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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">vfuzeml</journal-id><journal-title-group><journal-title xml:lang="ru">Вестник Северо-Восточного федерального университета им. М.К. Аммосова. Vestnik of North-Eastern Federal University. Серия «Науки о Земле». Earth Sciences</journal-title><trans-title-group xml:lang="en"><trans-title>Vestnik of North-Eastern Federal University Series "Earth Sciences"</trans-title></trans-title-group></journal-title-group><issn pub-type="epub">2587-8751</issn><publisher><publisher-name>Северо-Восточный федеральный университет имени М.К.Аммосова</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.25587/SVFU.2020.17.61132</article-id><article-id custom-type="elpub" pub-id-type="custom">vfuzeml-39</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>КАРТОГРАФИЯ И ГИС</subject></subj-group></article-categories><title-group><article-title>ДОЛГОСРОЧНОЕ ГЕОИНФОРМАЦИОННОЕ МОДЕЛИРОВАНИЕ РИСКА ЛЕСНЫХ ПОЖАРОВ В РЕСПУБЛИКЕ САХА (РОССИЙСКАЯ ФЕДЕРАЦИЯ)</article-title><trans-title-group xml:lang="en"><trans-title>LONG-TERM GIS MODELING OF THE FOREST FIRE RISK IN THE SAKHA REPUBLIC (YAKUTIA) (RUSSIAN FEDERATION)</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Янец</surname><given-names>П.</given-names></name><name name-style="western" xml:lang="en"><surname>Janiec</surname><given-names>P.</given-names></name></name-alternatives><email xlink:type="simple">szh.gadal@s-vfu.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Гадаль</surname><given-names>С.</given-names></name><name name-style="western" xml:lang="en"><surname>Gadal</surname><given-names>S.</given-names></name></name-alternatives><email xlink:type="simple">szh.gadal@s-vfu.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Университет Экс-Марсель; СВФУ им. М.К. Аммосова</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Aix-Marseille University; M.K. Ammosov North-Eastern Federal University</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2020</year></pub-date><pub-date pub-type="epub"><day>22</day><month>04</month><year>2022</year></pub-date><volume>0</volume><issue>1</issue><fpage>38</fpage><lpage>48</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Янец П., Гадаль С., 2022</copyright-statement><copyright-year>2022</copyright-year><copyright-holder xml:lang="ru">Янец П., Гадаль С.</copyright-holder><copyright-holder xml:lang="en">Janiec P., Gadal S.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.vnzsvfu.ru/jour/article/view/39">https://www.vnzsvfu.ru/jour/article/view/39</self-uri><abstract><p>В статье рассматриваются особенности лесных пожаров в России и Якутии, их роль в глобальном потеплении климата и факторы, влияющие на лесные пожары. Предлагается структура ГИС для мониторинга лесных пожаров. Исходными материалами были спутниковые снимки различного пространственного и спектрального разрешения (Landsat 5, Modis TERRA, GMTED2010, VIIRS), векторные данные (NextGIS), различные метеорологические данные (WORLDCLIM), результаты экспедиций и обследования местного населения. Впервые были разработаны структура и ГИС база данных пожаров за 2001-2018 годы для территории Якутии, которые содержат информацию о рельефе, климате, горючих материалах и антропогенной деятельности. Впервые на основе анализа литературных источников и мирового опыта оценки риска лесных пожаров были разработаны метод определения факторов, влияющих на пожарный риск в макро и микро масштабе, а также методика определения этого риска на территории Республики Саха (Якутия), используя искусственный интеллект и машинное обучение.</p></abstract><trans-abstract xml:lang="en"><p>The article discusses the features of forest ﬁres in Russia and Yakutia, their role in global climate warming, factors affecting forest ﬁres, suggests a GIS structure for monitoring forest ﬁres. The source material was satellite images of different spatial and spectral resolution (Landsat 5, Modis TERRA, GMTED2010, VIIRS), vector data (NextGIS), various meteorological data (WORLDCLIM), the results of expeditions and surveys of the local population. For the ﬁrst time, a structure and a GIS database of ﬁres for 2001-2018 were developed for the territory of Yakutia, which contains information about the relief, climate, combustible materials, and anthropogenic activity. For the ﬁrst time, based on an analysis of literary sources and world experience of assessing the risk of forest ﬁres, a method was developed for determining macroeconomic and microscale factors inﬂuencing ﬁre risk as well as a method for determining this risk in the Republic of Sakha (Yakutia) using artiﬁcial intelligence and machine learning.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>лесные пожары</kwd><kwd>дистанционное зондирование</kwd><kwd>моделирование рисков лесных пожаров</kwd><kwd>ГИС</kwd><kwd>мультимасштабный анализ</kwd><kwd>Якутия</kwd><kwd>Сибирь</kwd><kwd>искусственный интеллект</kwd><kwd>машинное обучение</kwd><kwd>случайный лес</kwd></kwd-group><kwd-group xml:lang="en"><kwd>MaxEnt</kwd><kwd>wildﬁres</kwd><kwd>remote sensing</kwd><kwd>risk modeling</kwd><kwd>GIS</kwd><kwd>multi-scale analysis</kwd><kwd>Yakutia</kwd><kwd>Siberia</kwd><kwd>artiﬁcial intelligence</kwd><kwd>machine learning</kwd><kwd>random forest</kwd><kwd>MaxEnt</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Kasischke, E.S. 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