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221 products in 26 categories |
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FEDs-RT-ABI-SSECDB-5min-buffer2000m
[FEDs-RT-ABI-SSECDB-5min-buffer2000m]
FEDs-RT-ABI-SSECDB-5min-buffer2000m
FEDs-RT-ABI-SSECDB-5min-buffer2000m
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FEDs-RT-ABI-SSECDB-60min-buffer2000m
[FEDs-RT-ABI-SSECDB-60min-buffer2000m]
FEDs-RT-ABI-SSECDB-60min-buffer2000m
FEDs-RT-ABI-SSECDB-60min-buffer2000m
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FEDs-RT-VIIRS-SSECDB-60min-buffer375m
[FEDs-RT-VIIRS-SSECDB-60min-buffer375m]
FEDs-RT-VIIRS-SSECDB-60min-buffer375m
FEDs-RT-VIIRS-SSECDB-60min-buffer375m
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GOES East FDC - FD
[goes-east-F-FDC]
The GOES-R Fire Detection and Characterization (FDC) data product uses bothvisible and infrared (IR) ABI spectral channels (or bands) to locate fires and retrieve fire characteristics. Fires produce a stronger signal in...
The GOES-R Fire Detection and Characterization (FDC) data product uses both visible and infrared (IR) ABI spectral channels (or bands) to locate fires and retrieve fire characteristics. Fires produce a stronger signal in mid-wave IR bands (around 4 µm) than they do in longwave IR bands (such as 11 µm). That differential response forms the basis for the GOES-R FDC product. The 3.9 µm ABI band is particularly useful for fire detection. Its shorter wavelength is sensitive to the hottest part of a fire pixel.
Right-click to "Probe" pixel value. 10-15 indicates first detection. 30-35 indicates multiple detections in the past 12 hours.
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GOES East FDC Contours - CONUS
[goes-east-C-FDC-contours]
goes-east-C-FDC-contours
goes-east-C-FDC-contours
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GOES East FDC Contours - Meso1
[goes-east-M1-FDC-contours]
goes-east-M1-FDC-contours
goes-east-M1-FDC-contours
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GOES East FDC Contours - Meso2
[goes-east-M2-FDC-contours]
goes-east-M2-FDC-contours
goes-east-M2-FDC-contours
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GOES West FDC Contours - CONUS
[goes-west-C-FDC-contours]
goes-west-C-FDC-contours
goes-west-C-FDC-contours
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GOES West FDC Contours - FD
[goes-west-F-FDC-contours]
goes-west-F-FDC-contours
goes-west-F-FDC-contours
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GOES West FDC Contours - Meso1
[goes-west-M1-FDC-contours]
goes-west-M1-FDC-contours
goes-west-M1-FDC-contours
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GOES West FDC Contours - Meso2
[goes-west-M2-FDC-contours]
goes-west-M2-FDC-contours
goes-west-M2-FDC-contours
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GOES East Daily Fire Detections - CONUS
[NGFS-DAILY-CONUS-EAST]
This terrain-corrected product represents cumulative detections at the 2kmABI pixel level in a 24hr UTC day. For performance, serial repeat detections for the same pixel have been removed. The source data are CSV...
This terrain-corrected product represents cumulative detections at the 2km ABI pixel level in a 24hr UTC day. For performance, serial repeat detections for the same pixel have been removed. The source data are CSV files from the link below.
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GOES East Scene Fire Detections - CONUS
[NGFS-SCENE-CONUS-EAST]
Pixel-level fire radiative power estimates from the CONUS scan of ABI onGOES East. Pixel corner point locations are terrain corrected. These data update every 5 minutes.
Pixel-level fire radiative power estimates from the CONUS scan of ABI on GOES East. Pixel corner point locations are terrain corrected. These data update every 5 minutes.
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GOES East Scene Fire Detections - Mesoscale1
[NGFS-SCENE-Mesoscale1-EAST]
Pixel-level fire radiative power estimates from the Mesoscale-1 scan of ABIon GOES East. Pixel corner point locations are terrain corrected. These data update every minute.
Pixel-level fire radiative power estimates from the Mesoscale-1 scan of ABI on GOES East. Pixel corner point locations are terrain corrected. These data update every minute.
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GOES East Scene Fire Detections - Mesoscale2
[NGFS-SCENE-Mesoscale2-EAST]
Pixel-level fire radiative power estimates from the Mesoscale-2 scan of ABIon GOES East. Pixel corner point locations are terrain corrected. These data update every minute.
Pixel-level fire radiative power estimates from the Mesoscale-2 scan of ABI on GOES East. Pixel corner point locations are terrain corrected. These data update every minute.
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GOES East Scene Fire Detections - No.&So. America
[NGFS-SCENE-FD-EAST]
Pixel-level fire radiative power estimates from the Full Disk scan of ABIon GOES East. Pixel corner point locations are terrain corrected. These data update every 5 minutes.
Pixel-level fire radiative power estimates from the Full Disk scan of ABI on GOES East. Pixel corner point locations are terrain corrected. These data update every 5 minutes.
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GOES West Daily Fire Detections - CONUS
[NGFS-DAILY-CONUS-WEST]
This terrain-corrected product represents cumulative detections at the 2kmABI pixel level in a 24hr UTC day. For performance, serial repeat detections for the same pixel have been removed. The source data are CSV...
This terrain-corrected product represents cumulative detections at the 2km ABI pixel level in a 24hr UTC day. For performance, serial repeat detections for the same pixel have been removed. The source data are CSV files from the link below.
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GOES West Scene Fire Detections - CONUS
[NGFS-SCENE-CONUS-WEST]
Pixel-level fire radiative power estimates from the CONUS scan of ABI onGOES West. Pixel corner point locations are terrain corrected. These data update every 5 minutes.
Pixel-level fire radiative power estimates from the CONUS scan of ABI on GOES West. Pixel corner point locations are terrain corrected. These data update every 5 minutes.
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GOES West Scene Fire Detections - Full Disk
[NGFS-SCENE-FD-WEST]
Pixel-level fire radiative power estimates from the Full Disk scan of ABIon GOES West. Pixel corner point locations are terrain corrected. These data update every 5 minutes.
Pixel-level fire radiative power estimates from the Full Disk scan of ABI on GOES West. Pixel corner point locations are terrain corrected. These data update every 5 minutes.
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GOES West Scene Fire Detections - Mesoscale1
[NGFS-SCENE-Mesoscale1-WEST]
Pixel-level fire radiative power estimates from the Mesoscale-1 scan of ABIon GOES West. Pixel corner point locations are terrain corrected. These data update every minute.
Pixel-level fire radiative power estimates from the Mesoscale-1 scan of ABI on GOES West. Pixel corner point locations are terrain corrected. These data update every minute.
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GOES West Scene Fire Detections - Mesoscale2
[NGFS-SCENE-Mesoscale2-WEST]
Pixel-level fire radiative power estimates from the Mesoscale-2 scan of ABIon GOES West. Pixel corner point locations are terrain corrected. These data update every minute.
Pixel-level fire radiative power estimates from the Mesoscale-2 scan of ABI on GOES West. Pixel corner point locations are terrain corrected. These data update every minute.
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NOAA-20 Fire Detections - WI DB (Experimental)
[NGFS-SCENE-noaa20]
This product is experimental
This product is experimental
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NOAA-20 Fire Radiative Power VIIRS I-band DB ConUS
[AFIMG-Points-j01]
VIIRS 375m I-band high spatial resolution imagery provides a greaterresponse over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime...
VIIRS 375m I-band high spatial resolution imagery provides a greater response over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime performance. Consequently, these data are well suited for use in support of fire management (e.g., near real-time alert systems), as well as other science applications requiring improved fire mapping fidelity. These data represent mean fire radiative power from SNPP and NOAA-20 Direct Broadcast imagery processed with CSPP software.
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NOAA-21 Fire Detections - WI DB (Experimental)
[NGFS-SCENE-noaa21]
This product is experimental
This product is experimental
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NOAA-21 Fire Radiative Power VIIRS I-band DB ConUS
[AFIMG-Points-j02]
VIIRS 375m I-band high spatial resolution imagery provides a greaterresponse over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime...
VIIRS 375m I-band high spatial resolution imagery provides a greater response over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime performance. Consequently, these data are well suited for use in support of fire management (e.g., near real-time alert systems), as well as other science applications requiring improved fire mapping fidelity. These data represent mean fire radiative power from SNPP and NOAA-20 Direct Broadcast imagery processed with CSPP software.
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SNPP Fire Detections - WI DB (Experimental)
[NGFS-SCENE-snpp]
This product is experimental
This product is experimental
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SNPP Fire Radiative Power VIIRS I-band DB ConUS
[AFIMG-Points-npp]
VIIRS 375m I-band high spatial resolution imagery provides a greaterresponse over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime...
VIIRS 375m I-band high spatial resolution imagery provides a greater response over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime performance. Consequently, these data are well suited for use in support of fire management (e.g., near real-time alert systems), as well as other science applications requiring improved fire mapping fidelity. These data represent mean fire radiative power from SNPP and NOAA-20 Direct Broadcast imagery processed with CSPP software.
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VIIRS Fire Detections - WI DB (Experimental)
[NGFS-SCENE-VIIRS-WIDB]
This product is experimental
This product is experimental
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VIIRS Fire Detections Non-PA Confidence - WI DB (Experimental)
[NGFS-SCENE-VIIRS-WIDB-Confidence]
View of NGFS-SCENE-VIIRS-WIDB
View of NGFS-SCENE-VIIRS-WIDB
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VIIRS Fire Detections PA Only - WI DB (Experimental)
[NGFS-SCENE-VIIRS-WIDB-PA]
View of NGFS-SCENE-VIIRS-WIDB
View of NGFS-SCENE-VIIRS-WIDB
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Alaska-FirePerimeter-2025-AICC
[Alaska-FirePerimeter-2025-AICC]
Alaska-FirePerimeter-2025-AICC
Alaska-FirePerimeter-2025-AICC
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NOAA-20 Fire Radiative Power VIIRS I-band - GINA
[AFIMG-Points-j01-GINA]
VIIRS 375m I-band high spatial resolution imagery provides a greaterresponse over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime...
VIIRS 375m I-band high spatial resolution imagery provides a greater response over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime performance. Consequently, these data are well suited for use in support of fire management (e.g., near real-time alert systems), as well as other science applications requiring improved fire mapping fidelity. These data represent mean fire radiative power from SNPP and NOAA-20 Direct Broadcast imagery processed with CSPP software at GINA.
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NOAA-21 Fire Radiative Power VIIRS I-band - GINA
[AFIMG-Points-j02-GINA]
VIIRS 375m I-band high spatial resolution imagery provides a greaterresponse over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime...
VIIRS 375m I-band high spatial resolution imagery provides a greater response over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime performance. Consequently, these data are well suited for use in support of fire management (e.g., near real-time alert systems), as well as other science applications requiring improved fire mapping fidelity. These data represent mean fire radiative power from SNPP and NOAA-20 Direct Broadcast imagery processed with CSPP software at GINA.
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NOAA20 Fire Detections - AK GINA (Experimental)
[NGFS-SCENE-noaa20-GINA]
This product is experimental
This product is experimental
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NOAA21 Fire Detections - AK GINA (Experimental)
[NGFS-SCENE-noaa21-GINA]
This product is experimental
This product is experimental
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SNPP Fire Detections - AK GINA (Experimental)
[NGFS-SCENE-snpp-GINA]
This product is experimental
This product is experimental
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SNPP Fire Radiative Power VIIRS I-band - GINA
[AFIMG-Points-npp-GINA]
VIIRS 375m I-band high spatial resolution imagery provides a greaterresponse over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime...
VIIRS 375m I-band high spatial resolution imagery provides a greater response over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime performance. Consequently, these data are well suited for use in support of fire management (e.g., near real-time alert systems), as well as other science applications requiring improved fire mapping fidelity. These data represent mean fire radiative power from SNPP and NOAA-20 Direct Broadcast imagery processed with CSPP software at GINA.
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Wildland Fire Perimeters - Current
[WFIGS-Perimeters]
This product represents the best available perimeters for recent andongoing wildland fires in the United States. It is produced by the Wildland Fire Interagency Geospatial Services (WFIGS) Group and provides...
This product represents the best available perimeters for recent and ongoing wildland fires in the United States.
It is produced by the Wildland Fire Interagency Geospatial Services (WFIGS) Group and 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.
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Historical Alaska Fire Occurrences by Month
[HistoricalAlaskaFires-Months-Points]
Wildfire occurrences in Alaska from 1939 to 2023. This dataset contains allfires, including false alarms and small fires. Not all months contain data. This data was created by the Alaska Interagency Coordination Center (ALCC)....
Wildfire occurrences in Alaska from 1939 to 2023. This dataset contains all fires, including false alarms and small fires. Not all months contain data. This data was created by the Alaska Interagency Coordination Center (ALCC).
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Historical Alaska Fire Occurrences by Year
[HistoricalAlaskaFires-Year-Point]
Wildfire occurrences in Alaska from 1939 to 2023. This dataset contains allfires, including false alarms and small fires. This data was created by the Alaska Interagency Coordination Center (ALCC).
Wildfire occurrences in Alaska from 1939 to 2023. This dataset contains all fires, including false alarms and small fires. This data was created by the Alaska Interagency Coordination Center (ALCC).
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Historical Alaska Fire Perimeters by Month
[HistoricalAlaskaFires-Months-Polygon]
Perimeters of Alaskan wildfires from 1939 to 2023. This dataset does notcontain data for smaller fires without parameters. This data was created by the Alaska Interagency Coordination Center (ALCC).
Perimeters of Alaskan wildfires from 1939 to 2023. This dataset does not contain data for smaller fires without parameters. This data was created by the Alaska Interagency Coordination Center (ALCC).
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Historical Alaska Fire Perimeters by Year
[HistoricalAlaskaFires-Year-Polygon]
Perimeters of Alaskan wildfires from 1939 to 2023. This dataset does notcontain data for smaller fires without parameters. This data was created by the Alaska Interagency Coordination Center.
Perimeters of Alaskan wildfires from 1939 to 2023. This dataset does not contain data for smaller fires without parameters. This data was created by the Alaska Interagency Coordination Center.
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MTBS Burned Area Boundaries by Month
[MTBS-Polygon-Month]
This dataset provides the fire perimeters of burned areas in MonitoringTrends in Burn Severity (MTBS) database. Analysts used post-fire imagery, Normalized Burn Ratio (NBR), and difference NBR (dNBR) to delineate the...
This dataset provides the fire perimeters of burned areas in Monitoring Trends in Burn Severity (MTBS) database. Analysts used post-fire imagery, Normalized Burn Ratio (NBR), and difference NBR (dNBR) to delineate the burned area and create fire perimeters. Each fire is organized by the month it ignited. The dataset only includes fires greater than 1,000 acres in the western U.S. and 500 acres in the eastern U.S.
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MTBS Burn Severity by Year
[Severity]
MTBS Burn severity metrics for wildfires in the Continental United States,Hawaii, and Alaska from 2000 to 2021 are displayed by the year of occurrence. This data set includes all fires 1,000 acres or greater in the...
MTBS Burn severity metrics for wildfires in the Continental United States, Hawaii, and Alaska from 2000 to 2021 are displayed by the year of occurrence. This data set includes all fires 1,000 acres or greater in the western United States and 500 acres or greater in the eastern Unites States. Burn severity layers are thematic images depicting severity as unburned to low, low, moderate, high, and increased greenness (increased postfire vegetation response). The layer may also have a sixth class representing a mask for clouds, shadows, large water bodies, or other features on the landscape that erroneously affect the severity classification.
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MTBS Fires Occurrences by Month
[MTBS-Points-Month]
This dataset provides the central points of fire perimeters in theMonitoring Trends in Burn Severity (MTBS) database. Analysts used post-fire imagery, Normalized Burn Ratio (NBR), and difference NBR (dNBR) to...
This dataset provides the central points of fire perimeters in the Monitoring Trends in Burn Severity (MTBS) database. Analysts used post-fire imagery, Normalized Burn Ratio (NBR), and difference NBR (dNBR) to delineate the fire perimeters and calculate the centroids. Each fire is organized by the month it ignited. The dataset only includes fires greater than 1,000 acres in the western U.S. and 500 acres in the eastern U.S.
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MTBS Fires Occurrences by Year
[MTBS-Point-Year]
This dataset provides the central points of fire perimeters in theMonitoring Trends in Burn Severity (MTBS) database. Analysts used post-fire imagery, Normalized Burn Ratio (NBR), and difference NBR (dNBR) to...
This dataset provides the central points of fire perimeters in the Monitoring Trends in Burn Severity (MTBS) database. Analysts used post-fire imagery, Normalized Burn Ratio (NBR), and difference NBR (dNBR) to delineate the fire perimeters and calculate the centroids. Each fire is organized by the year it ignited. The dataset only includes fires greater than 1,000 acres in the western U.S. and 500 acres in the eastern U.S.
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USGS Fire Occurrence
[USGSFireOccurrence-Months-Points]
The USGS Fire Occurrence Database includes fires with ignition originsknown to the nearest point on the Public Land Survey System grid (1.6 km horizontal resolution) and spans 1992–2020. Fires are displayed by the...
The USGS Fire Occurrence Database includes fires with ignition origins known to the nearest point on the Public Land Survey System grid (1.6 km horizontal resolution) and spans 1992–2020. Fires are displayed by the month they were discovered in.
This data was created by Karen Short and published in 2022
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USGS Fire Occurrences Over 1 Acre
[USGSFireOccurrence-Months-Over1Acre-Points]
The USGS Fire Occurrence Database includes fires with ignition originsknown to the nearest point on the Public Land Survey System grid (1.6 km horizontal resolution) and a size greater than 1 acre. The dataset spans...
The USGS Fire Occurrence Database includes fires with ignition origins known to the nearest point on the Public Land Survey System grid (1.6 km horizontal resolution) and a size greater than 1 acre. The dataset spans 1992–2020. Fires are displayed by the month they were discovered in. The data was created by Karen Short and published in 2022
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GOES East Microphysics - CONUS
[G19-C-NGFSMicrophysics-TC]
G16-C-NGFSMicrophysics-TC
G16-C-NGFSMicrophysics-TC
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GOES East Microphysics - FD
[G19-F-NGFSMicrophysics-TC]
G16-F-NGFSMicrophysics-TC
G16-F-NGFSMicrophysics-TC
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GOES East Microphysics - Meso1
[G19-M1-NGFSMicrophysics-TC]
G16-M1-NGFSMicrophysics-TC
G16-M1-NGFSMicrophysics-TC
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GOES East Microphysics - Meso2
[G19-M2-NGFSMicrophysics-TC]
G16-M2-NGFSMicrophysics-TC
G16-M2-NGFSMicrophysics-TC
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GOES West Microphysics - CONUS
[G18-C-NGFSMicrophysics-TC]
G18-C-NGFSMicrophysics-TC
G18-C-NGFSMicrophysics-TC
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GOES West Microphysics - FD
[G18-F-NGFSMicrophysics-TC]
G18-F-NGFSMicrophysics-TC
G18-F-NGFSMicrophysics-TC
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GOES West Microphysics - Meso1
[G18-M1-NGFSMicrophysics-TC]
G18-M1-NGFSMicrophysics-TC
G18-M1-NGFSMicrophysics-TC
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GOES West Microphysics - Meso2
[G18-M2-NGFSMicrophysics-TC]
G18-M2-NGFSMicrophysics-TC
G18-M2-NGFSMicrophysics-TC
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GOES-East GLM FED CONUS
[GOESEastGLMFEDRadC]
GOES-East flash-extent density, a 5-min accumulation of flashes at eachpoint.
GOES-East flash-extent density, a 5-min accumulation of flashes at each point.
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GOES-West GLM FED CONUS
[GOESWestGLMFEDRadC]
GOES-West flash-extent density, a 5-min accumulation of flashes at eachpoint.
GOES-West flash-extent density, a 5-min accumulation of flashes at each point.
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LightningCast GOES-East CONUS
[PLTGGOESEastRadC]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast GOES-East FD (OCONUS)
[PLTGGOESEastRadF]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast GOES-East MESO1
[PLTGGOESEastRadM1]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast GOES-East MESO2
[PLTGGOESEastRadM2]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast GOES-West Alaska/Western Canada
[PLTGGOESWestRadFAKCAN]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast GOES-West CONUS
[PLTGGOESWestRadC]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast GOES-West MESO1
[PLTGGOESWestRadM1]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast GOES-West MESO2
[PLTGGOESWestRadM2]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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TEST: GOES East Daily Fire Detections - CONUS
[NGFS-DAILY-CONUS-EAST-TEST]
This terrain-corrected product represents cumulative detections at the 2kmABI pixel level in a 24hr UTC day. For performance, serial repeat detections for the same pixel have been removed. The source data are CSV...
This terrain-corrected product represents cumulative detections at the 2km ABI pixel level in a 24hr UTC day. For performance, serial repeat detections for the same pixel have been removed. The source data are CSV files from the link below.
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TEST: GOES East Scene Fire Detections - CONUS
[NGFS-SCENE-CONUS-EAST-TEST]
Pixel-level fire radiative power estimates from the CONUS scan of ABI onGOES East. Pixel corner point locations are terrain corrected. These data update every 5 minutes.
Pixel-level fire radiative power estimates from the CONUS scan of ABI on GOES East. Pixel corner point locations are terrain corrected. These data update every 5 minutes.
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Surface Observations
[MADIS-SurfaceObs]
MADIS Surface Observations (METAR + Mesonet)
MADIS Surface Observations (METAR + Mesonet)
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FEDs-RT-VIIRS-SSECDB-60min-buffer375m
[FEDs-RT-VIIRS-SSECDB-60min-buffer375m]
FEDs-RT-VIIRS-SSECDB-60min-buffer375m
FEDs-RT-VIIRS-SSECDB-60min-buffer375m
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U.S. Electric Power Transmission Lines
[PowerLineDatabase]
Electric power transmission lines in the United States
Electric power transmission lines in the United States
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Wildland Urban Interface by Decade
[WUI-Decade-Change-FULL]
The purpose of this data is to provide a spatially detailed nationalassessment of the Wildland Urban Interface (WUI) and WUI change between 1990 and 2020 across the coterminous U.S. to support wildland fire...
The purpose of this data is to provide a spatially detailed national assessment of the Wildland Urban Interface (WUI) and WUI change between 1990 and 2020 across the coterminous U.S. to support wildland fire research, policy and management, and inquiries into the effects of housing growth on the environment.
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Experimental: NRL PyroCb - Early Warning
[NRL-PyroCB-west-conus-mu]
The US Naval Research Laboratory is developing a pyrocumulonimbus (pyroCb)early warning product. It represents a forecast of pyroCb development potential over the 6-12 hours for individual fire events. PyroCb...
The US Naval Research Laboratory is developing a pyrocumulonimbus (pyroCb) early warning product. It represents a forecast of pyroCb development potential over the 6-12 hours for individual fire events.
PyroCb development is conditional on having significant heat flux from the fire.
Data inputs: atmospheric variables from NOAA-Unique Combined Atmospheric Processing System (NUCAPS) soundings including mid-level moisture and stability variables and low-level moisture and stability variables. It does NOT include fire characteristics such as FRP or size.
Questions, comments, or feedback
Contact the NRL pyroCb Team at pyrocb@us.navy.mil:
David Peterson, Lance Wilson, Ted McHardy, Lauren Porter
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Experimental: NRL PyroCb - Early Warning WNA
[NRL-PyroCB-Western-North-America-mu]
The US Naval Research Laboratory is developing a pyrocumulonimbus (pyroCb)early warning product. It represents a forecast of pyroCb development potential over the 6-12 hours for individual fire events. PyroCb...
The US Naval Research Laboratory is developing a pyrocumulonimbus (pyroCb) early warning product. It represents a forecast of pyroCb development potential over the 6-12 hours for individual fire events.
PyroCb development is conditional on having significant heat flux from the fire.
Data inputs: atmospheric variables from NOAA-Unique Combined Atmospheric Processing System (NUCAPS) soundings including mid-level moisture and stability variables and low-level moisture and stability variables. It does NOT include fire characteristics such as FRP or size.
Questions, comments, or feedback
Contact the NRL pyroCb Team at pyrocb@us.navy.mil:
David Peterson, Lance Wilson, Ted McHardy, Lauren Porter
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NOAA-20 Microphysics
[n20-NAGG-NGFSMicrophysics]
n20-NAGG-NGFSMicrophysics
n20-NAGG-NGFSMicrophysics
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NOAA-21 Microphysics
[n21-NAGG-NGFSMicrophysics]
n21-NAGG-NGFSMicrophysics
n21-NAGG-NGFSMicrophysics
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SNPP Microphysics
[snpp-NAGG-NGFSMicrophysics]
snpp-NAGG-NGFSMicrophysics
snpp-NAGG-NGFSMicrophysics
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Building Counts (CONUS)
[wui-conus-build-count]
Each grid cell has a value indicating how many building centroids fallwithin that grid cell.
Each grid cell has a value indicating how many building centroids fall within that grid cell.
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Building Count Within 1500m of WUI
[wui-conus-build-count-1500m]
Each grid cell has a value indicating how many building centroids fallwithin 1,500 meters of that grid cell. Modified date: 2021-12-09
Each grid cell has a value indicating how many building centroids fall within 1,500 meters of that grid cell. Modified date: 2021-12-09
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Wildland Urban Interface - 1500m
[wui-conus-1500m]
Yellow: 1 - the intermix, where there is at least 50% vegetation coversurrounding buildings Red: 2 - the interface, where buildings are within 2.4 km of a patch of vegetation at least 5 km2 in size that contains at...
Yellow: 1 - the intermix, where there is at least 50% vegetation cover surrounding buildings
Red: 2 - the interface, where buildings are within 2.4 km of a patch of vegetation at least 5 km2 in size that contains at least 75% vegetation.
Both classes required a minimum building density of 6.17 buildings per km2. Maps of intermix and interface WUI were generated using a range of circular neighborhood sizes, based on radius distances from 100 – 1,500 m, to determine building density and vegetation cover on a pixel-by-pixel basis (Bar Massada et al., 2013).
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Wildland Urban Interface and Intermix by Decade
[WUIbyDecade]
The purpose of this data is to provide a spatially detailed nationalassessment of the Wildland Urban Interface (WUI) and WUI change between 1990 and 2020 across the coterminous U.S. to support wildland fire...
The purpose of this data is to provide a spatially detailed national assessment of the Wildland Urban Interface (WUI) and WUI change between 1990 and 2020 across the coterminous U.S. to support wildland fire research, policy and management, and inquiries into the effects of housing growth on the environment.
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