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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Archives</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9034</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/isprsarchives-XL-1-161-2014</article-id>
<title-group>
<article-title>Utilizing Multi-Sensor Fire Detections to Map Fires in the United States</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Howard</surname>
<given-names>S. M.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Picotte</surname>
<given-names>J. J.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Coan</surname>
<given-names>M. J.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>U.S. Geological Survey (USGS) EROS Center, 47914 252nd Street, Sioux Falls, South Dakota, USA</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>ASRC Federal InuTeq, EROS Center, 47914 252nd Street, Sioux Falls, South Dakota, USA</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Stinger Ghaffarian Technologies, EROS Center, 47914 252nd Street , Sioux Falls, South Dakota, USA</addr-line>
</aff>
<pub-date pub-type="epub">
<day>07</day>
<month>11</month>
<year>2014</year>
</pub-date>
<volume>XL-1</volume>
<fpage>161</fpage>
<lpage>166</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2014 S. M. Howard et al.</copyright-statement>
<copyright-year>2014</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/3.0/">https://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions>
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<abstract>
<p>In 2006, the Monitoring Trends in Burn Severity (MTBS) project began a cooperative effort between the US Forest Service (USFS)
and the U.S.Geological Survey (USGS) to map and assess burn severity all large fires that have occurred in the United States since
1984. Using Landsat imagery, MTBS is mandated to map wildfire and prescribed fire that meet specific size criteria: greater than
1000 acres in the west and 500 acres in the east, regardless of ownership. Relying mostly on federal and state fire occurrence
records, over 15,300 individual fires have been mapped. While mapping recorded fires, an additional 2,700 &quot;unknown&quot; or
undocumented fires were discovered and assessed. It has become apparent that there are perhaps thousands of undocumented fires in
the US that are yet to be mapped. Fire occurrence records alone are inadequate if MTBS is to provide a comprehensive accounting
of fire across the US. Additionally, the sheer number of fires to assess has overwhelmed current manual procedures.
To address these problems, the National Aeronautics and Space Administration (NASA) Applied Sciences Program is helping to
fund the efforts of the USGS and its MTBS partners (USFS, National Park Service) to develop, and implement a system to
automatically identify fires using satellite data. In near real time, USGS will combine active fire satellite detections from MODIS,
AVHRR and GOES satellites with Landsat acquisitions. Newly acquired Landsat imagery will be routinely scanned to identify
freshly burned area pixels, derive an initial perimeter and tag the burned area with the satellite date and time of detection. Landsat
imagery from the early archive will be scanned to identify undocumented fires. Additional automated fire assessment processes will
be developed. The USGS will develop these processes using open source software packages in order to provide freely available tools
to local land managers providing them with the capability to assess fires at the local level.</p>
</abstract>
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