Abstract
Kahramanmaras province is located in an area where Mediterranean, Eastern Anatolia and Southeast Anatolia eco-regions are the nearest to each other. Southern regions of the province, in particular, are dominated by Mediterranean climate and correspond to high susceptible areas in terms of forest fires. In this study, the distribution of forest fires in Kahramanmaras province was analyzed based on the outbreak points of 376 forest fires (2012-2017) recorded by Kahramanmaras Regional Directorate of Forestry. This analysis was carried out considering the factors affecting forest fire risk (vegetation, altitude, slope, aspect, temperature, precipitation, distance to settlement, distance to roads). By using GIS (Geographical Information Systems) techniques and AHP (Analytical Hierarchy Process) method, fire-susceptible areas were mapped in Kahramanmaras province at the end of the analysis conducted based on the distribution of the number of forest fires by factors that affect fire. Accordingly, 46.2% of Kahramanmaras province are high susceptible to forest fire, 47.6% are very high and 4.1% are extremely susceptible. The moderate susceptible areas are 30.197 ha, accounting for only 2.1% of the province land. There is no low susceptible area. All these values indicate that the geographical conditions at the location where the province is located are high susceptible to forest fires.
References
- Bilgili, E. Saglam, B., Baskent, Z. E., (2001), Fire danger rating and geographical ınformation systems in fire management planning , Journal of Science and Engineering, 4(2), 88-97.
- Bingol, B., (2017), Determination of forest fire risk areas in Burdur province using geographic information systems, Turkish Journal Of Forest Science 1(2) 2017: 169-182.
- Caceres, C. F., (2011), Using GIS in hotspots analysis and for forest fire risk zones mapping in the Yeguare Region, Southeastern Honduras, 13, Papers in Resource Analysis, 14 pp. Saint Mary’s University of Minnesota University Central Services Press. Winona, MN. Retrieved (date) http://www.gis.smumn.edu.
- Chuvieco, E.; Congalton, R.G., (1989), Application of remote sensing and geographic information systems to forest fire hazard mapping. Remote Sens. Environ. 29, 147-159.
- Doganay, H., Doganay, S., (2004), Forest fires and measures to be taken in Turkey, Eastern Geographical Journal, 11/29, 147-159.
- Dong, X., Li-min, D., Guo-fan, S., Lei, T., Hui, W., (2005), Forest fire risk zone mapping from satellite images and GIS for Baihe Forestry Bureau, Jilin, China, Journal of Forestry Research, 16 (3), 169-174.
- Eugenio, F.C., Santos, A.R., Fiedler, N.C., Ribeiro, G.A., Silva, A.G., Santos, A.B., Paneto, G.G., Schettino, V.R., (2016), Applying GIS to develop a model for forest fire risk: A case study in Espírito Santo, Brazil, J Environ Manage 173, 65-71
- George, L.W., Ashley Perry, D., Sparrow L. F. O., (1999), A GIS-supported model for the simulation of the spatial structure of wildland fire, Cass Basin, New Zeland, Journal of Applied Ecology, 36(4), 502-518.
- Ghobadi, G. J., Gholizadeh, B., Dashliburun, O. M., (2012), Forest fire risk zone mapping from geographic ınformation system in northern forests of Iran (Case study, Golestan province), International Journal of Agriculture and Crop Sciences, 4 (12), 818-824.
- Goodrick, S., Jim, B., (1999), Florida's fire management information system, In proceedings from the joint fire science conference and workshop, Moscow, Idaho: University of Idaho, 1, 3-11.
- Jaiswal, R., Saumitra, M., Kumaran, D., Rajesh, S., (2002), Forest fire risk zone mapping from satellite imagery and GIS, International Journal of Applied Earth Observation and Geo-information, 4, 1-10.
- Joaquim, G. S., Bahaaeddin, A. E., Josep, R. C., (2007), Remote Sensing Analysis to Detect Fire Risk Locations, GeoCongres-2007, Quebec, Canada.Karabulut, M., Karakoc, A., Gürbüz, M., Kızılelma, Y., (2013), Determination of forest fire risk areas using geographical ınformation systems in Baskonus Mountain (Kahramanmaras), The Journal of International Social Research, 6 (24), 171-179.
- Keramitsoglou, I., Kiranoudis, C.T., Sarimveis, H., at al., (2004), A multisplinary decision support for system for forest fire crisis management, Environmental Management, 33(2), 212-225.
- Lymberopoulos, N., Papadopoulos, C., Stefanakis, L., et. al., (1996), A GIS-based forest fire management information system, EARSEL Advances in Romote Sensing, 4(4), 68-75.
- Mahdavi, A., Fallah Shamsi, S. R., Nazari, R., (2012), Forests and rangelands’ wildfire risk zoning using GIS and AHP techniques, Caspian Journal of Environmental Sciences, 10 (1), 43-52.
- Mohammadi, F., Shabanian, N., Pourhashemi, M., Fatehi, P., (2010), Risk zone mapping of forest fire using GIS and AHP in a part of Paveh forests, Iranian Journal of Forest and Poplar Research, 18 (4), 586.
- Ozsahin, E., (2014), Forest fire susceptibility analysis using GIS and AHP: the case of Antakya Forestry Operation Directorate, Route Educational and Social Science Journal Volume 1(3), 50-71.
- Saglam, B., Ertugrul, B., Durmaz, B. D., Kadıoğulları, A. I., Küçük, O., (2008), Spatio-temporal analysis of forest fire risk and danger using LANDSAT imagery, Sensors,8, 3970-3987.
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Abstract
Kahramanmaraş İli, Akdeniz, Doğu
Anadolu ve Güneydoğu Anadolu ekolojik bölgelerinin birbirine en çok yaklaştığı
yerde konumlanmıştır. İlde özellikle Akdeniz ikliminin egemen olduğu güney
kesimler, orman yangınları açısından son derece hassas alanlara karşılık
gelmektedir. Bu çalışmada Kahramanmaraş Orman Bölge Müdürlüğü kayıtlarındaki
(2012-2017) 376 orman yangınının başlangıç noktaları esas alınarak,
Kahramanmaraş İl’inde orman yangınlarının dağılımları analiz edilmiştir. Bu
analiz, orman yangını riskini etkileyen faktörler (bitki örtüsü, yükselti,
eğim, bakı, sıcaklık, yağış, yerleşmeye uzaklık, yollara uzaklık) göz önünde
bulundurularak yapılmıştır. CBS (Coğrafi Bilgi Sistemleri) teknikleri ile AHS
(Analitik Hiyerarşi Süreci) yöntemi kullanarak, yangın sayısının yangını
etkileyen faktörlere göre dağılımı esas alınmış, yapılan analizler sonucunda
Kahramanmaraş İl’inde yangına duyarlı alanlar haritalanmıştır. Buna göre orman
yangını için Kahramanmaraş İl topraklarının %46.2'si yüksek derecede, %47.6'sı
çok yüksek derecede ve %4.1'i de ekstrem derecede duyarlıdır. Orta derecede
duyarlı olan alanlar ise 30.197 ha olup il arazisinin sadece %2.1'ini
oluşturmaktadır. Düşük derecede duyarlı alan ise bulunmamaktadır. Tüm bu
değerler ilin bulunduğu konumda coğrafi koşulların orman yangını için yüksek
duyarlılık gösterdiğini ifade etmektedir.
Keywords
References
- Bilgili, E. Saglam, B., Baskent, Z. E., (2001), Fire danger rating and geographical ınformation systems in fire management planning , Journal of Science and Engineering, 4(2), 88-97.
- Bingol, B., (2017), Determination of forest fire risk areas in Burdur province using geographic information systems, Turkish Journal Of Forest Science 1(2) 2017: 169-182.
- Caceres, C. F., (2011), Using GIS in hotspots analysis and for forest fire risk zones mapping in the Yeguare Region, Southeastern Honduras, 13, Papers in Resource Analysis, 14 pp. Saint Mary’s University of Minnesota University Central Services Press. Winona, MN. Retrieved (date) http://www.gis.smumn.edu.
- Chuvieco, E.; Congalton, R.G., (1989), Application of remote sensing and geographic information systems to forest fire hazard mapping. Remote Sens. Environ. 29, 147-159.
- Doganay, H., Doganay, S., (2004), Forest fires and measures to be taken in Turkey, Eastern Geographical Journal, 11/29, 147-159.
- Dong, X., Li-min, D., Guo-fan, S., Lei, T., Hui, W., (2005), Forest fire risk zone mapping from satellite images and GIS for Baihe Forestry Bureau, Jilin, China, Journal of Forestry Research, 16 (3), 169-174.
- Eugenio, F.C., Santos, A.R., Fiedler, N.C., Ribeiro, G.A., Silva, A.G., Santos, A.B., Paneto, G.G., Schettino, V.R., (2016), Applying GIS to develop a model for forest fire risk: A case study in Espírito Santo, Brazil, J Environ Manage 173, 65-71
- George, L.W., Ashley Perry, D., Sparrow L. F. O., (1999), A GIS-supported model for the simulation of the spatial structure of wildland fire, Cass Basin, New Zeland, Journal of Applied Ecology, 36(4), 502-518.
- Ghobadi, G. J., Gholizadeh, B., Dashliburun, O. M., (2012), Forest fire risk zone mapping from geographic ınformation system in northern forests of Iran (Case study, Golestan province), International Journal of Agriculture and Crop Sciences, 4 (12), 818-824.
- Goodrick, S., Jim, B., (1999), Florida's fire management information system, In proceedings from the joint fire science conference and workshop, Moscow, Idaho: University of Idaho, 1, 3-11.
- Jaiswal, R., Saumitra, M., Kumaran, D., Rajesh, S., (2002), Forest fire risk zone mapping from satellite imagery and GIS, International Journal of Applied Earth Observation and Geo-information, 4, 1-10.
- Joaquim, G. S., Bahaaeddin, A. E., Josep, R. C., (2007), Remote Sensing Analysis to Detect Fire Risk Locations, GeoCongres-2007, Quebec, Canada.Karabulut, M., Karakoc, A., Gürbüz, M., Kızılelma, Y., (2013), Determination of forest fire risk areas using geographical ınformation systems in Baskonus Mountain (Kahramanmaras), The Journal of International Social Research, 6 (24), 171-179.
- Keramitsoglou, I., Kiranoudis, C.T., Sarimveis, H., at al., (2004), A multisplinary decision support for system for forest fire crisis management, Environmental Management, 33(2), 212-225.
- Lymberopoulos, N., Papadopoulos, C., Stefanakis, L., et. al., (1996), A GIS-based forest fire management information system, EARSEL Advances in Romote Sensing, 4(4), 68-75.
- Mahdavi, A., Fallah Shamsi, S. R., Nazari, R., (2012), Forests and rangelands’ wildfire risk zoning using GIS and AHP techniques, Caspian Journal of Environmental Sciences, 10 (1), 43-52.
- Mohammadi, F., Shabanian, N., Pourhashemi, M., Fatehi, P., (2010), Risk zone mapping of forest fire using GIS and AHP in a part of Paveh forests, Iranian Journal of Forest and Poplar Research, 18 (4), 586.
- Ozsahin, E., (2014), Forest fire susceptibility analysis using GIS and AHP: the case of Antakya Forestry Operation Directorate, Route Educational and Social Science Journal Volume 1(3), 50-71.
- Saglam, B., Ertugrul, B., Durmaz, B. D., Kadıoğulları, A. I., Küçük, O., (2008), Spatio-temporal analysis of forest fire risk and danger using LANDSAT imagery, Sensors,8, 3970-3987.
- Saaty, T. L., (1994), How to make a decision: the analytic hierarchy process, Interfaces, 24, 19–43.
- Saaty, T. L., Vargas, L. G., Dellman, K., (2003),The allocation of instangible resources: the analytic hierarchy process and linear programming, Socio-Economic Planning Sciences, 37, 169-189.
- Sharma, D., Hoa, V., Cuong, V., Tuyen, T., Sharma, N., (2009), Forest fire risk zonation for Jammu district forest division using remote sensing and GIS, 7th FIG Regional Conference-2009, Hanoi, Vietnam.
- Vadrevu, K. P., Eaturu, A., Badarinath, K. V. S., (2010), Fire risk evaluation using multicriteria analysis—a case study, Environmental Monitoring and Assessment, 166 (1-4), 223-239.
- Wind, Y., Saaty, T. L., (1980), Marketing applications of the analytic hierarchy process, Management Science, 26 (7), 641- 658.
Details
| Primary Language | English |
|---|---|
| Subjects | Human Geography |
| Journal Section | Articles |
| Authors | |
| Publication Date | October 1, 2018 |
| Published in Issue | Year 2018Volume: 8 Issue: 16 |
Cited By
Fire susceptibility modeling and mapping in Mediterranean forests of Turkey: a comprehensive study based on fuel, climatic, topographic, and anthropogenic factors
Euro-Mediterranean Journal for Environmental Integration
https://doi.org/10.1007/s41207-024-00475-6
