


{"id":70078,"date":"2026-08-30T10:02:55","date_gmt":"2026-08-30T09:02:55","guid":{"rendered":"https:\/\/dzwatch.dz\/?p=70078"},"modified":"2026-08-30T10:02:55","modified_gmt":"2026-08-30T09:02:55","slug":"dzw-a0df119ce15ad5de5be80f5f12d629d3cb64a81b","status":"publish","type":"post","link":"https:\/\/dzwatch.dz\/?p=70078","title":{"rendered":"National Research Develops Fire Prevention Tools"},"content":{"rendered":"<p>Algerian researchers have developed sophisticated scientific models and maps to predict forest fire risks, offering new tools for prevention and management across the country. One study, conducted by researchers from the Natural Resources and Sensitive Environments Management Laboratory at Oum El Bouaghi University and published in the journal &quot;Trees, Forests and People,&quot; focused on the Djebel El Wahch massif in Constantine province. This research identified critical risk factors including dry vegetation, high temperatures, favorable winds, sloped terrain, and human activity. Utilizing data from climate monitoring stations, satellite imagery, and Geographic Information Systems (GIS), the team applied a mathematical technique known as &quot;fuzzy logic&quot; to integrate these diverse elements, resulting in predictive maps that indicate varying levels of fire susceptibility and provide a valuable &quot;fire readiness map&quot; for authorities.<\/p>\n<p>A second study, undertaken by researchers from the Geomorphology and Geological Risks Laboratory at the Faculty of Agricultural Sciences and Technology at the University of Science and Technology in Algiers, concentrated on El Tarf province, a region frequently affected by fires. This research incorporated artificial intelligence tools and analyzed satellite images from 1995 to 2024 to create a historical fire map. The researchers then gathered data on ten distinct factors across four categories: terrain (altitude, landform), vegetation (density, type), soil (type, organic carbon content), and climate (rainfall, wind). By training four machine learning models with this data, the &quot;Random Forest&quot; model emerged as the most effective in identifying areas prone to fires. Key risk factors identified included altitude, vegetation cover, wind speed, and low rainfall, leading to the production of high-resolution maps that can aid monitoring, prevention, and early preparedness efforts.<\/p>\n<p>These innovative Algerian studies challenge the traditional view that high temperatures are the sole cause of forest fires, highlighting instead a complex interplay of climatic, vegetative, topographical, and human factors. Dr. Majdi Allam, a consultant for the global climate program and Secretary-General of the Union of Arab Environmental Experts, underscored the global applicability of these models, stating they address a fundamental misconception about forest fires. He emphasized that understanding these multi-faceted risks enables nations to prepare proactively, asserting that prevention is superior to relying solely on increased firefighting capacities, as even advanced fire brigades face difficulties once large blazes ignite.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Algerian scientific research has developed advanced forest fire risk maps, utilizing sophisticated data analysis and artificial intelligence to enhance national prevention and preparedness efforts against environmental threats.<\/p>\n","protected":false},"author":1,"featured_media":70077,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"cybocfi_hide_featured_image":"","iawp_total_views":1,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-70078","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-algeria"],"acf":[],"_links":{"self":[{"href":"https:\/\/dzwatch.dz\/index.php?rest_route=\/wp\/v2\/posts\/70078","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dzwatch.dz\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dzwatch.dz\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dzwatch.dz\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/dzwatch.dz\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=70078"}],"version-history":[{"count":0,"href":"https:\/\/dzwatch.dz\/index.php?rest_route=\/wp\/v2\/posts\/70078\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/dzwatch.dz\/index.php?rest_route=\/wp\/v2\/media\/70077"}],"wp:attachment":[{"href":"https:\/\/dzwatch.dz\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=70078"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dzwatch.dz\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=70078"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dzwatch.dz\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=70078"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}