Assessing forest fire behavior simulation using FlamMap software and remote sensing techniques in Western Black Sea Region, Turkey

Mehmet Yavuz; Bülent Sağlam; Ömer Küçük; Aydın Tüfekçioğlu

doi:10.17475/kastorman.459698

Research Article

Batı Karadeniz Bölgesinde FlamMap yazılımı ve uzaktan algılama teknikleri kullanılarak orman yangın davranışı simülasyonunun değerlendirilmesi

Year 2018, Volume: 18 Issue: 2, 171 - 188, 15.09.2018

Mehmet Yavuz , Bülent Sağlam Ömer Küçük Aydın Tüfekçioğlu

https://doi.org/10.17475/kastorman.459698

Cited By: 17

Abstract

Çalışmanın amacı: Yanıcı madde tipleri ve tüketilebilir yanıcı madde miktarı yangın davranışının modellenmesinde, yangın şiddetinin hesaplanmasında ve yangın tehlike riskinin haritalanmasında çok önemlidir. Yanıcı madde tipi, yanıcı madde nem içeriği, rüzgâr hızı ve eğim arasındaki ilişki, belirli bir bölgenin yangın davranışının tahmin edilmesinde kullanılan önemli parametrelerden bazılarıdır. Bu çalışmada, Bayam Orman İşletme Şefliğine ait ormanlarda yanıcı madde özellikleri, hava halleri ve bazı topoğrafik özellikler kullanılarak yangın şiddeti ve yangın yayılma oranı haritaları ile yangın risk haritaları uzaktan algılama teknikleri ve FlamMap yazılımı yardımıyla geliştirilmiştir.

Çalışma alanı: Çalışma alanı Türkiye’nin batı Karadeniz bölgesinde bulunan Kastamonu ili, Taşköprü ilçesi, Bayam Orman İşletme Şefliği sınırlarını kapsamaktadır.

Materyal ve Yöntem: Çalışma alanının yanıcı madde miktarını tahmin etmek ve haritalamak için yanıcı madde modelleri kullanılmıştır. FlamMap yazılımı kullanılarak yanıcı madde miktarı, yanıcı madde nem içeriği, rüzgâr hızı ve eğim parametrelerine bağlı olarak yayılma oranı ve yangın şiddeti tahmin edilmiştir. Geçmişte çıkan yangın verileri ile baş yangın şiddeti haritaları çakıştırılarak potansiyel yangın tehlikesi olan yerler CBS ve uzaktan algılama teknikleri kullanarak belirlenmiştir.

Sonuçlar: Bölgenin %20,0’sının düşük (<2 m dakika-1), %43,2 'inin orta (2-15 m dakika-1), %12,0' ü yüksek (15-30 m dakika-1) ve %24,8’si sırasıyla, çok yüksek (> 30 m.dakika-1) yayılma oranına sahiptir. Yangın şiddeti haritasına göre, alanın %60,7’unun düşük (0-350 kW m-1), %24,9’nin orta (350-1700 kW m-1), %1,3'ü yüksek (1700-3500 kW m -1) ve %13,0'si çok yüksek (> 3500 kW m-1) yangın şiddeti sınıfında yer almaktadır.

Önemli Vurgular: Bu çalışmayla çalışma alanına ait yanıcı madde türlerinin mekansal dağılımı haritalanmış ve yangın davranışı parametrelerinden üçü (baş yangın şiddeti, yayılma oranı ve alev yüksekliği) uzaktan algılama ve CBS teknikleri kullanılarak tahmin edilmiştir. Daha önce yanan alanların yangın davranış modeli çıktı verileriyle uzamsal olarak çakıştırılması sonucunda, en çok yangına maruz kalan alanların % 40-70 kapalılığındaki karışık genç Anadolu karaçamı ile sarıçam meşcereleri ile kapalılığı %70'den fazla olan genç Anadolu karaçam meşcerelerinin bulunduğu alanlarda olduğu sonucuna varılmıştır.

Keywords

Yangın simülasyonu, yangın şiddeti, yayılma oranı, yangın risk haritası, Bayam Orman İşletme Şefliğ

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Assessing forest fire behavior simulation using FlamMap software and remote sensing techniques in Western Black Sea Region, Turkey

Year 2018, Volume: 18 Issue: 2, 171 - 188, 15.09.2018

Mehmet Yavuz , Bülent Sağlam Ömer Küçük Aydın Tüfekçioğlu

https://doi.org/10.17475/kastorman.459698

Cited By: 17

Abstract

Aim of study: Forest fuels are very critical for fire behavior models and hazard maps. Relationship among wind speed, fuel moisture content, slope, and fuel type directs us to predict fire behavior of a given region. For this study, we evaluated fire behavior parameters such as fireline intensity and rate of fire spread using the fuel moisture content, slope, fuel load, and wind speed for the Bayam Forest District with the help of remote sensing techniques and FlamMap software.

Area of study: The study area is located in Bayam Forest District in the city of Taskopru, Kastamonu, a Western Black Sea region of Turkey.

Material and Methods: In order to estimate and map forest fuel load of the study area, fuel models were developed using the parameters of the average vegetation height, 1-hr, 10-hr, and 100-hr fuel load, foliage, total fuel load, litter load and litter depth. Three basic fire descriptors (fireline intensity, rate of fire spread, and flame length) were calculated using FlamMap software with the parameters fuel load, wind speed, fuel moisture, and slope. Using the descriptors above, the historical fire data was overlaid with the fireline intensity maps to determine fire potential areas within the remote sensing and GIS framework.

Main results: The results of this study showed that 20.0% of the region had low (<2 m min-1), 43.2% had moderate (2-15 m min-1), 12.0% had high (15-30 m min-1), and 24.8% had very high (>30 m min-1) rate of fire spread, respectively. The fireline intensity map showed that 60.7% of the area was in low (0-350 kW m-1), 24.9% was in moderate (350-1700 kW m-1), 1.3% was in high (1700-3500 kW m-1), and 13.0% was in very high (>3500 kW m-1) fireline intensity.

Highlights: The spatial extent of fuel types was observed and three of the potential fire behavior predictors (fire intensity, rate of fire spread and flame length) were estimated using remote sensing and GIS techniques. The overlaid historical fire data showed that the most fire-prone areas are in the mixed young Anatolian black pine - Scots pine tree stands that have 40-70% canopy cover and that are in the young Anatolian black pine tree stands that have more than 70% canopy cover.

Keywords

Fire simulation, fire risk mapping, rate of fire spread, fireline intensity, Bayam Forest District

References

Yavuz, M., Saglam, B. (2012). Use of remote sensing and geographic information systems techniquies in forest fires. KSU Journal of Engineering Science (Special Issue), 235-242.
Yavuz, M., Saglam, B., Kucuk, O., Tufekcioglu, A. (2015). Assessing fuel load and fireline intensity in Bayam forest district, Turkey using Flam Map software and remote sensing techniquies. Paper presented at the International forest fire conference in Black Sea Region.
Zaimes, G. N., Tufekcioglu, M., Tufekcioglu, A., Zibtsev, S., Kaziolas, D., Yavuz, M., Trombitsky, I., Emmanouloudis, D., Uratu, R., Ghulijanyan, A. (2013). Innovative and sustainable use of stream water to suppress fires in protected areas: overview of the streams-2-suppress-fires project. Paper presented at the International Caucasia Forestry Symposium, Artvin, Turkey.
Zibtsev, S. V., Goldammer, J. G., Robinson, S., Borsuk, O. A. (2015). Fires in nuclear forests: silent threats to the environment and human security. Unasylva, 66(243/244), 40.
Yavuz, M., Saglam, B. (2012). Use of remote sensing and geographic information systems techniquies in forest fires. KSU Journal of Engineering Science (Special Issue), 235-242.
Mitsopoulos, I., Mallinis, G., Zibtsev, S., Yavuz, M., Saglam, B., Kucuk, O., Bogomolov, V., Borsuk, A., Zaimes, G.(2017). An integrated approach for mapping fire suppression difficulty in three different ecosystems of Eastern Europe. Journal of Spatial Science, 62(1), 139-155.
Nelson, R. M. (2001). Water relations of forest fuels Forest fires (pp. 79-149): Elsevier.
Pearce, H. G. (2009). Review of fire growth simulation models for application in New Zealand. Scion Fire Research Group, Christchurch, NZ. Client Report(16246).
Peterson, D. L., Evers, L., Gravenmier, R. A., Eberhardt, E. (2007). Analytical and decision support for managing vegetation and fuels: A consumer guide. Gen. Tech. Rep. PNW-GTR-690. Portland, OR: USDA Forest Service, Pacific Northwest Research Station.
Pyne, S. J., Andrews, P. L., Laven, R. D. (1996). Introduction to wildland fire (2nd ed.). New York: Wiley.
Rebain, S. A., Reinhardt, E. D., Crookston, N. L., Beukema, S. J., Kurz, W. A., Greenough, J. A., Robinson, D. C. E., Lutes, D. C. (2010). The fire and fuels extension to the forest vegetation simulator: updated model documentation. USDA For. Serv. Int. Rep, 408.
Rothermel, R. C. (1972). A mathematical model for predicting fire spread in wildland fuels. USDA For. Serv. Res. Pap. INT-115.
Rothermel, R. C. (1983). How to predict the spread and intensity of forest and range fires. USDA For. Serv. Gen. Tech. Rep. INT-143.
Roussopoulos, P. J., Loomis, R. M. (1979). Weights and dimensional properties of shrubs and small trees of the Great Lakes conifer forest.
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Details

Primary Language	English
Journal Section	Articles
Authors	Mehmet Yavuz Bülent Sağlam This is me Ömer Küçük This is me Aydın Tüfekçioğlu This is me
Publication Date	September 15, 2018
Published in Issue	Year 2018 Volume: 18 Issue: 2

Cite

APA	Yavuz, M., Sağlam, B., Küçük, Ö., Tüfekçioğlu, A. (2018). Assessing forest fire behavior simulation using FlamMap software and remote sensing techniques in Western Black Sea Region, Turkey. Kastamonu University Journal of Forestry Faculty, 18(2), 171-188. https://doi.org/10.17475/kastorman.459698
AMA	Yavuz M, Sağlam B, Küçük Ö, Tüfekçioğlu A. Assessing forest fire behavior simulation using FlamMap software and remote sensing techniques in Western Black Sea Region, Turkey. Kastamonu University Journal of Forestry Faculty. September 2018;18(2):171-188. doi:10.17475/kastorman.459698
Chicago	Yavuz, Mehmet, Bülent Sağlam, Ömer Küçük, and Aydın Tüfekçioğlu. “Assessing Forest Fire Behavior Simulation Using FlamMap Software and Remote Sensing Techniques in Western Black Sea Region, Turkey”. Kastamonu University Journal of Forestry Faculty 18, no. 2 (September 2018): 171-88. https://doi.org/10.17475/kastorman.459698.
EndNote	Yavuz M, Sağlam B, Küçük Ö, Tüfekçioğlu A (September 1, 2018) Assessing forest fire behavior simulation using FlamMap software and remote sensing techniques in Western Black Sea Region, Turkey. Kastamonu University Journal of Forestry Faculty 18 2 171–188.
IEEE	M. Yavuz, B. Sağlam, Ö. Küçük, and A. Tüfekçioğlu, “Assessing forest fire behavior simulation using FlamMap software and remote sensing techniques in Western Black Sea Region, Turkey”, Kastamonu University Journal of Forestry Faculty, vol. 18, no. 2, pp. 171–188, 2018, doi: 10.17475/kastorman.459698.
ISNAD	Yavuz, Mehmet et al. “Assessing Forest Fire Behavior Simulation Using FlamMap Software and Remote Sensing Techniques in Western Black Sea Region, Turkey”. Kastamonu University Journal of Forestry Faculty 18/2 (September 2018), 171-188. https://doi.org/10.17475/kastorman.459698.
JAMA	Yavuz M, Sağlam B, Küçük Ö, Tüfekçioğlu A. Assessing forest fire behavior simulation using FlamMap software and remote sensing techniques in Western Black Sea Region, Turkey. Kastamonu University Journal of Forestry Faculty. 2018;18:171–188.
MLA	Yavuz, Mehmet et al. “Assessing Forest Fire Behavior Simulation Using FlamMap Software and Remote Sensing Techniques in Western Black Sea Region, Turkey”. Kastamonu University Journal of Forestry Faculty, vol. 18, no. 2, 2018, pp. 171-88, doi:10.17475/kastorman.459698.
Vancouver	Yavuz M, Sağlam B, Küçük Ö, Tüfekçioğlu A. Assessing forest fire behavior simulation using FlamMap software and remote sensing techniques in Western Black Sea Region, Turkey. Kastamonu University Journal of Forestry Faculty. 2018;18(2):171-88.