in which the fire is currently reacting to the influences of fuel, weather, and topography). attr_FireBehaviorGeneral3A more specific category further describing the general fire behavior (manner in which the fire is currently reacting to the influences of fuel, weather, and topography). attr_FireCauseBroad classification of the reason the fire occurred identified as human, natural or unknown. attr_FireCauseGeneralAgency or circumstance which started a fire or set the stage for its occurrence; source of a fire's ignition. For statistical purposes, fire causes are further broken into specific causes. attr_FireCauseSpecificA further categorization of each General Fire Cause to indicate more specifically the agency or circumstance which started a fire or set the stage for its occurrence; source of a fire's ignition. attr_FireCodeA code used within the interagency wildland fire community to track and compile cost information for emergency fire suppression expenditures for the incident. attr_FireDepartmentIDThe U.S. Fire Administration (USFA) has created a national database of Fire Departments. Most Fire Departments do not have an NWCG Unit ID and so it is the intent of the IRWIN team to create a new field that includes this data element to assist the National Association of State Foresters (NASF) with data collection.attr_FireDiscoveryDateTimeThe date and time a fire was reported as discovered or confirmed to exist. May also be the start date for reporting purposes.attr_FireMgmtComplexityThe highest management level utilized to manage a wildland fire event. attr_FireOutDateTimeThe date and time when a fire is declared out. attr_FireStrategyConfinePercentIndicates the percentage of the incident area where the fire suppression strategy of "Confine" is being implemented.attr_FireStrategyFullSuppPrcntIndicates the percentage of the incident area where the fire suppression strategy of "Full Suppression" is being implemented.attr_FireStrategyMonitorPercentIndicates the percentage of the incident area where the fire suppression strategy of "Monitor" is being implemented.attr_FireStrategyPointZonePrcntIndicates the percentage of the incident area where the fire suppression strategy of "Point Zone Protection" is being implemented.attr_FSJobCodeA code use to indicate the Forest Service job accounting code for the incident. This is specific to the Forest Service. Usually displayed as 2 char prefix on FireCode.attr_FSOverrideCodeA code used to indicate the Forest Service override code for the incident. This is specific to the Forest Service. Usually displayed as a 4 char suffix on FireCode. For example, if the FS is assisting DOI, an override of 1502 will be used.attr_GACCA code that identifies one of the wildland fire geographic area coordination center at the point of origin for the incident.A geographic area coordination center is a facility that is used for the coordination of agency or jurisdictional resources in support of one or more incidents within a geographic coordination area.attr_ICS209ReportDateTimeThe date and time of the latest approved ICS-209 report.attr_ICS209RptForTimePeriodFromThe date and time of the beginning of the time period for the current ICS-209 submission.attr_ICS209RptForTimePeriodToThe date and time of the end of the time period for the current ICS-209 submission. attr_ICS209ReportStatusThe version of the ICS-209 report (initial, update, or final). There should never be more than one initial report, but there can be numerous updates, and even multiple finals (as determined by business rules).attr_IncidentManagementOrgThe incident management organization for the incident, which may be a Type 1, 2, or 3 Incident Management Team (IMT), a Unified Command, a Unified Command with an IMT, National Incident Management Organization (NIMO), etc. This field is null if no team is assigned.attr_IncidentNameThe name assigned to an incident.attr_IncidentShortDescriptionGeneral descriptive location of the incident such as the number of miles from an identifiable town. attr_IncidentTypeCategoryThe Event Category is a sub-group of the Event Kind code and description. The Event Category further breaks down the Event Kind into more specific event categories.attr_IncidentTypeKindA general, high-level code and description of the types of incidents and planned events to which the interagency wildland fire community responds.attr_InitialLatitudeThe latitude location of the initial reported point of origin specified in decimal degrees.attr_InitialLongitudeThe longitude location of the initial reported point of origin specified in decimal degrees.attr_InitialResponseAcresAn estimate of acres burning at the time of initial response. More specifically when the IC arrives and performs initial size up. The minimum size must be 0.1. The estimate should include number of acres within the current perimeter of a specific, individual incident, including unburned and unburnable islands.attr_InitialResponseDateTimeThe date/time of the initial response to the incident. More specifically when the IC arrives and performs initial size up. attr_IrwinIDUnique identifier assigned to each incident record in IRWIN.attr_IsFireCauseInvestigatedIndicates if an investigation is underway or was completed to determine the cause of a fire.attr_IsFSAssistedIndicates if the Forest Service provided assistance on an incident outside their jurisdiction.attr_IsMultiJurisdictionalIndicates if the

Ambee’s wildfire dataset captures active fire events, historical fire activity, and forward-looking wildfire risk with global coverage and high confidence. Fire detections are sourced from satellite thermal anomalies and verified reports, filtered to remove ambiguity, and enriched with fire behavior metrics including FRP, FWI, and fire category. Ambee maintains a clean, spatially and temporally complete archive of historical wildfire events, providing a trusted foundation for exposure analysis, ESG modeling, and long-range risk assessments. A proprietary model projects wildfire risk up to four weeks ahead, using inputs such as weather, fuel conditions, terrain, and surface moisture. Forecasts are continuously refined and structured for integration into grid-based models, alerting systems, and operational platforms. Key parameters: • Fire detections with FRP and FWI • Fire type and category (wildfire, prescribed, normal) • Historical wildfire activity archive • Four-week wildfire risk forecast • Real-time detection confidence scores

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