Araştırma Makalesi

Burned Area Detection and Analysis with Sentinel-2 Satellite Imagery: A Case Study of İzmir Wildfires

Cilt: 1 Sayı: 1 30 Eylül 2025
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Burned Area Detection and Analysis with Sentinel-2 Satellite Imagery: A Case Study of İzmir Wildfires

Öz

Wildfires cause lasting damage to natural ecosystems and adversely affect biodiversity, soil structure, and air quality. This study aims to assess the environmental impacts of four major wildfires that occurred in early July 2025 in the districts of Çeşme, Seferihisar, Buca, and Ödemiş in İzmir Province, using remote sensing techniques. High-resolution multispectral images obtained from the Sentinel-2 satellite, provided by the European Space Agency, were used in the analyses. To minimize seasonal variability and differences in vegetation cover, images dated 10 July 2024 (pre-fire) and 5 July 2025 (post-fire) were selected. The Normalized Burn Ratio (NBR) and differenced NBR (dNBR) indices were calculated to analyze the impact of the fire and the spatial distribution of burned areas using the QGIS software. According to the results, the largest burned area was identified in Seferihisar, covering 96.77 km², followed by Çeşme (93.85 km²), Ödemiş (25.38 km²), and Buca (25.07 km²). The severity of fire impact was classified across the regions with varying degrees, ranging from low to high. This study demonstrates that remote sensing and Geographic Information Systems (GIS) technologies are reliable and effective tools for post-fire damage assessment and monitoring of ecosystem recovery processes. The findings provide a scientifically grounded basis for forest management and disaster planning.

Anahtar Kelimeler

Kaynakça

  1. Akinci, H. A., Akinci, H., and Zeybek, M. (2024). Comparison of diverse machine learning algorithms for forest fire susceptibility mapping in Antalya, Türkiye. Advances in Space Research, 74(2), 647-667. https://doi.org/10.1016/j.asr.2024.04.018
  2. Atalay, H., Dervisoglu, A., and Sunar, A. F. (2024). Exploring forest fire dynamics: fire danger mapping in Antalya Region, Türkiye. ISPRS International Journal of Geo-Information, 13(3), 74. https://doi.org/10.3390/ijgi13030074
  3. Chemura, A., Mutanga, O., Odindi, J., and Kutywayo, D. (2018). Mapping spatial variability of foliar nitrogen in coffee (Coffea arabica L.) plantations with multispectral Sentinel-2 MSI data. ISPRS Journal of Photogrammetry and Remote Sensing, 138, 1-11. https://doi.org/10.1016/j.isprsjprs.2018.02.004
  4. Chen, G., Metz, M. R., Rizzo, D. M., and Meentemeyer, R. K. (2015). Mapping burn severity in a disease-impacted forest landscape using Landsat and MASTER imagery. International Journal of Applied Earth Observation and Geoinformation, 40, 91-99. https://doi.org/10.1016/j.jag.2015.04.005
  5. Çınarer, G. (2025). Hybrid Backbone-Based Deep Learning Model for Early Detection of Forest Fire Smoke. Applied Sciences, 15(13), 7178. https://doi.org/10.3390/app15137178
  6. Dereli M., (2019), Sentinel-2A uydu görüntüleri ile Giresun il merkezi için kısa dönem arazi örtüsü değişiminin belirlenmesi, Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 19(2), 361-368. https://doi.org/10.35414/akufemubid.481455
  7. Dindaroglu, T., Babur, E., Yakupoglu, T., Rodrigo-Comino, J., and Cerda, A. (2021). Evaluation of geomorphometric characteristics and soil properties after a wildfire using Sentinel-2 MSI imagery for future fire-safe forest. Fire safety journal, 122, 103318. https://doi.org/10.1016/j.firesaf.2021.103318
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Ayrıntılar

Birincil Dil

İngilizce

Konular

Fotogrametri ve Uzaktan Algılama

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

30 Eylül 2025

Gönderilme Tarihi

21 Ağustos 2025

Kabul Tarihi

15 Eylül 2025

Yayımlandığı Sayı

Yıl 2025 Cilt: 1 Sayı: 1

Kaynak Göster

APA
Çallı, R., & Özdemir, E. (2025). Burned Area Detection and Analysis with Sentinel-2 Satellite Imagery: A Case Study of İzmir Wildfires. Türkiye Teknik Bilimler ve İnovasyon Dergisi, 1(1), 24-32. https://izlik.org/JA86KM65PS
AMA
1.Çallı R, Özdemir E. Burned Area Detection and Analysis with Sentinel-2 Satellite Imagery: A Case Study of İzmir Wildfires. TJTSI. 2025;1(1):24-32. https://izlik.org/JA86KM65PS
Chicago
Çallı, Rüştü, ve Emirhan Özdemir. 2025. “Burned Area Detection and Analysis with Sentinel-2 Satellite Imagery: A Case Study of İzmir Wildfires”. Türkiye Teknik Bilimler ve İnovasyon Dergisi 1 (1): 24-32. https://izlik.org/JA86KM65PS.
EndNote
Çallı R, Özdemir E (01 Eylül 2025) Burned Area Detection and Analysis with Sentinel-2 Satellite Imagery: A Case Study of İzmir Wildfires. Türkiye Teknik Bilimler ve İnovasyon Dergisi 1 1 24–32.
IEEE
[1]R. Çallı ve E. Özdemir, “Burned Area Detection and Analysis with Sentinel-2 Satellite Imagery: A Case Study of İzmir Wildfires”, TJTSI, c. 1, sy 1, ss. 24–32, Eyl. 2025, [çevrimiçi]. Erişim adresi: https://izlik.org/JA86KM65PS
ISNAD
Çallı, Rüştü - Özdemir, Emirhan. “Burned Area Detection and Analysis with Sentinel-2 Satellite Imagery: A Case Study of İzmir Wildfires”. Türkiye Teknik Bilimler ve İnovasyon Dergisi 1/1 (01 Eylül 2025): 24-32. https://izlik.org/JA86KM65PS.
JAMA
1.Çallı R, Özdemir E. Burned Area Detection and Analysis with Sentinel-2 Satellite Imagery: A Case Study of İzmir Wildfires. TJTSI. 2025;1:24–32.
MLA
Çallı, Rüştü, ve Emirhan Özdemir. “Burned Area Detection and Analysis with Sentinel-2 Satellite Imagery: A Case Study of İzmir Wildfires”. Türkiye Teknik Bilimler ve İnovasyon Dergisi, c. 1, sy 1, Eylül 2025, ss. 24-32, https://izlik.org/JA86KM65PS.
Vancouver
1.Rüştü Çallı, Emirhan Özdemir. Burned Area Detection and Analysis with Sentinel-2 Satellite Imagery: A Case Study of İzmir Wildfires. TJTSI [Internet]. 01 Eylül 2025;1(1):24-32. Erişim adresi: https://izlik.org/JA86KM65PS