Identifying anthropogenic and natural causes of wildfires by maximum entropy method-based ignition susceptibility distribution models

Sarı, Fatih

doi:10.1007/s11676-022-01502-4

Cited by 28 publications

(13 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…There is a need for effective methods for fire risk assessments because wildfires have a significant impact on socioeconomic and environmental aspects, even at a local spatial scale. This will allow for the use of proactive control measures for environmental management (Attri et al, 2020;Moreira et al, 2011;Sari, 2022). This study evaluated the effects of vegetation, topographic factors (elevation, slope, and aspect), and population density on burn severity (Fig.…”

Section: Discussionmentioning

confidence: 99%

Remote Sensing for Assessing the Ecological and Socio-Economic Impacts of Forest Fire Severity in Kozan District, Turkey

Ibrahim¹,

KÖSE

Adamu

et al. 2022

Preprint

View full text Add to dashboard Cite

Monitoring the ecological and socio-economic impacts of wildfires using traditional approaches requires significant financial resources, time, and sampling expertise. However, not only are resources scarce, but the spatial and temporal extent of forest fires may make it impractical to assess large areas over time. As a result, fire monitoring initiatives are often not realized. This makes the remote sensing approach an intriguing option for fire protection managers and decision makers due to its ability to measure large areas and its temporal capabilities. In this study, burn spectral indices derived from Landsat 8 (difference normalized vegetation index (dNDVI) and difference normalized burn ratio (dNBR)) were used to assess the ecological and socio-economic impacts of forest fire based on an existing land use land cover dataset. The relationships between estimated fire severity/area and, environmental and anthropogenic factors were also evaluated. The results show that more than 700 hectares of forest and other land use categories were burnt. Fires adversely affect high forests, thickets, degraded forests, and most cultivation and rural areas. The study also shows a moderate positive relationship between burn severity and pre-fire vegetation (R2 = 0.48 and R2 = 0.49 for dNDVI and dNBR, respectively). This result suggests, that fuel amount is the main driver of burn severity during the fire season in this particular ecosystem. Topography has been shown to affect the fire behavior in the study area, where fires occurred primarily on elevations averaging 400-800 meters above mean sea level. In addition, there is a weak positive relationship between population density and burnt area. This is typical of certain areas where fire increases with increasing population density, and falls when the burning exceeds a threshold. This study has shown that Landsat 8 data-derived burn spectral indices (dNDVI and dNBR) have a high potential for the spatial analysis of wildfire. The study recommends an improvement in the application of remote sensing to detect, monitor, and assess fire extent and patterns. These in return will protect and improve lives and properties for sustainable development.

show abstract

Section: Discussionmentioning

confidence: 99%

Remote Sensing for Assessing the Ecological and Socio-Economic Impacts of Forest Fire Severity in Kozan District, Turkey

Ibrahim¹,

KÖSE

Adamu

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…İklim değişikliğine bağlı olarak sıcak hava dalgalarının sıklığının ve şiddetinin artması sonucunda bitki örtüsü yangınlarının görülme sıklığı da artmıştır. İklim değişikliği nedeniyle aşırı kurak koşullara maruz kalan bitki örtüsü içerisindeki nem miktarının iyice azalması daha kolay yanıcı hale gelmesi sonucunu doğurmaktadır (Sarı, 2022;Tavşanoğlu, 2021;Tüfekçioğlu vd., 2022).…”

Section: çAlışma Alanıunclassified

“…Orman alanlarının, yeryüzünün doğal yapısını koruması üzerinde atmosferik kirliliği azaltmadan, toprak kaymasına kadar faydalı birçok etkisinin olduğu bilinmektedir. Ayrıca pek çok doğal zenginliğe ev sahipliği yaparak, ülkelerin ekonomilerine çeşitli katkıları da bulunmaktadır (Arca vd., 2020;Karabacak vd., 2019;Sarı, 2022;Zúñiga-Vásquez vd., 2017). Orman yangınları, paleozoik zamandan itibaren geçen süre içerisinde yeryüzünde var olan karasal ekosistemlerin önemli bir parçası olmuştur (Tüfekçioğlu vd., 2022).…”

Section: Introductionunclassified

“…veya insan kaynaklı nedenler (avcılık, piknik, sigara izmariti, terör saldırıları, sabotaj vb.) orman yangınlarına sebep olmaktadır (Busico vd., 2019;Çolak ve Sunar, 2020a;İban ve Şekertekin, 2022;Novo vd., 2020;Sarı, 2022). Dünyada insan kaynaklı nedenlerle çıkan yangınlar, doğal nedenlerle çıkan yangınlardan çok daha fazladır (Chen ve Yang, 2018;Duran, 2014).…”

Section: Introductionunclassified

See 1 more Smart Citation

Türkiye’deki 2000 – 2021 Yılları Arasındaki Bitki Örtüsü Yangınlarının Mekânsal Analizi

Akyürek

2023

Turk J Remote Sens GIS

View full text Add to dashboard Cite

Doğal veya insani sebeplerden meydana gelen yangınlar, yeryüzünde yaşayan tüm canlıları etkileyen en önemli doğal afetlerden bir tanesidir. Yeryüzünde her yıl ortalama olarak 3-5 milyon km2lik ormanlık alan yanmaktadır. Meydana gelen yangınlar, canlıları etkileyen küresel ısınma, atmosferde bulunan hava kirletici parametrelerin yoğunluğunda artış vb. çeşitli faktörler meydana getirmektedirler. Uzaktan Algılama ve Coğrafi Bilgi Sistemleri gelişen günümüz teknolojisinde meydana gelen doğal afetlerin izlenmesinde ve yönetiminde sıklıkla başvurulan araçlardandır. Konumsal verileri yönetmedeki başarısı, konumsal analiz yapabilme yeteneği, sonuçları sunabilme ve görselleştirme kapasitesi nedeniyle sıklıkla tercih edilmektedir. Bu çalışmada 2000 – 2021 yılları arasında Türkiye’de ormanlık ve otlak alanlarda meydana gelen bitki örtüsü yangınları mekânsal istatistik yöntemlerle incelenerek analizi yapılmış ve haritalandırılması sağlanmıştır. Analizler sonucunda 21 yıllık süreç içerisinde ormanlık alan yangınlarından en çok etkilenen bölgelerin Ege, Akdeniz ve Güneydoğu Anadolu bölgeleri, otlak alan yangınlarından ise İç ve Güneydoğu Anadolu bölgesi olduğu tespit edilmiştir. Ormanlık alan yangınlarından en çok etkilenen ilin Antalya, otlak alan yangınlarından en çok etkilenen ilin ise Şanlıurfa olduğu belirlenmiştir.

show abstract

“…In forest fire risk mapping, diverse methods are employed, including logistic regression [13], GIS-based decision support systems [17], maximum entropy [18], machine learning [19,20], artificial neural network analytics [21], analytical hierarchy processes [22], and fuzzy analytic hierarchy processes [23,24]. GIS-based Multi-Criteria Decision Analysis (MCDA) is an intelligent approach that transforms spatial and non-spatial data into usable information alongside the decision maker's judgment to facilitate critical decisions [25].…”

Section: Introductionmentioning

confidence: 99%

Comparison between Post-Fire Analysis and Pre-Fire Risk Assessment According to Various Geospatial Data

Güngöroğlu,

İsmailoğlu,

Kapukaya

et al. 2024

Sustainability

View full text Add to dashboard Cite

Wildfires in forest ecosystems exert substantial ecological, economic, and social impacts. The effectiveness of fire management hinges on precise pre-fire risk assessments to inform mitigation efforts. This study aimed to investigate the relationship between predictions from pre-fire risk assessments and outcomes observed through post-fire burn severity analyses. In this study, forest fire risk was assessed through the Fuzzy Analytical Hierarchy Process (FAHP), in which fire-oriented factors were used as input. The degree of burn was determined by the Random Forest method using 11,519 training points and 400 test points on Sentinel-2 satellite images under three different classes. According to the results obtained from 266 selected test points located within the forest, all primary factors put forth increased high burn severity. Climate, in particular, emerged as the most significant factor, accounting for 52% of the overall impact. However, in cases of high fire severity, climate proved to be the most effective risk factor, accounting for 67%. This was followed by topography with 50% accuracy at a high fire intensity. In the risk assessment based on the FAHP method, climate was assigned the highest weight value among the other factors (32.2%), followed by topography (27%). To evaluate the results more comprehensively, both visually and statistically, two regions with different stand canopy characteristics were selected within the study area. While high burn severity had the highest accuracy in the Case 1 area, moderate burn severity had the highest in the Case 2 area. During the days of the fire, the direction of spreading was obtained from the MODIS images. In this way, the fire severity was also interpreted depending on the direction of fire progression. Through an analysis of various case studies and literature, this research underlines both the inherent strengths and limitations of predicting forest fire behavior-based pre-fire risk assessments. Furthermore, it emphasizes the necessity of continuous improvement to increase the success of forest fire management.

show abstract

Identifying anthropogenic and natural causes of wildfires by maximum entropy method-based ignition susceptibility distribution models

Cited by 28 publications

References 57 publications

Remote Sensing for Assessing the Ecological and Socio-Economic Impacts of Forest Fire Severity in Kozan District, Turkey

Remote Sensing for Assessing the Ecological and Socio-Economic Impacts of Forest Fire Severity in Kozan District, Turkey

Türkiye’deki 2000 – 2021 Yılları Arasındaki Bitki Örtüsü Yangınlarının Mekânsal Analizi

Comparison between Post-Fire Analysis and Pre-Fire Risk Assessment According to Various Geospatial Data

Contact Info

Product

Resources

About