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FireTracking/Fire_Events_Data_Suite_New_Fire_Pixels_NRT (MapServer)

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Service Description: <div style='text-align:Left;'><div><div><div style='font-size:12pt'><ul><li><p><span style='font-weight:bold;'>Temporal coverage</span><span>: Current calendar year - Today</span></p></li><li><p><span /><span style='font-weight:bold;'>Data Sources</span><span>: VIIRS Sensor on NOAA-20</span></p></li><li><p><span /><span style='font-weight:bold;'>Time Interval</span><span>: Every 12 Hours</span></p></li><li><p><span /><span style='font-weight:bold;'>Data Latency</span><span>: ~ 9 - 12 hours from satellite overpass </span></p></li><li><p><span style='font-weight:bold;'>Projection</span><span>: EPSG:4326</span></p></li><li><p><span style='font-weight:bold;'>Spatial Extent</span><span>: Contiguous United States, Alaska, and Canada. Portions of Alaska west of 169 Degrees west and portions of Canada north of 75 degrees north are excluded. </span></p></li><li><p><span style='font-weight:bold;'>Resolution</span><span>: Vector data derived from the 375 m nadir resolution of the VIIRS sensors </span></p></li><li><p><span style='font-weight:bold;'>Purpose / use case</span><span>: The FEDS algorithm is an “event-based” approach that tracks the growth and intensity of individual fires every 12 hours and treats them as discrete objects that persist, expand, and evolve together. This tracking strategy allows for detailed monitoring of large fires in space and time as they spread across a landscape. The algorithm clusters VIIRS active fire observations into specific fire events, and then estimates a fire perimeter polygon, the active segment of the perimeter, and metrics for each fire, such as the total estimated area (km^2) and length of the active fire front (km). Each 12-hour increment also includes information on a fire’s mean Fire Radiative Power (FRP), which is a metric that describes fire intensity as estimated by the satellite sensor. This dataset is best used for near real-time situational awareness and retrospective scientific analysis of fire behavior.</span></p></li><li><p><span style='font-weight:bold;'>Notes on Interpretation of the Data</span><span>: As a satellite-based data product, FEDS has lower spatial resolution and accuracy than fire perimeters derived in operational contexts, such as those from airborne imagers. However, FEDS can provide information when other sources are unavailable, and the algorithm runs automatically in fixed 12-hr intervals for all clusters of fire activity greater than 4 km^2. The FEDS algorithm inherits the same uncertainties associated with the VIIRS active fire product. These include potential geolocation errors that can be relevant for interpreting fire locations and fire spread. For example, hot plumes of smoke can generate false positive detections that overestimate the size of the fire at that time step. In addition, active fire detections may be clustered into events that do not align directly with operational definitions of fire events (i.e., FEDS may group multiple agency-designated fires into a single fire event, or consider a single agency-designated fire to be multiple fire events). Finally, clouds or thick smoke may lead to the omission of VIIRS active fire detections, leading to an underestimate of fire activity and fire spread. More information on the interpretation of the VIIRS Active Fire Dataset for fires can be found in the NASA Fire Information for Resource Management System (FIRMS) </span><a href='https://www.earthdata.nasa.gov/data/tools/firms/faq' style='text-decoration:underline;'><span>FAQ</span></a><span>. </span></p></li><li><p><span style='font-weight:bold;'>Source information/ Program Information</span><span>: This dataset was developed as part of the NASA Earth Information Systems (EIS) project. This dataset was generated through the Wildfire Tracking Lab –a collaboration between scientists at NASA Goddard, NASA Langley, NASA Marshall, University of California Irvine, and University of Maryland. </span></p></li><li><p><span style='font-weight:bold;'>Citation</span><span>: Chen et al. “California wildfire spread derived using VIIRS satellite observations and an object-based tracking system.” Scientific data 9.1 (2022): 249 https://doi.org/10.1038/s41597-022-01343-0.</span></p></li><li><p><span style='font-weight:bold;'>Repository</span><span>: The underlying algorithm that generates these data layers is hosted and developed at the </span><a href='https://github.com/Earth-Information-System/fireatlas' style='text-decoration:underline;'><span>Fire Events Data Suite repository</span></a><span>. </span></p></li><li><p><span style='font-weight:bold;'>Parameters</span><span>:</span></p><ul><li><p><span>Column Name: t</span></p><ul><li><p><span>Description: Time of VIIRS detection. Data collected during approximately 1:30 AM and 1:30 PM local solar time overpasses. The time component of the datetime is assigned a local time of 00:00:00 for 1:30 AM overpasses, and 12:00:00 for 1:30 PM overpasses. Unit is Datetime. yyyy-mm-ddThh:mm:ss. Time component is in local solar time. Date component is the UTC date. UTC date will match local date for all of CONUS and Canada, but will not match for Alaska. </span></p></li></ul></li><li><p><span>Column Name: region</span></p><ul><li><p><span>Description: Descriptive name of larger region where tracking is occurring.</span></p></li></ul></li><li><p><span>Column Name: fireid</span></p><ul><li><p><span>Description: Fire ID. Unique for each fire within a given region. Unit is Numeric ID</span></p></li></ul></li><li><p><span>Column: geometry</span></p><ul><li><p><span>Description: The location of the pixels. Unit is Geometry. CRS is EPSG:4326. </span></p></li></ul></li><li><p><span>Column: Primary Key</span></p><ul><li><p><span>Description: Globally unique identifier for a given layer entry. This key is formatted by [region]|[fireid]|[timestamp]. Unitless.</span></p></li></ul></li></ul></li><li><p><span style='font-weight:bold;'>Alternate Forms Of Data Access</span><span>: This data can also be accessed through </span><a href='https://openveda.cloud/api/features/' target='_blank' style='text-decoration:underline;'><span>an API</span></a><span>. Documentation for the API can be found </span><a href='https://docs.openveda.cloud/user-guide/notebooks/tutorials/mapping-fires.html' target='_blank' style='text-decoration:underline;'><span>here</span></a><span>. The API distributes data in open source data formats. </span></p></li></ul><ul><li><p><span style='font-weight:bold;'>Contact</span><span>: For inquiries about service performance please contact support@earthdata.nasa.gov or post/view questions on </span><a href='https://forum.earthdata.nasa.gov/' style='text-decoration:underline;'><span>the Earthdata Forum</span></a><span>. For questions about the data, please contact the science team with </span><a href='https://forms.gle/vHX7FvHhamDVRDHn9' style='text-decoration:underline;'><span>this form</span></a><span>.</span></p></li></ul></div></div></div></div>

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Layers: Description: Temporal coverage: Current calendar year - TodayData Sources: VIIRS Sensor on NOAA-20Time Interval: Every 12 HoursData Latency: ~ 9 - 12 hours from satellite overpass Projection: EPSG:4326Spatial Extent: Contiguous United States, Alaska, and Canada. Portions of Alaska west of 169 Degrees west and portions of Canada north of 75 degrees north are excluded. Resolution: Vector data derived from the 375 m nadir resolution of the VIIRS sensors Purpose / use case: The FEDS algorithm is an “event-based” approach that tracks the growth and intensity of individual fires every 12 hours and treats them as discrete objects that persist, expand, and evolve together. This tracking strategy allows for detailed monitoring of large fires in space and time as they spread across a landscape. The algorithm clusters VIIRS active fire observations into specific fire events, and then estimates a fire perimeter polygon, the active segment of the perimeter, and metrics for each fire, such as the total estimated area (km^2) and length of the active fire front (km). Each 12-hour increment also includes information on a fire’s mean Fire Radiative Power (FRP), which is a metric that describes fire intensity as estimated by the satellite sensor. This dataset is best used for near real-time situational awareness and retrospective scientific analysis of fire behavior.Notes on Interpretation of the Data: As a satellite-based data product, FEDS has lower spatial resolution and accuracy than fire perimeters derived in operational contexts, such as those from airborne imagers. However, FEDS can provide information when other sources are unavailable, and the algorithm runs automatically in fixed 12-hr intervals for all clusters of fire activity greater than 4 km^2. The FEDS algorithm inherits the same uncertainties associated with the VIIRS active fire product. These include potential geolocation errors that can be relevant for interpreting fire locations and fire spread. For example, hot plumes of smoke can generate false positive detections that overestimate the size of the fire at that time step. In addition, active fire detections may be clustered into events that do not align directly with operational definitions of fire events (i.e., FEDS may group multiple agency-designated fires into a single fire event, or consider a single agency-designated fire to be multiple fire events). Finally, clouds or thick smoke may lead to the omission of VIIRS active fire detections, leading to an underestimate of fire activity and fire spread. More information on the interpretation of the VIIRS Active Fire Dataset for fires can be found in the NASA Fire Information for Resource Management System (FIRMS) FAQ. Source information/ Program Information: This dataset was developed as part of the NASA Earth Information Systems (EIS) project. This dataset was generated through the Wildfire Tracking Lab –a collaboration between scientists at NASA Goddard, NASA Langley, NASA Marshall, University of California Irvine, and University of Maryland. Citation: Chen et al. “California wildfire spread derived using VIIRS satellite observations and an object-based tracking system.” Scientific data 9.1 (2022): 249 https://doi.org/10.1038/s41597-022-01343-0.Repository: The underlying algorithm that generates these data layers is hosted and developed at the Fire Events Data Suite repository. Parameters:Column Name: tDescription: Time of VIIRS detection. Data collected during approximately 1:30 AM and 1:30 PM local solar time overpasses. The time component of the datetime is assigned a local time of 00:00:00 for 1:30 AM overpasses, and 12:00:00 for 1:30 PM overpasses. Unit is Datetime. yyyy-mm-ddThh:mm:ss. Time component is in local solar time. Date component is the UTC date. UTC date will match local date for all of CONUS and Canada, but will not match for Alaska. Column Name: regionDescription: Descriptive name of larger region where tracking is occurring.Column Name: fireidDescription: Fire ID. Unique for each fire within a given region. Unit is Numeric IDColumn: geometryDescription: The location of the pixels. Unit is Geometry. CRS is EPSG:4326. Column: Primary KeyDescription: Globally unique identifier for a given layer entry. This key is formatted by [region]|[fireid]|[timestamp]. Unitless.Alternate Forms Of Data Access: This data can also be accessed through an API. Documentation for the API can be found here. The API distributes data in open source data formats. Contact: For inquiries about service performance please contact support@earthdata.nasa.gov or post/view questions on the Earthdata Forum. For questions about the data, please contact the science team with this form.

Service Item Id: 72141743cb724d1a80446833e7d51a43

Copyright Text: Wildfire Tracking Lab, Chen et al. “California wildfire spread derived using VIIRS satellite observations and an object-based tracking system.” Scientific data 9.1 (2022): 249. Thumbnail image by NASA's Scientific Visualization Studio and Cindy Starr.

Spatial Reference: 4326  (4326)  LatestVCSWkid(0)


Single Fused Map Cache: false

Initial Extent: Full Extent: Time Info: Units: esriDecimalDegrees

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Document Info: Supports Dynamic Layers: true

Resampling: false

MaxRecordCount: 2000

MaxSelectionCount: 2000

MaxImageHeight: 4096

MaxImageWidth: 4096

Supported Query Formats: JSON, geoJSON, PBF

Supports Query Data Elements: true

Min Scale: 0

Max Scale: 0

Supports Datum Transformation: true



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