Orman Yangını Riskinin CBS Kullanılarak Niğde Örneğinde Belirlenmesi

Year 2022, , 77 - 94, 15.04.2022

Orhun Soydan

https://doi.org/10.24011/barofd.1078642

Cited By: 4

Abstract

Bu çalışmanın temel amacı, CBS kullanarak orman yangın risk haritası hazırlamak için istatistiksel bir model geliştirmektir. Bu çalışmada orman yangını riskini belirlemek için arazi kullanımı/arazi örtüsü tipi, eğim, bakı, rakım, yerleşim, yol, sıcaklık ve yağış gibi sekiz önemli faktör kullanılmıştır. Faktörleri değerlendirmek için Analitik Hiyerarşi Süreci (AHP) kullanılmıştır. Yağış ve sıcaklık orman yangını riskini belirleyen en önemli faktörler olarak belirlenmiştir. Çalışma alanı yaklaşık %10.72 düşük yangın riski, %28.21 orta yangın riski, %43.50 yüksek yangın riski, %14.65 çok yüksek yangın riski ve %2.92 aşırı orman yangını riskine sahiptir. Çalışma alanının %61,07'si yüksek, çok yüksek ve aşırı orman yangını riskine sahiptir. Orman yangınlarını önlemek için arazi örtüsü/arazi kullanımı ormanlara zarar vermeyecek şekilde planlanmalıdır. Özellikle ormanların yakınında bulunan araç yolları, otoyollar vb. alanlarının yangın riskini yükselttiği unutulmamalıdır. Bu nedenle bu alanlar ormanlara zarar vermeyecek şekilde planlanmalıdır. Çalışma alanının iklimsel özellikleri incelenmeli, kentsel doku rüzgâr ve yağış gibi mikro iklim faktörlerini engelleyecek şekilde planlanmamalıdır.

Keywords

Çevre koruma, çevre yönetimi, orman, CBS, yangın risk analizi

Determination of Forest Fire Risk Using GIS: A Case Study in Nigde, Turkey

Abstract

The main purpose of this study is to develop a statistical model to prepare forest fire risk map using GIS. In this study eight important factors were used to determining the forest fire risk such as land use/land cover type, slope, aspect, altitude, settlement, road, temperature and precipitation. The analytic hierarchy process (AHP) was used to evaluate the factors. Precipitation and temperature were the most important factors to determining the forest fire risk. The study area has approximately 10.72% low fire risk, 28.21% moderate fire risk, 43.50% high fire risk, 14.65% very high fire risk, and 2.92% extreme forest fire risk. 61.07% of the study area has a high, very high and extreme forest fire risk. In order to prevent forest fires, land cover/land use should be planned in a way that does not damage forests. Especially vehicle roads, expressways, etc. which are located near the forests, have a high fire risk. Therefore, these areas should be planned in a way that will not damage the forests. The climatic characteristics of the study area should be examined, the urban texture should not be in a way to prevent microclimatic factors such as wind and precipitation.

Keywords

Environmental preservation, environmental management, forest, GIS, fire risk analysis

References

• Al-Harbi, K. M. A. S. (2001). Application of the AHP in project management. International Journal of Project Management, 19(1), 19-27.
• Ateșoğlu, A., Melemez, K., Uğur, B. (2015). Determination of pumper truck intervention ratios in zones with forest fire potential: case study for Bartın Regional Forest Directorate. Journal of Applied Remote Sensing, 16(1), 132-143.
• Bilgili, E. (2003). Stand development and fire behaviour. Forest Ecology and Management, 179(1), 333-339.
• Bilici, E. (2009). A study on the integration of firebreaks and fireline with forest roads networks and it's planning and construction (a case study of Gallipoly National Park). Journal of Istanbul University Faculty of Forestry Series A, 59(2), 86–102.
• Carmel, Y., Paz, S., Jahashan, F., Shoshany, M. (2009). Assessing fire risk using Monte Carlo simulations of fire spread. Forest Ecology and Management, 257(1), 370-377.
• Bingöl, B. (2017). Determination of Forest Fire Risk Areas in Burdur Province Using Geographical Information Systems. Turkish Journal of Forest Science, 1(2), 169-182.
• Çoban, H. O., Erdin, C. (2020). Forest fire risk assessment using GIS and AHP integration in Bucak forest enterprise, Turkey. Applied Ecology and Environmental Research, 18(1), 1567-1583.
• Dağdeviren, M., Tamer, E. (2001). Analytical hierarchy process and use of 0-1 goal programming methods in supplier selection. Journal of the Faculty of Engineering and Architecture of Gazi University, 16(1), 41-52.
• Demir, M., Kucukosmanoglu, A., Hasdemir, M., Acar, H., Ozturk, T. (2009). Assessment of forest roads and firebreaks in Turkey. African Journal of Biotechnology, 8(18), 4553-4561.
• Dilekçi, S., Marangoz, A. M., Ateşoglu, A. (2019). Zonguldak and Eregli Forest Management Directorates of Forestry Fire Risk Areas Determination. Geomatik, 6(1), 44-53.
• Erten, E., Kurgun, V., Musaoglu, N. (2004). Forest fire risk zone mapping from satellite imagery and GIS: a case study. XXth Congress of the International Society for Photogrammetry and Remote Sensing, 222-230, 12-23 July 2004, Istanbul.
• Estoque, R. C., Murayama, Y., Myint, S. W. (2017). Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia. Science of the Total Environment, 577, 349-359.
• Eugenio, FC, Dos Santos, AR., Fiedler, NC., Ribeiro, GA., Da Silva, AG., Dos Santos, ÁB., Schettino, VR. (2016). Applying GIS to develop a model for forest fire risk: a case study in Espírito Santo, Brazil. Journal of Environmental Management, 173, 65-71.
• Gao, X., Fei, X., Xie, H. (2011). Forest fire risk zone evaluation based on high spatial resolution RS image in Liangyungang Huaguo Mountain Scenic Spot. International Conference on Spatial Data Mining and Geographical Knowledge Services, 1, 593-596.
• Gazzard, R. (2012). Risk Management Control Measure: Toolkit for Practitioners and Advisors. UK Vegetation Fire Risk Management Press: London, 24 pages.
• General Directorate of Meteorology. (2019). Chart of Nigde City rainfall intensity over time. Ankara: Republic of Turkey, Ministry of Agriculture and Forestry, https://www.mgm.gov.tr/ (01.09.2021).
• Gigović, L,. Jakovljević, G., Sekulović, D., Regodić, M. (2018). GIS Multi-Criteria Analysis for Identifying and Mapping Forest Fire Hazard: Nevesinje, Bosnia and Herzegovina. Tehnički Vjesnik 25(3), 891-897.
• Hasdemir, M., Küçükosmanoğlu, A., Demir, M., Öztürk, T., Akgül, M., Bilici, E. (2009). Evaluation of the Forest Roads, Fire Safety Roads and Ribbon in Context of Prevention Forest Fire. I. Prevention Forest Fires Symposium, 419-425, 07-10 Jan. 2009, Ankara.
• Jaiswal, R. K., Mukherjee, S., Raju, K. D., Saxena, R. (2002). Forest fire risk zone mapping from satellite imagery and GIS. International Journal of Applied Earth Observation and Geoinformation, 4(1), 1-10.
• Karabulut, M., Karakoç, A., Gürbüz, M., Kızılelma, Y. (2013). Determination of Forest Fire Risk Areas Using Geographical Information Systems in Başkonuş Mountain (Kahramanmaraş). The Journal of International Social Research, 6(24), 171-179.
• Kenar, N. (2014). Notes and contributions on the flora of Melendiz Mountains and its surroundings (Niğde, Turkey). Flora Mediterranea, 24(1), 109-138.
• Kovacs, J. M., Malczewski, J., Flores-Verdugo, F. (2004). Examining local ecological knowledge of hurricane impacts in a mangrove forest using an analytical hierarchy process (AHP) approach. Journal of Coastal Research, 20(3), 792-800.
• Kumari, B., Pandey, A. C. (2020). Geo-informatics based multi-criteria decision analysis (MCDA) through analytic hierarchy process (AHP) for forest fire risk mapping in Palamau Tiger Reserve, Jharkhand state, India. Journal of Earth System Science, 129(1), 1-16.
• Lin, J., Sergio, R. (2009). A derivation of the statistical characteristics of forest fires. Ecological Modelling. 220(7), 898-903.
• Ljubomir, G., Pamučar, D., Drobnjak, S., Pourghasemi, H. R. (2019). Modelling the spatial variability of forest fire susceptibility using geographical information systems and the analytical hierarchy process. In Spatial Modelling in GIS and R fFor Earth and Environmental Sciences, 4(1), 337-369.
• Malik, T., Rabbani, G., Farooq, M. (2013). Forest fire risk zonation using remote sensing and GIS technology in Kansrao Forest Range of Rajaji National Park, Uttarakhand, India. India. Inter. J. of advanced RS and GIS, 2(1), 86-95.
• Mahdavi, A. (2012). Forests and rangelands? Wildfire risk zoning using GIS and AHP techniques. Caspian Journal of Environmental Sciences, 10(1), 43-52.
• Mohammadi, K., Hosseini, S. A., Lotfian, M., Najafi, A. (2010). Planning road network in mountain forests using GIS and Analytic Hierarchical Process (AHP). Caspian Journal of Environmental Sciences, 8(2), 151-162.
• Nuthammachot, N., Stratoulias, D. (2019). A GIS-and AHP-based approach to map fire risk: a case study of Kuan Kreng peat swamp forest, Thailand. Geocarto International, 36(2), 212-225.
• Özkazanç, N. K., Ertuğrul, M. (2011). Effects of Forest Fires on Fauna. Journal of Bartin Faculty of Forestry, 13(19), 128-135.
• Nigde Forestry Directorate. (2019). Provincial Environmental Status Report. Ministry of agriculture and forestry Press: Nigde, 65 pages
• Özşahin, E. (2014). Forest Fire Sensitivity Analysis Using GIS and AHS: Example of the Antakya Forest Enterprise Directorate. Route Educational and Social Science Journal, 1(1), 50-71.
• Pradhan, B., Suliman, M. D. H. B., Awang, M. A. B. (2007). Forest fire susceptibility and risk mapping using remote sensing and geographical information systems (GIS). Disaster Prevention and Management: An International Journal, 16(2), 46-65.
• Saaty, T. L. (1977). A scaling method for priorities in hierarchical structures. Journal of mathematical Psychology, 15(3), 234-281.
• Sağlam, B., Bilgili, E., Dincdurmaz, B., Kadiogulari, A. I., Küçük, Ö. (2008). Spatio-temporal analysis of forest fire risk and danger using LANDSAT imagery. Sensors, 8(6), 3970-3987.
• Soydan, O. (2021). Solar power plants site selection for sustainable ecological development in Nigde, Turkey. SN Applied Sciences, 3(1), 1-18.
• Toksarı, M. (2007). Determining the target market for the furniture industry in the Aegean region using analytical hierarchy process approach. Management and Economics, 14(1), 171-180.
• Vadrevu, K. P., Eaturu, A., Badarinath, K. (2010). Fire risk evaluation using multicriteria analysis—a case study. Environ. Environmental monitoring and assessment, 166(1), 223-239.
• Van Der Werf, G. R., Randerson, J. T., Collatz, G. J., Giglio, L., Kasibhatla, P. S., Arellano, A. F., Kasischke, E. S. (2004). Continental-scale partitioning of fire emissions during the 1997 to 2001 El Nino/La Nina period. Science, 303(5654), 3-76.
• Van Hoang, T., Chou, T. Y., Fang, Y. M., Nguyen, N. T., Nguyen, Q. H., Xuan Canh, P., Meadows, M. E. (2020). Mapping Forest Fire Risk and Development of Early Warning System for NW Vietnam Using AHP and MCA/GIS Methods. Applied Sciences, 10(12), 4348.