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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>ISPRS - 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/isprs-archives-XLII-4-W18-475-2019</article-id>
<title-group>
<article-title>INTELLIGENT MANAGEMENT OCCURRENCE AND SPREAD OF FRONT FIRE IN GIS BY USING CELLULAR AUTOMATA. CASE STUDY: GOLESTAN FOREST</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Hesam</surname>
<given-names>S.</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>Valizadeh Kamran</surname>
<given-names>K.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Dept. GIS Engineering, University Islamic Azad, Tabriz, Iran</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Dept. Remote Sensing and GIS, University Tabriz, Tabriz, Iran</addr-line>
</aff>
<pub-date pub-type="epub">
<day>18</day>
<month>10</month>
<year>2019</year>
</pub-date>
<volume>XLII-4/W18</volume>
<fpage>475</fpage>
<lpage>481</lpage>
<permissions>
<copyright-statement>Copyright: © 2019 S. Hesam</copyright-statement>
<copyright-year>2019</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-4-W18-475-2019.html">This article is available from https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-4-W18-475-2019.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-4-W18-475-2019.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-4-W18-475-2019.pdf</self-uri>
<abstract>
<p>Jungles are a country’s treasures, and the survival of humans and the earth depends on the oxygen that they produce (trees). Three million hectares of jungle are destroyed each year as a result of natural or human-caused wildfires. The massive wildfires occurring in the world confirms that this destructive phenomenon leaves irreconcilable effects on regional ecosystems, vegetation and wildlife; presenting more effective approaches for preventing and managing this complex phenomenon has therefore always been the focus of environmental managers and planners. In other words, it is necessary to model the spread of wildfires, which can be used for utilizing forces and equipment most effectively. Cellular automaton is considered a very simple yet highly effective method that is very capable of modeling dynamic events, like urban development, spread of wildfires, disease outbreaks and others. This study used layers such as height, slope, aspect, vegetation density, roads, rivers and climate as its basis. This was a case study of the Golestan region’s jungles, which calculated the general accuracy of the wildfire spread model to be 65 percent, and the Cohen’s kappa coefficient to be 59 percent.</p>
</abstract>
<counts><page-count count="7"/></counts>
</article-meta>
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