Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2014 | 23 | 1 |
Tytuł artykułu

Evaluation of forest fire risk with GIS

Treść / Zawartość
Warianty tytułu
Języki publikacji
This paper uses GIS to describe and evaluate forest fire risk considering the most important factors affecting fire behavior at fine scales. The study was implemented in Yeşilova Forestry Enterprise in the Mediterranean city of Kahramanmaraş, Turkey. To determine an overall fire risk index for the study area, fire risk rating (extreme, high, moderate, or low) was assigned to decision variables (i.e. species composition, stand development stage, stand crown closure, slope, insolation, settlements, and roads) according to their risk potentials. Additionally, the visibility analysis of fire towers was carried out for monitoring of forests in the case study area. Finally, visibility analysis and a forest fire risk map were evaluated together for determining the efficiency of fire towers. Results indicated that more than half of the total forested area (65.7%) was classified as low category in the fire risk map. According to visibility analysis, the existing fire tower was able to monitor only 37% of forest areas; therefore, it was essential to consider new fire towers for monitoring the overall study area. After locating a potential new fire tower in the study area, it was found that about 71.8% of the area was with the visible zones of two fire towers.
Opis fizyczny
  • Faculty of Forestry, Kahramanmaras Sutcu İmam University, Kahramanmaras, Turkey
  • Faculty of Forestry, Artvin Coruh University, Artvin, Turkey
  • Faculty of Forestry, Kahramanmaras Sutcu İmam University, Kahramanmaras, Turkey
  • Faculty of Forestry, Kahramanmaras Sutcu İmam University, Kahramanmaras, Turkey
  • 1. MASELLI F., RODOLFI A., BOTTAI L., ROMANELLI S., CONESE C. Classification of Mediterranean vegetation by TM and ancillary data for the evaluation of fire risk. Int. J. Remote Sens. 21, 3303, 2000.
  • 2. CARMEL Y., PAZ S., JAHASHAN F., SHOSHANY M. Assessing fire risk using Monte Carlo simulations of fire spread. Forest Ecol. Manag. 257, 370, 2009.
  • 3. AKAY A.E., SESSIONS J., BETTINGER P., TOUPIN R., EKLUND A. Evaluating the salvage value of fire-killed timber by helicopter-effects of time since fire and Yarding distance. West J. Appl. For. 21, (2), 102, 2006.
  • 4. AKAY A.E., WING G.M., SIVRIKAYA F., SAKAR D. A GIS-based decision support system for determining the shortest and safest route to forest fires: a case study in Mediterranean Region of Turkey. Environ. Monit. Assess. 184, (3), 1391, 2012.
  • 5. ANONYMOUS. Forest Atlas. General Directorate of Forestry. 2007 [In Turkish].
  • 6. BONAZOUNTAS M., KALLIDROMITOU D., KASSOMENOS P., PASSAS N. Forest fire risk analysis. Hum. Ecol. Risk. Assess. 11, 617, 2005.
  • 7. CALABRI G. Forest fires in Italy in 1989 and 1990. International Forest Fire News (4), 1990.
  • 8. JAISWAL R.K., MUKHERJEE S., RAJU K.D., SAXENA R. Forest fire risk zone mapping from satellite imagery and GIS. Int. J. Appl. Earth Obs. 4, 1, 2002.
  • 9. CASTRO R., CHUVIECO E. Modeling forest fire danger from Geographical Information Systems. Geocarto. Int. 13, 15, 1998.
  • 10. DURMAZ B.D., KADIOĞULLARI A.I., BILGILI E., BAŞKENT E.Z., SAĞLAM B. Mapping fire development potential using Landsat satellite imagery. In Workshop on 3D Remote Sensing in Forestry. Vienna (Austria), pp. 307-314, 2006.
  • 11. ÇANAKCIOĞLU H. Forest Conservation. Istanbul University Press, Faculty of Forestry Press: Istanbul (Turkey). 1993 [In Turkish].
  • 12. MARTEL L.D. Forest Fires: Behaviour and Ecelogical Effects. (Johnson EA, Miyanishi K eds). Academic Press: London, pp. 594, 2001.
  • 13. OĞURLU İ. Determination of optimum fire observation point using set covering model. Turk. J. Agric. For. 14, 78, 1990 [In Turkish].
  • 14. CHUVIECO E., SALAS J. Mapping the spatial distribution of forest fire danger using GIS. Int. J. Geogr. Inf. Sci. 10, (3), 333, 1996.
  • 15. SAĞLAM B., BILGILI E., DURMAZ B.D., KÜÇÜK Ö., KADIOĞULLARI A.İ. Spatio-temporal analysis of forest fire risk and danger using LANDSAT imagery. Sensors. 8, 3970, 2008.
  • 16. KUTER N., YENILMEZ F., KUTER S. Forest fire risk mapping by kernel density estimation. Croat. J. For. Eng. 32, (2), 599, 2011.
  • 17. SIVRIKAYA F., AKAY A.E., OĞUZ H., YENILMEZ N. Mapping forest fire danger zones using GIS: A Case Study from Kahramanmaraş, In VI. International Symposium Ecology and Environmental Problems. Antalya (Turkey), 17-20 November, 2011.
  • 18. GAO X., FEI X., XIE H. Forest fire risk zone evaluation based on high spatial resolution RS image in Liangyungang Huaguo Mountain Scenic Spot. In: IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services. Fuzhou, (China), 2011.
  • 19. XIAO J., HUANG S., ZHONG A., ZHU B., YE Q., SUN L. A Study of Forest Fire Danger District Division in Lushan Mountain Based on RS and GIS. In: Proceeding of Remote Sensing for Environmental Monitoring, GIS Applications and Geology, 2009.
Typ dokumentu
Identyfikator YADDA
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.