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NOAA’s Multi-Sensor Fire Detection Program Using Environmental Satellites by Donna McNamara 1, George Stephens 1, Rob Fennimore 1, Tim Kasheta 2, Tom Callsen.

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Presentation on theme: "NOAA’s Multi-Sensor Fire Detection Program Using Environmental Satellites by Donna McNamara 1, George Stephens 1, Rob Fennimore 1, Tim Kasheta 2, Tom Callsen."— Presentation transcript:

1 NOAA’s Multi-Sensor Fire Detection Program Using Environmental Satellites by Donna McNamara 1, George Stephens 1, Rob Fennimore 1, Tim Kasheta 2, Tom Callsen 3, Mark Ruminski 1 and Bruce Ramsay 1

2 Background Who are we? NOAA’s National Environmental Satellite Data and Information Service (NESDIS), Office of Satellite Data Processing and Distribution, Satellite Services Division, located in Camp Springs MD. What is special about our product? Our approach is to use multiple sensors to detect fires, and provide the data from individual algorithms, as well as a satellite analyst’s quality controlled product, to the public in a user friendly format. We are here to introduce our web-based GIS fire page and solicit partnerships to improve our product based on customer feedback and requirements.

3 Input Layer – WF-ABBA from GOES Running Wildfire Automated Biomass Burning Algorithm (WF- ABBA) developed by Dr. Elaine Prins 1. Satellite analysts also rely heavily on images from Geostationary satellites. 15-minute imagery allows for rapid detection of hot spots and smoke plumes; animation. The GOES field of view at nadir is large (4x4 km), but the minimum detectable fire size at the sub- satellite point (smoldering at 450K) is approximately.002 km 2. 1. Affiliation – NOAA/NESDIS Office of Research and Applications/Cooperative Institute for Meteorological Satellite Studies (CIMSS) at the Univ. of Wisconsin

4 Input Layer – FIMMA from AVHRR Running Fire Identification Mapping and Monitoring Algorithm developed by Dr. Ivan Csiszar 1. Satellite analysts also view the HRPT (High Resolution Picture Transmission) data from Advanced Very High Resolution Radiometer instrument on polar- orbiting satellites NOAA-12, 14, 15 & 16. First step in FIMMA is to pass data through navigation correction software. When ground points found, accuracy is within 1 km. Field of view at nadir is 1.1 km 2. 1. Affiliation – formerly with the Cooperative Institute for Research in the Atmosphere at the NOAA/NESDIS Office of Research and Applications; currently with Univ. of Maryland. Imagery from Operational Significant Event Imagery (http://www.osei.noaa.gov/)

5 Input Layer – MODIS Satellite Services Division receives Moderate Resolution Imaging Spectroradiometer (MODIS) fire products from NOAA's MODIS Near Real Time Processing System, run by it's sister division – the Information Processing Division. The MODIS instrument flies onboard the NASA TERRA satellite, and the fire algorithm was developed by the MODIS Fire and Thermal Anomalies team 1. Satellite analysts view select images downloaded from the NOAA server or CIMSS (at Univ of Wisc.) Access limited by large size of image files – full access expected fall 2002. Field of view at nadir is 1 km 2 for thermal channels. 1. Dr. Christopher Justice PI, http://modis-fire.gsfc.nasa.gov/

6 Input Layer – DMSP/OLS The Defense Meteorological Satellite Program/Operational Linescan System fire detection algorithm was developed at NOAA's National Geophysical Data Center (NGDC) in Boulder CO. 1 Algorithm is not automated. Ingest of DMSP data and preprocessing/geolocation of the data used to make the fire product originate still at NGDC. Satellite Services Division satellite analysts perform the analysis each morning on previous evening’s passes. They identify clouds, subtract stable lights, and eliminate false detects. Analysis done for western US (west of 95 degrees W.). Analysis stopped during winter and early spring due to large numbers of false detects. Will resume pending successful validation in 2002. 1. Dr. Christopher Elvidge PI, http://www.ngdc.noaa.gov/dmsp/fires/globalfires.html

7 Data Integration: Hazard Mapping System (HMS) The HMS is an interactive processing system that allows trained satellite analysts from SSD’s Satellite Analysis Branch to integrate data from various automated fire detection algorithms and imagery. Suspicious detects from automated layers are deleted. Additional detects, seen on imagery, are added. Smoke is annotated. Contacts with field often made to confirm source of fires. Result – highly accurate, strategic view of hot spots and smoke in the lower 48 US states and Alaska.

8 Web-GIS Fire Page New map server gives users access to layer updates in near real time, as well as quality controlled product from the analyst. Links: http://nhis7.wwb.noaa.gov/website/SSDFire/viewer.htm http://www.ssd.noaa.gov/PS/FIRE/hms-demo.html http://www.ssd.noaa.gov/PS/FIRE/hms-demo.html http://gp16.wwb.noaa.gov/FIRE/fire.html

9 Web-GIS Fire Page User can turn on automated layers, and toggle to legend.

10 Web-GIS Fire Page User zooms in further, turning on rivers, interstates and counties to better locate detects.

11 Web-GIS Fire Page Very close-in zoom reveals large fires in Oregon detected in many WF-ABBA pixels (purple and pink), MODIS pixels (light blue), FIMMA pixels (blue), and confirmed by satellite analyst (red). Large area of smoke is in yellow.

12 Summary NOAA/NESDIS is taking advantage of multiple environmental satellites and the trained eye of the satellite analyst to provide a fire detection product for the conterminous US and Alaska. Detects from automated algorithms are released as data are received, with higher rates of false detects than the analyzed product. Due to high spatial resolution, products best used for large scale (strategic) view of fire activity. Data are available in GIS formats, and via a web-GIS interface. Future products and layers will be added as available. User contacts are sought to assist with 2002 validation efforts and future product requirements definition.


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