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            <front>

                <journal-meta>
                                                                <journal-id>ajfr</journal-id>
            <journal-title-group>
                                                                                    <journal-title>Anadolu Orman Araştırmaları Dergisi</journal-title>
            </journal-title-group>
                            <issn pub-type="ppub">1309-856X</issn>
                                        <issn pub-type="epub">2564-7660</issn>
                                                                                            <publisher>
                    <publisher-name>Cankiri Karatekin University</publisher-name>
                </publisher>
                    </journal-meta>
                <article-meta>
                                        <article-id pub-id-type="doi">10.53516/ajfr.1302553</article-id>
                                                                <article-categories>
                                            <subj-group  xml:lang="en">
                                                            <subject>Engineering</subject>
                                                    </subj-group>
                                            <subj-group  xml:lang="tr">
                                                            <subject>Mühendislik</subject>
                                                    </subj-group>
                                    </article-categories>
                                                                                                                                                        <title-group>
                                                                                                                        <article-title>Akdeniz bölgesi’ndeki orman yangınlarının uzaktan algılama ve coğrafi bilgi sistemleri kullanılarak değerlendirilmesi: Mersin ili Silifke ilçesi örneği</article-title>
                                                                                                                                                                                                <trans-title-group xml:lang="en">
                                    <trans-title>Evaluation of forest fires using remote sensing and geographic information systems: a case study of Mersin province, Silifke district</trans-title>
                                </trans-title-group>
                                                                                                    </title-group>
            
                                                    <contrib-group content-type="authors">
                                                                        <contrib contrib-type="author">
                                                                    <contrib-id contrib-id-type="orcid">
                                        https://orcid.org/0000-0003-4569-888X</contrib-id>
                                                                <name>
                                    <surname>Çelik</surname>
                                    <given-names>Mehmet Özgür</given-names>
                                </name>
                                                                    <aff>MERSİN ÜNİVERSİTESİ</aff>
                                                            </contrib>
                                                    <contrib contrib-type="author">
                                                                    <contrib-id contrib-id-type="orcid">
                                        https://orcid.org/0000-0003-0856-5594</contrib-id>
                                                                <name>
                                    <surname>Fidan</surname>
                                    <given-names>Doğa</given-names>
                                </name>
                                                                    <aff>MERSİN ÜNİVERSİTESİ</aff>
                                                            </contrib>
                                                    <contrib contrib-type="author">
                                                                    <contrib-id contrib-id-type="orcid">
                                        https://orcid.org/0000-0003-3005-8011</contrib-id>
                                                                <name>
                                    <surname>Ulvi</surname>
                                    <given-names>Ali</given-names>
                                </name>
                                                                    <aff>MERSİN ÜNİVERSİTESİ</aff>
                                                            </contrib>
                                                    <contrib contrib-type="author">
                                                                    <contrib-id contrib-id-type="orcid">
                                        https://orcid.org/0000-0002-2664-6251</contrib-id>
                                                                <name>
                                    <surname>Yakar</surname>
                                    <given-names>Murat</given-names>
                                </name>
                                                                    <aff>MERSİN ÜNİVERSİTESİ</aff>
                                                            </contrib>
                                                                                </contrib-group>
                        
                                        <pub-date pub-type="pub" iso-8601-date="20240101">
                    <day>01</day>
                    <month>01</month>
                    <year>2024</year>
                </pub-date>
                                        <volume>9</volume>
                                        <issue>2</issue>
                                        <fpage>116</fpage>
                                        <lpage>125</lpage>
                        
                        <history>
                                    <date date-type="received" iso-8601-date="20230525">
                        <day>05</day>
                        <month>25</month>
                        <year>2023</year>
                    </date>
                                                    <date date-type="accepted" iso-8601-date="20231228">
                        <day>12</day>
                        <month>28</month>
                        <year>2023</year>
                    </date>
                            </history>
                                        <permissions>
                    <copyright-statement>Copyright © 2015, Anatolian Journal of Forest Research</copyright-statement>
                    <copyright-year>2015</copyright-year>
                    <copyright-holder>Anatolian Journal of Forest Research</copyright-holder>
                </permissions>
            
                                                                                                <abstract><p>Orman yangınları çevreyi ve canlıları olumsuz etkileyen olaylardır. Bu yangınların önlenmesi ile yangın sonrası ağaçlandırma ve koruma stratejilerinin geliştirilmesi için, hasarın boyutunun belirlenmesi ve yanma şiddetinin hızlı bir şekilde araştırılması gereklidir. Uzaktan algılama (UA) yangından etkilenen bölgelerin ve yanma şiddetinin haritalanmasında Coğrafi Bilgi Sistemleri (CBS) ile birlikte sıklıkla kullanılmaktadır. Bu çalışmada, 2021 yılında Mersin ili Silifke içesinde meydana gelen orman yangını incelenmiştir. Sahanın yangın öncesi ve sonrasına ait Sentinel-2A ve Landsat 8 OLI uydu görüntüleri yardımıyla NDVI (Normalize Fark Vejetasyon İndeksi) ve NBR (Normalize Yanma Şiddeti) indeksleri hesaplanmıştır. Elde edilen indeks haritalarından fark haritaları oluşturulmuş, yangın sonrasındaki arazi örtüsündeki değişim ve yanma şiddeti belirlenmiştir. Buna göre toplam yanan alanlar 2324,71 hektardır. Yangına “yüksek” derecede maruz kalan alanlar çalışma alanın %27,72’sini (644,44 ha), “orta” derecede yanan alanlar %66,72’sini (1538,16 ha) ve “düşük” seviyede yanan alanlar ise %6,11’ini (142,11 ha) oluşturmaktadır. Ayrıca, EFFIS veri tabanından elde edilen çalışma alanına ait yangın verisiyle de yapılan analizin doğrulaması gerçekleştirilmiştir. Bu işlem için alıcı işletim karakteristik (receiver operating characteristic – ROC) eğrisi kullanılmış ve eğri altındaki alan (area under the curve - AUC) değeri 0,973 olarak hesaplanmıştır. Çıkan sonuçlar, Orman Genel Müdürlüğü (OGM) yetkililerine ve diğer karar vericilere sürdürülebilir arazi yönetimi uygulamaları konusunda yardımcı olmayı amaçlamaktadır.</p></abstract>
                                                                                                                                    <trans-abstract xml:lang="en">
                            <p>Forest fires are events that negatively affect the environment and living creatures. In order to prevent these fires, and to develop post-fire regeneration techniques, it is vital to promptly evaluate the damage amount and to investigate the fire&#039;s severity. Remote sensing (RS) is frequently used with Geographic Information Systems (GIS) to map fire-affected areas and fire intensity. In this study, the forest fire in Silifke district in Mersin took place in 2021 was examined. Before and following the fire, NDVI (Normalized Difference Vegetation Index) and NBR (Normalized Burn Ratio) indexes were derived using Sentinel-2A and Landsat 8 OLI satellite images. The index maps were used to generate difference maps, and the change in land cover after the fire, as well as the intensity of the fire, was determined. Accordingly, the total area burned is 2324.71 hectares. The study area is made up of 27.72% (644.44 ha) of &quot;high&quot; fire areas, 66.72% (1538.16 ha) of &quot;moderate&quot; fire areas, and 6.11 (142.11 ha) of &quot;low&quot; fire areas. Furthermore, the analysis was validated using fire data from the EFFIS database for the research area. The receiver operating characteristic (ROC) curve was employed for this operation, and area under the curve (AUC) value was calculated at 0.973. The conclusions are intended to assist the General Directorate of Forestry (GDF) and other decision-makers to practice sustainable land management.</p></trans-abstract>
                                                            
            
                                                            <kwd-group>
                                                    <kwd>Orman yangını</kwd>
                                                    <kwd>  Landsat 8 OLI</kwd>
                                                    <kwd>  Sentinel-2A</kwd>
                                                    <kwd>  Sürdürülebilir orman yönetimi</kwd>
                                            </kwd-group>
                                                        
                                                                            <kwd-group xml:lang="en">
                                                    <kwd>Forest fire</kwd>
                                                    <kwd>  Landsat 8 OLI</kwd>
                                                    <kwd>  Sentinel-2A</kwd>
                                                    <kwd>  Sustainable forest management</kwd>
                                            </kwd-group>
                                                                                                            </article-meta>
    </front>
    <back>
                            <ref-list>
                                    <ref id="ref1">
                        <label>1</label>
                        <mixed-citation publication-type="journal">Amjad, D., Kausar, S., Waqar, R., Sarwar, F., 2019. Land cover change analysis and impacts of deforestation on the climate of district Mansehra, Pakistan. Journal of Biodiversity and Environmental Sciences 14(6), 103-113.</mixed-citation>
                    </ref>
                                    <ref id="ref2">
                        <label>2</label>
                        <mixed-citation publication-type="journal">Arca, D., Hacısalihoğlu, M., Kutoğlu, Ş. H., 2020. Producing forest fire susceptibility map via multi-criteria decision analysis and frequency ratio methods. Natural Hazards 104, 73-89.</mixed-citation>
                    </ref>
                                    <ref id="ref3">
                        <label>3</label>
                        <mixed-citation publication-type="journal">Arisanty, D., Adyatma, S., Muhaimin, M., Nursaputra, A., 2019. Landsat 8 OLI TIRS Imagery Ability for Monitoring Post Forest Fire Changes. Pertanika Journal of Science &amp; Technology, 27(3), 1105-1120.</mixed-citation>
                    </ref>
                                    <ref id="ref4">
                        <label>4</label>
                        <mixed-citation publication-type="journal">Arunachalam, M., Joshua, R. M., Kochuparampil, A. J., Saravanavel, J., 2023. ArcOLITIRS: A toolbox for radiometric calibration and surface temperature estimation from Landsat 8 products in ArcGIS environment. Journal of the Indian Society of Remote Sensing, 51(3), 453-468.</mixed-citation>
                    </ref>
                                    <ref id="ref5">
                        <label>5</label>
                        <mixed-citation publication-type="journal">Bekçi, R. N., Kuşak, L., 2022. Mekânsal çözünürlüğün güneşlenme potansiyeline etkisi. Türkiye İnsansız Hava Araçları Dergisi 4(1), 46-51.</mixed-citation>
                    </ref>
                                    <ref id="ref6">
                        <label>6</label>
                        <mixed-citation publication-type="journal">Bekçi, R. N., Zorlu, Ö., Menekşe, E., 2022. Regression analysis and use of artificial neural networks in housing valuation forecasting: case example of Güvenevler neighbourhood in Mersin. Estate Development with Risk Analysis, Advanced GIS 2(1), 24-32.</mixed-citation>
                    </ref>
                                    <ref id="ref7">
                        <label>7</label>
                        <mixed-citation publication-type="journal">Bentekhici, N., Bellal, SA., Zegrar, A., 2020. Contribution of remote sensing and GIS to mapping the fire risk of Mediterranean forest case of the forest massif of Tlemcen (North-West Algeria). Natural Hazards 104(1), 811–831.</mixed-citation>
                    </ref>
                                    <ref id="ref8">
                        <label>8</label>
                        <mixed-citation publication-type="journal">Bustillo Sánchez, M., Tonini, M., Mapelli, A., Fiorucci, P., 2021. Spatial assessment of wildfires susceptibility in SantaCruz (Bolivia) using random forest. Geosciences 11(5), 224.</mixed-citation>
                    </ref>
                                    <ref id="ref9">
                        <label>9</label>
                        <mixed-citation publication-type="journal">Chuvieco, E., 2009. Earth Observation of Wildland Fires in Mediterranean Ecosystems (p. 257). Springer, Berlin / Heidelberg.</mixed-citation>
                    </ref>
                                    <ref id="ref10">
                        <label>10</label>
                        <mixed-citation publication-type="journal">Coruhlu, Y. E., Baser, V., Yildiz, O., 2021. Object-based geographical data model for determination of the cemetery sites using SWOT and AHP integration. Survey Review 53(377), 108-121.</mixed-citation>
                    </ref>
                                    <ref id="ref11">
                        <label>11</label>
                        <mixed-citation publication-type="journal">Coruhlu, Y. E., Uzun, B., Yildiz, O., 2020. Zoning plan-based legal confiscation without expropriation in Turkey in light of ECHR decisions. Land use Policy 95, 104598.</mixed-citation>
                    </ref>
                                    <ref id="ref12">
                        <label>12</label>
                        <mixed-citation publication-type="journal">Çakır, M., 2017. Toprak faunasının kurak ekosistemlerdeki görevleri. Anadolu Orman Araştırmaları Dergisi,3(1),67-78.</mixed-citation>
                    </ref>
                                    <ref id="ref13">
                        <label>13</label>
                        <mixed-citation publication-type="journal">Çelik, M. A., Gülersoy, A. E., 2018. Climate classification and drought analysis of Mersin. Manisa Celal Bayar University Journal of Social Sciences 16(1), 1-26.</mixed-citation>
                    </ref>
                                    <ref id="ref14">
                        <label>14</label>
                        <mixed-citation publication-type="journal">Çolak, E., Sunar, F., 2020. Evaluation of forest fire risk in the Mediterranean Turkish forests: A case study of Menderes region, Izmir. International journal of disaster risk reduction, 45, 101479.</mixed-citation>
                    </ref>
                                    <ref id="ref15">
                        <label>15</label>
                        <mixed-citation publication-type="journal">Çoruhlu, Y. E., Çelik, M. Ö., 2022. Protected area geographical management model from design to implementation for specially protected environment area. Land Use Policy 122, 106357.</mixed-citation>
                    </ref>
                                    <ref id="ref16">
                        <label>16</label>
                        <mixed-citation publication-type="journal">Das, J., Mahato, S., Joshi, P. K., Liou, Y. A., 2023. Forest fire susceptibility zonation in Eastern India using statistical and weighted modelling approaches. Remote Sensing, 15(5), 1340.</mixed-citation>
                    </ref>
                                    <ref id="ref17">
                        <label>17</label>
                        <mixed-citation publication-type="journal">Dilekçi, S., Marangoz, A. M., Ateşoğlu, A., 2021). Zonguldak ve Ereğli Orman İşletme Müdürlükleri orman yangını risk alanlarının belirlenmesi. Geomatik, 6(1), 44-53.</mixed-citation>
                    </ref>
                                    <ref id="ref18">
                        <label>18</label>
                        <mixed-citation publication-type="journal">Doğan, Y., Yakar, M., 2018. GIS and three-dimensional modeling for cultural heritages. International Journal of Engineering and Geosciences 3(2), 50-55.</mixed-citation>
                    </ref>
                                    <ref id="ref19">
                        <label>19</label>
                        <mixed-citation publication-type="journal">Down to Earth, 2022. Down to Earth state of the world’s forests https://www.downtoearth.org.in/news/forests/state-of-the-world-s-forests-2022-10-of-total-forest-area-on-earth-lost-in-30-years-82658.
Duran, C., 2014. Mersin ilindeki orman yangınlarının başlangıç noktalarına göre mekânsal analizi (2001-2013). Ormancılık Araştırma Dergisi 1(1 A), 38-49.</mixed-citation>
                    </ref>
                                    <ref id="ref20">
                        <label>20</label>
                        <mixed-citation publication-type="journal">EFFIS, 2023a. European Forest Fire Information System. effis.jrc.ec.europa.eu/apps/effis.statistics/estimates (Erişildi 03.01.2023).</mixed-citation>
                    </ref>
                                    <ref id="ref21">
                        <label>21</label>
                        <mixed-citation publication-type="journal">EFFIS, 2023b. European Forest Fire Information System. https://effis.jrc.ec.europa.eu/applications/data-and-services (Erişildi 16.11.2023).</mixed-citation>
                    </ref>
                                    <ref id="ref22">
                        <label>22</label>
                        <mixed-citation publication-type="journal">Ercan, B., Özdilim, S., Avcı, M. G., 2023. Orman yangınlarına ilk müdahale ekiplerinin yerleşim planlaması: Aliağa-İzmir örneği. Anadolu Orman Araştırmaları Dergisi, 9(1), 96-103.</mixed-citation>
                    </ref>
                                    <ref id="ref23">
                        <label>23</label>
                        <mixed-citation publication-type="journal">ESA, 2023. Sentinel. sentinels.copernicus.eu/web/ sentinel/missions/sentinel-2 (Erişildi 03.01.2023).
ESA. 2021. ESA. http://www.esa.int/ (Erişildi 15.10.2021).</mixed-citation>
                    </ref>
                                    <ref id="ref24">
                        <label>24</label>
                        <mixed-citation publication-type="journal">Escuin, S., Navarro, R., Fernández, P., 2008. Fire severity assessment by using NBR (Normalized Burn Ratio) and NDVI (Normalized Difference Vegetation Index) derived from LANDSAT TM/ETM images. International Journal of Remote Sensing 29(4), 1053-1073.</mixed-citation>
                    </ref>
                                    <ref id="ref25">
                        <label>25</label>
                        <mixed-citation publication-type="journal">FAO. 2022a. EFFIS statistic estimates https://effis.jrc.ec.europa.eu/apps/effis.statistics/estimates (Erişildi 29.12.2022).</mixed-citation>
                    </ref>
                                    <ref id="ref26">
                        <label>26</label>
                        <mixed-citation publication-type="journal">FAO, 2022b.  The State of the World’s Forests (SOFO) https://www.fao.org/publications/sofo/2022/en/ (Erişildi 30.12.2022).</mixed-citation>
                    </ref>
                                    <ref id="ref27">
                        <label>27</label>
                        <mixed-citation publication-type="journal">Fidanboy, M., Adar, N., Okyay, S., 2022. Derin öğrenmeye dayalı orman yangını tahmin modeli geliştirilmesi ve Türkiye yangın risk haritasının oluşturulması. Ormancılık Araştırma Dergisi 9(2), 206-218.</mixed-citation>
                    </ref>
                                    <ref id="ref28">
                        <label>28</label>
                        <mixed-citation publication-type="journal">Garbolino, E., Sanseverino-Godfrin, V., Hinojos-Mendoza, G., 2017. Describing and predicting of the vegetation development of Corsicadue to expected climate change and its impact on forest fire risk evolution. Safety Science 88, 180-186.</mixed-citation>
                    </ref>
                                    <ref id="ref29">
                        <label>29</label>
                        <mixed-citation publication-type="journal">Ghorbanzadeh, O., Valizadeh Kamran, K., Blaschke, T., Aryal, J., Naboureh, A., Einali, J., Bian, J., 2019. Spatial prediction of wildfire susceptibility using field surveygpsdata and machine learning approaches. Fire 2(3).</mixed-citation>
                    </ref>
                                    <ref id="ref30">
                        <label>30</label>
                        <mixed-citation publication-type="journal">Giannakopoulos, C., Le Sager, P., Bindi, M., Moriondo, M., Kostopoulou, E., Goodess, C. M., 2009. Climatic changes and associated impacts in the Mediterranean resulting from a 2 C global warming. Global and Planetary Change 68(3), 209-224.</mixed-citation>
                    </ref>
                                    <ref id="ref31">
                        <label>31</label>
                        <mixed-citation publication-type="journal">Golkarian, A., S. A. Naghibi, B. Kalantar, Pradhan, B., 2018. Groundwater Potential Mapping Using C5.0, Random Forest, and Multivariate Adaptive Regression Spline Models in GIS.Environmental Monitoring and Assessment, 190,149.</mixed-citation>
                    </ref>
                                    <ref id="ref32">
                        <label>32</label>
                        <mixed-citation publication-type="journal">Gürsoy, M. İ., Orhan, O., Tekin, S., 2023. Creation of wildfire susceptibility maps in the Mediterranean Region (Turkey) using convolutional neural networks and multilayer perceptron techniques. Forest Ecology and Management, 538, 121006.</mixed-citation>
                    </ref>
                                    <ref id="ref33">
                        <label>33</label>
                        <mixed-citation publication-type="journal">Iban, M. C., Sekertekin, A., 2022. Machine learning based wildfire susceptibility mapping using remotely sensed fire data and GIS: A case study of Adana and Mersin provinces, Turkey. Ecological Informatics 69, 101647.</mixed-citation>
                    </ref>
                                    <ref id="ref34">
                        <label>34</label>
                        <mixed-citation publication-type="journal">Isaev, A. S., Korovin, G. N., Bartalev, S. A., Ershov, D. V., Janetos, A., Kasischke, E. S., Shugart, H. H., French B. E. O. Murphy, T. L., 2002. Using remote sensing to assess Russian forest fire carbon emissions. Climatic Change, 55, 235-249.</mixed-citation>
                    </ref>
                                    <ref id="ref35">
                        <label>35</label>
                        <mixed-citation publication-type="journal">İban, M. C., Şahin, E., 2022. Monitoring burn severity and air pollutants in wildfire events using remotesensing data: the case of Mersin wildfires in summer 2021. Gümüşhane Üniversitesi Fen Bilimleri Dergisi 12(2), 487-497.</mixed-citation>
                    </ref>
                                    <ref id="ref36">
                        <label>36</label>
                        <mixed-citation publication-type="journal">Jin, R., Lee, K. S., 2022. Investigation of forest fire characteristics in north korea using remote sensing data and GIS. Remote Sensing 14(22), 5836.</mixed-citation>
                    </ref>
                                    <ref id="ref37">
                        <label>37</label>
                        <mixed-citation publication-type="journal">Kalantar, B., Ueda, N., Idrees, M. O., Janizadeh, S., Ahmadi, K., Shabani, F., 2020. Forest fire susceptibility prediction based on machine learning models with resampling algorithms on remote sensing data. Remote Sensing, 12(22), 3682.</mixed-citation>
                    </ref>
                                    <ref id="ref38">
                        <label>38</label>
                        <mixed-citation publication-type="journal">Karabulut, M., Karakoç, A., Gürbüz, M., Kızılelma, Y., 2013. Coğrafi bilgi sistemleri kullanarak başkonuş dağında (Kahramanmaraş) orman yangını risk alanlarının belirlenmesi. Uluslararası Sosyal Araştırmalar Dergisi, 6(24), 171-179.</mixed-citation>
                    </ref>
                                    <ref id="ref39">
                        <label>39</label>
                        <mixed-citation publication-type="journal">Kimengsi, J. N., Owusu, R., Djenontin, I. N., Pretzsch, J., Giessen, L., Buchenrieder, G., Pouliot, M., Acosta, A. N., 2022. What do we (not) know on forest management institutions in sub-Saharan Africa A regional comparative review. Land Use Policy 114, 105931.</mixed-citation>
                    </ref>
                                    <ref id="ref40">
                        <label>40</label>
                        <mixed-citation publication-type="journal">Lapola, D. M., Pinho, P., Barlow, J., Aragão, L. E., Berenguer, E., Carmenta, R., Liddy, H. M., Walker, W. S., 2023. The drivers and impacts of Amazon Forest degradation. Science, 379(6630), eabp8622.</mixed-citation>
                    </ref>
                                    <ref id="ref41">
                        <label>41</label>
                        <mixed-citation publication-type="journal">Lavanya, B., Padmaja, B., 2014. A Novel approach for identification of forest fires using land surface temperature images. IOSR Journal of Computer Engineering 16(5), 78-83.</mixed-citation>
                    </ref>
                                    <ref id="ref42">
                        <label>42</label>
                        <mixed-citation publication-type="journal">Li, W., Guo, W. Y., Pasgaard, M., Niu, Z., Wang, L., Chen, F., Qin Y., Svenning, J. C., 2023. Human fingerprint on structural density of forests globally. Nature Sustainability 1-12.</mixed-citation>
                    </ref>
                                    <ref id="ref43">
                        <label>43</label>
                        <mixed-citation publication-type="journal">Lībiete, Z., Jansons, Ā., Ruņis, D., Donis, J., 2023. Forest resources and sustainable management. In Forest Microbiology (pp. 3-31). Academic Press.</mixed-citation>
                    </ref>
                                    <ref id="ref44">
                        <label>44</label>
                        <mixed-citation publication-type="journal">Liu, S., Zheng, Y., Dalponte, M., Tong, X., 2020. A novel fire index-based burned area change detection approach using Landsat-8 OLI data. European journal of remotesensing 53(1), 104-112.</mixed-citation>
                    </ref>
                                    <ref id="ref45">
                        <label>45</label>
                        <mixed-citation publication-type="journal">Mersin Valiliği, 2022. Nüfus ve dağılım. http://www.mersin.gov.tr/nufus-ve-dagilim(Erişildi 15.11.2022)
MGM, 2022a. Kuraklık analizi, https://www.mgm.gov.tr/veridegerlendirme/kuraklik-analizi.aspx?d=yillik#sfB (Erişildi 27.12.2022).</mixed-citation>
                    </ref>
                                    <ref id="ref46">
                        <label>46</label>
                        <mixed-citation publication-type="journal">MGM, 2022b. İl ve ilçe veri değerlendirme. https://www.mgm.gov.tr/veridegerlendirme/il-ve-ilceler-istatistik.aspx?k=A (Erişildi 27.12.2022).</mixed-citation>
                    </ref>
                                    <ref id="ref47">
                        <label>47</label>
                        <mixed-citation publication-type="journal">Moayedi, H., Mehrabi, M., Bui, D. T., Pradhan, B., Foong, L. K., 2020. Fuzzy-metaheuristicensembles for spatial assessment of forest fire susceptibility. Journal of Environmental Management 260, 109867.</mixed-citation>
                    </ref>
                                    <ref id="ref48">
                        <label>48</label>
                        <mixed-citation publication-type="journal">Mwaniki, M. W., Kuria, D. N., Boitt, M. K., Ngigi, T. G., 2017. Image enhancements of Landsat 8 (OLI) and SAR data for preliminary landslide identification and mapping applied to the central region of Kenya. Geomorphology, 282, 162-175.</mixed-citation>
                    </ref>
                                    <ref id="ref49">
                        <label>49</label>
                        <mixed-citation publication-type="journal">Naghibi, S. A., H. R. Pourghasemi, Dixon, B., 2016. GIS-based Groundwater Potential Mapping Using Boosted Regression Tree, Classification and Regression Tree, and Random Forest Machine Learning Models in Iran. Environmental Monitoring and Assessment, 188,44.</mixed-citation>
                    </ref>
                                    <ref id="ref50">
                        <label>50</label>
                        <mixed-citation publication-type="journal">Navarro, G., Caballero, I., Silva, G., Parra, P., Vázquez, Á., Caldeira, R., 2017. Evaluation of forest fire on Madeira Island using Sentinel-2A MSI imagery. International Journal of Applied Earth Observation and Geoinformation 58, 97-106.</mixed-citation>
                    </ref>
                                    <ref id="ref51">
                        <label>51</label>
                        <mixed-citation publication-type="journal">Nguyen, Q. H., Nguyen, H. D., Le, D. T., Bui, Q. T., 2023. Fine-tuning LightGBM using an artificial ecosystem-based optimizer for forest fire analysis. Forest Science, 69(1), 73-82.</mixed-citation>
                    </ref>
                                    <ref id="ref52">
                        <label>52</label>
                        <mixed-citation publication-type="journal">OBM, 2022. Silifke Orman bilgileri https://mersinobm.ogm.gov.tr/SilifkeOIM/Sayfalar/default.aspx (Erişildi 08.12.2022).</mixed-citation>
                    </ref>
                                    <ref id="ref53">
                        <label>53</label>
                        <mixed-citation publication-type="journal">OGM, 2022. Orman Genel Müdürlüğü. Ormancılık ve Yangın İstatistikleri. https://www.ogm.gov.tr/tr/e-kutuphane/resmi-istatistikler (Erişildi 17.08.2023).</mixed-citation>
                    </ref>
                                    <ref id="ref54">
                        <label>54</label>
                        <mixed-citation publication-type="journal">Oğuz, E., Oğuz, K., Öztürk, K., 2021.Determination of flood susceptibility areas of Düzce region. Journal of Geomatics 7(3), 220-234.</mixed-citation>
                    </ref>
                                    <ref id="ref55">
                        <label>55</label>
                        <mixed-citation publication-type="journal">Orhan, O., 2021. Land suitability determination for citrus cultivation using a GIS-based multi-criteria analysis in Mersin, Turkey. Computers and Electronics in Agriculture, 190, 106433.</mixed-citation>
                    </ref>
                                    <ref id="ref56">
                        <label>56</label>
                        <mixed-citation publication-type="journal">Orhan, O., Yakar, M., Ekercin, S., 2020. An application on sinkhole susceptibility mapping by integrating remote sensing and geographic information systems. Arabian Journal of Geosciences 13, 886.</mixed-citation>
                    </ref>
                                    <ref id="ref57">
                        <label>57</label>
                        <mixed-citation publication-type="journal">Our World in Data, 2022. Our World in Data forest area. https://ourworldindata.org/forest-area (Erişildi 29.12.2022).</mixed-citation>
                    </ref>
                                    <ref id="ref58">
                        <label>58</label>
                        <mixed-citation publication-type="journal">Öztürk, D., 2022. Sentinel-2A MSI ve Landsat-9 OLI-2 görüntüleri kullanılarak farklı geçirimsiz yüzey indekslerinin karşılaştırmalı değerlendirmesi: Samsun Örneği. Ege Coğrafya Dergisi, 31(2), 401-423.</mixed-citation>
                    </ref>
                                    <ref id="ref59">
                        <label>59</label>
                        <mixed-citation publication-type="journal">Öztürk, T., Gürsoy, F., 2022. Küresel iklim değişikliğinin Arktik Okyanusu’na jeopolitik etkisi. Akdeniz Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 22(1), 117–31.</mixed-citation>
                    </ref>
                                    <ref id="ref60">
                        <label>60</label>
                        <mixed-citation publication-type="journal">Pourtaghi, Z. S., Pourghasemi, H. R., Aretano, R., Semeraro, T., 2016. Investigation of general indicators influencing on forest fire and its susceptibility modeling using different data mining techniques. Ecological indicators, 64, 72-84.</mixed-citation>
                    </ref>
                                    <ref id="ref61">
                        <label>61</label>
                        <mixed-citation publication-type="journal">Pourtaghi, Z. S., Pourghasemi, H. R., Rossi, M., 2015. Forest fire susceptibility mapping in the Minudasht forests, Golestan province, Iran. Environmental Earth Sciences 73(4), 1515-1533.</mixed-citation>
                    </ref>
                                    <ref id="ref62">
                        <label>62</label>
                        <mixed-citation publication-type="journal">Pouyan, S., Pourghasemi, H. R., Bordbar, M., Rahmanian, S., Clague, J. J., 2021. A multi-hazard map-based flooding, gully erosion, forest fires, and earthquakes in Iran. Scientific Reports, 11(1), 1-19.</mixed-citation>
                    </ref>
                                    <ref id="ref63">
                        <label>63</label>
                        <mixed-citation publication-type="journal">Rege, J.E.O., Ochieng, J.W., 2022. The state of capacities, enabling environment, applications and ımpacts of biotechnology in the forestry sector. Agricultural Biotechnology in Sub-Saharan Africa, 123-143.</mixed-citation>
                    </ref>
                                    <ref id="ref64">
                        <label>64</label>
                        <mixed-citation publication-type="journal">Sabuncu, A., Özener, H., 2019. Uzaktan algılama teknikleri ile yanmış alanların tespiti: İzmir Seferihisar orman yangını örneği. Doğal Afetler ve Çevre Dergisi, 5(2), 317-326.</mixed-citation>
                    </ref>
                                    <ref id="ref65">
                        <label>65</label>
                        <mixed-citation publication-type="journal">Saglam, B., Bilgili, E., Dincdurmaz, B. D., Kadiogulları, A. İ., Kücük, Ö., 2008. Spatio-temporal analysis of forest fire risk and danger using LANDSAT imagery. Sensors 8(6), 3970-3987.</mixed-citation>
                    </ref>
                                    <ref id="ref66">
                        <label>66</label>
                        <mixed-citation publication-type="journal">Sari, F., 2021. Forest fire susceptibility mapping via multi-criteria decision analysis techniques for Muğla, Turkey: A comparative analysis of VIKOR and TOPSIS. Forest Ecology and Management 480, 118644.</mixed-citation>
                    </ref>
                                    <ref id="ref67">
                        <label>67</label>
                        <mixed-citation publication-type="journal">Sargıncı, M., Beyazyüz, F, 2022. İklim değişikliğinin ormanlar üzerindeki etkisi: İklim akılcı ormancılık bakış açısı. Anadolu Orman Araştırmaları Dergisi, 8(2), 142-149.</mixed-citation>
                    </ref>
                                    <ref id="ref68">
                        <label>68</label>
                        <mixed-citation publication-type="journal">Satir, O., Berberoglu, S., Donmez, C., 2016. Mapping regional forest fire probability using artificial neural network model in a Mediterranean forest ecosystem. Geomatics, Natural Hazards and Risk 7(5), 1645-1658.</mixed-citation>
                    </ref>
                                    <ref id="ref69">
                        <label>69</label>
                        <mixed-citation publication-type="journal">Seleem, T., Bafi, D., Karantzia, M., Parcharidis, I., 2022. Water quality monitoring using Landsat 8 and Sentinel-2 satellite data (2014–2020) in Timsah Lake, Ismailia, Suez Canal Region (Egypt). Journal of the Indian Society of Remote Sensing, 50(12), 2411-2428.</mixed-citation>
                    </ref>
                                    <ref id="ref70">
                        <label>70</label>
                        <mixed-citation publication-type="journal">Shin, J. I., Seo, W. W., Kim, T., Park, J., Woo, C. S., 2019. Using UAV multispectralimages for classification of forest burnseverity—A case study of the 2019 Gangneung forest fire. Forests 10(11), 1025.</mixed-citation>
                    </ref>
                                    <ref id="ref71">
                        <label>71</label>
                        <mixed-citation publication-type="journal">Si, L., Shu, L., Wang, M., Zhao, F., Chen, F., Li, W., Li, W., 2022. Study on forest fire danger prediction in plateau mountainous forest area. Natural Hazards Research, 2(1), 25-32.</mixed-citation>
                    </ref>
                                    <ref id="ref72">
                        <label>72</label>
                        <mixed-citation publication-type="journal">Silva, I. D. B.,Valle, M. E., Barros, L. C., Meyer, J. F. C., 2020. A wildfirewarning system applied to the state of Acre in the Brazilian Amazon. Applied Soft Computing 89, 106075.</mixed-citation>
                    </ref>
                                    <ref id="ref73">
                        <label>73</label>
                        <mixed-citation publication-type="journal">Sivrikaya, F., Küçük, Ö., 2022. Modeling forest fire risk based on GIS-based analytical hierarchy process and statistical analysis in Mediterranean region. Ecological Informatics 68, 101537.</mixed-citation>
                    </ref>
                                    <ref id="ref74">
                        <label>74</label>
                        <mixed-citation publication-type="journal">The Global Economy, 2022. The Global Economy rankings forest area. https://www.theglobaleconomy.com/rankings/forest_area/ (Erişildi 29.12.2022).</mixed-citation>
                    </ref>
                                    <ref id="ref75">
                        <label>75</label>
                        <mixed-citation publication-type="journal">Tonbul, H., Kavzoglu, T., Kaya, S., 2016. Assessment of fire severity and post-fire regeneration based on topographical features using multitemporal Landsat imagery: A case study in Mersin, Turkey. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 41, 763-769.</mixed-citation>
                    </ref>
                                    <ref id="ref76">
                        <label>76</label>
                        <mixed-citation publication-type="journal">USGS FIREMON, 2023. United States Geological Survey, Fire Effects Monitoring and Inventory Protocol. https://www.frames.gov/firemon/home Erişildi 17.08.2023.</mixed-citation>
                    </ref>
                                    <ref id="ref77">
                        <label>77</label>
                        <mixed-citation publication-type="journal">USGS, 2021. United States Geological Survey. 20201. https://earthexplorer.usgs.gov/ (Erişildi 15.10.2021).</mixed-citation>
                    </ref>
                                    <ref id="ref78">
                        <label>78</label>
                        <mixed-citation publication-type="journal">USGS, 2023. United States Geological Survey https://www.usgs.gov/landsat-missions(Erişildi 1.03.2023).</mixed-citation>
                    </ref>
                                    <ref id="ref79">
                        <label>79</label>
                        <mixed-citation publication-type="journal">WB, 2023. The World Bank. https://data.worldbank.org/indicator/AG.LND.FRST.ZS?end=2020&amp;start=1990&amp;view=chart  (Erişildi 27.02.2023).
Warren, M. A., Simis, S. G., Martinez-Vicente, V., Poser, K., Bresciani, M., Alikas, K., Spyrakos, E., Giardino, C., &amp; Ansper, A., 2019. Assessment of atmospheric correction algorithms for the Sentinel-2A multispectral ımager over coastal and inland waters. Remote sensing of environment, 225, 267-289.</mixed-citation>
                    </ref>
                                    <ref id="ref80">
                        <label>80</label>
                        <mixed-citation publication-type="journal">Weather Spark, 2021. Weather Spark hava tahmini https://tr.weatherspark.com/h/d/98267/2021/7/28/28-Temmuz-2021-%C3%87ar%C5%9Famba-tarihinde-inMersin-T%C3%BCrkiye-Ortalama-Hava-Durumu#metar-04-50 (Erişildi 12.12.2022).</mixed-citation>
                    </ref>
                                    <ref id="ref81">
                        <label>81</label>
                        <mixed-citation publication-type="journal">Worldometer, 2022. Worldometers Turkey food agriculture https://www.worldometers.info/food-agriculture/turkey-food-agriculture/ (Erişildi 01.12.2022).</mixed-citation>
                    </ref>
                                    <ref id="ref82">
                        <label>82</label>
                        <mixed-citation publication-type="journal">Yakubu, I.,Mireku-Gyimah, D., &amp;Duker, A. A. (2015). Review of methods for modelling forest fire risk and hazard. African Journal of Environmental Science and Technology 9(3), 155-165.</mixed-citation>
                    </ref>
                                    <ref id="ref83">
                        <label>83</label>
                        <mixed-citation publication-type="journal">Yılmaz, B., Demirel, M., &amp; Balçık, F. (2022). Yanmış alanların Sentinel-2 msı ve Landsat-8 olı ile tespiti ve analizi: Çanakkale/Gelibolu orman yangını. Doğal Afetler ve Çevre Dergisi, 8(1), 76-86.</mixed-citation>
                    </ref>
                            </ref-list>
                    </back>
    </article>
