Forest Fire Risk Modeling Using Logistic Regression and Geographic Information Systems: A Case Study in Muğla - Milas
Forest fires are an important environmental problem, they negatively affect the entire ecosystem and human and animal life in it. In Turkey 192.734 hectares of forest area has been damaged in 46.669 forest fires in the last 20 years. Negligence-accident is the primary cause of these fires. For this...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Artvin Corun University
2022-01-01
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| Series: | Doğal Afetler ve Çevre Dergisi |
| Subjects: | |
| Online Access: | http://dacd.artvin.edu.tr/tr/pub/issue/68003/951902 |
| _version_ | 1797906368301105152 |
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| author | İlker Atmaca Özge Işık Pekkan Mehtap Özenen Kavlak Yavuz Selim Tunca Saye Nihan Çabuk |
| author_facet | İlker Atmaca Özge Işık Pekkan Mehtap Özenen Kavlak Yavuz Selim Tunca Saye Nihan Çabuk |
| author_sort | İlker Atmaca |
| collection | DOAJ |
| description | Forest fires are an important environmental problem, they negatively affect the entire ecosystem and human and animal life in it. In Turkey 192.734 hectares of forest area has been damaged in 46.669 forest fires in the last 20 years. Negligence-accident is the primary cause of these fires. For this reason, in order to minimize the frequency of forest fires and prevent damages, areas with fire risk should be determined and it is necessary to be prepared for the precautions to be taken before, during and after the fire. In this study, Logistic Regression (LR) and Geographic Information Systems (GIS) were used to model the forest fire risk for the Milas province in Muğla. Considering the topographic features, stand data and cultural data, the relationship of these factors with the occurrence of fires was investigated. Accuracy analyzes of fire risk estimation with LR and fire risks of areas with different properties were examined by Receiver Operating Characteristic (ROC) and Hosmer-Lemeshow test. In line with the findings obtained by the LR method, a forest fire risk map was created in the GIS environment. Here, forest fire risk is evaluated at five levels, with “1” very low risk and “5” very high risk. In the resulting forest fire risk map, it was concluded that 16% of the total forest areas in the study area are in high and very high risk classes. |
| first_indexed | 2024-04-10T10:20:53Z |
| format | Article |
| id | doaj.art-323a17f52bbf47e8a2ce3e1b676fad95 |
| institution | Directory Open Access Journal |
| issn | 2528-9640 |
| language | English |
| last_indexed | 2024-04-10T10:20:53Z |
| publishDate | 2022-01-01 |
| publisher | Artvin Corun University |
| record_format | Article |
| series | Doğal Afetler ve Çevre Dergisi |
| spelling | doaj.art-323a17f52bbf47e8a2ce3e1b676fad952023-02-15T16:21:39ZengArtvin Corun UniversityDoğal Afetler ve Çevre Dergisi2528-96402022-01-01816675https://doi.org/10.21324/dacd.951902Forest Fire Risk Modeling Using Logistic Regression and Geographic Information Systems: A Case Study in Muğla - Milasİlker Atmaca0https://orcid.org/0000-0001-9950-2833Özge Işık Pekkan1https://orcid.org/0000-0003-4634-4864Mehtap Özenen Kavlak2https://orcid.org/0000-0002-5369-4494Yavuz Selim Tunca3https://orcid.org/0000-0003-3164-926XSaye Nihan Çabuk4https://orcid.org/0000-0003-4859-2271Yozgat Bozok Üniversitesi, Mühendislik Mimarlık Fakültesi, Şehir ve Bölge Planlama Bölümü, 66900, Yozgat.Eskişehir Teknik Üniversitesi, Lisansüstü Eğitim Enstitüsü, Uzaktan Algılama ve Coğrafi Bilgi Sistemleri A.B.D., 26555, Eskişehir.Eskişehir Teknik Üniversitesi, Lisansüstü Eğitim Enstitüsü, Uzaktan Algılama ve Coğrafi Bilgi Sistemleri A.B.D., 26555, Eskişehir.Eskişehir Teknik Üniversitesi, Lisansüstü Eğitim Enstitüsü, Uzaktan Algılama ve Coğrafi Bilgi Sistemleri A.B.D., 26555, Eskişehir.Eskişehir Teknik Üniversitesi, Yer ve Uzay Bilimleri Enstitüsü, 26555, Eskişehir.Forest fires are an important environmental problem, they negatively affect the entire ecosystem and human and animal life in it. In Turkey 192.734 hectares of forest area has been damaged in 46.669 forest fires in the last 20 years. Negligence-accident is the primary cause of these fires. For this reason, in order to minimize the frequency of forest fires and prevent damages, areas with fire risk should be determined and it is necessary to be prepared for the precautions to be taken before, during and after the fire. In this study, Logistic Regression (LR) and Geographic Information Systems (GIS) were used to model the forest fire risk for the Milas province in Muğla. Considering the topographic features, stand data and cultural data, the relationship of these factors with the occurrence of fires was investigated. Accuracy analyzes of fire risk estimation with LR and fire risks of areas with different properties were examined by Receiver Operating Characteristic (ROC) and Hosmer-Lemeshow test. In line with the findings obtained by the LR method, a forest fire risk map was created in the GIS environment. Here, forest fire risk is evaluated at five levels, with “1” very low risk and “5” very high risk. In the resulting forest fire risk map, it was concluded that 16% of the total forest areas in the study area are in high and very high risk classes.http://dacd.artvin.edu.tr/tr/pub/issue/68003/951902forest firefire risk mappinglogistic regressiongeographical information systemsmilas (muğla) |
| spellingShingle | İlker Atmaca Özge Işık Pekkan Mehtap Özenen Kavlak Yavuz Selim Tunca Saye Nihan Çabuk Forest Fire Risk Modeling Using Logistic Regression and Geographic Information Systems: A Case Study in Muğla - Milas Doğal Afetler ve Çevre Dergisi forest fire fire risk mapping logistic regression geographical information systems milas (muğla) |
| title | Forest Fire Risk Modeling Using Logistic Regression and Geographic Information Systems: A Case Study in Muğla - Milas |
| title_full | Forest Fire Risk Modeling Using Logistic Regression and Geographic Information Systems: A Case Study in Muğla - Milas |
| title_fullStr | Forest Fire Risk Modeling Using Logistic Regression and Geographic Information Systems: A Case Study in Muğla - Milas |
| title_full_unstemmed | Forest Fire Risk Modeling Using Logistic Regression and Geographic Information Systems: A Case Study in Muğla - Milas |
| title_short | Forest Fire Risk Modeling Using Logistic Regression and Geographic Information Systems: A Case Study in Muğla - Milas |
| title_sort | forest fire risk modeling using logistic regression and geographic information systems a case study in mugla milas |
| topic | forest fire fire risk mapping logistic regression geographical information systems milas (muğla) |
| url | http://dacd.artvin.edu.tr/tr/pub/issue/68003/951902 |
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