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بررسی ریسک وقوع آتش‌سوزی عرصه های طبیعی استان کردستان به کمک تکنیک شاخص آماری | ||
| نشریه محیط زیست طبیعی | ||
| مقاله 10، دوره 72، شماره 3، مهر 1398، صفحه 403-416 اصل مقاله (1.21 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/jne.2019.271708.1594 | ||
| نویسندگان | ||
| نگار هدایتی1؛ حامد جنیدی جعفری1؛ شیرکو ابراهیمی محمدی* 2 | ||
| 1گروه مهندسی مرتع و آبخیزداری، دانشکده منابع طبیعی، دانشگاه کردستان، سنندج، ایران. | ||
| 2گروه مهندسی مرتع و آبخیزداری، دانشکده منابع طبیعی، دانشگاه کردستان، سنندج، ایران | ||
| چکیده | ||
| آتش سوزی به‌عنوان یکی از عوامل اصلی اختلال و تغییر در اکوسیستم‌های طبیعی محسوب می‌شود. شناسایی عوامل مؤثر در وقوع آتش‌سوزی و تهیه الگوی مکانی خطر آن یکی از ابزارهای اساسی جهت دست یابی به راهکارهای کنترل و مقابله با آتش‌سوزی است. آمارها حاکی از وقوع 1124 مورد آتش سوزی و سوختن 7364 هکتار از جنگلها و مراتع استان کردستان تنها بین سالهای 1385 تا 1394 هستند. لذا در این پژوهش اقدام به تهیه نقشه ریسک خطر آتش‌سوزی در عرصه-های طبیعی استان کردستان با استفاده از روش شاخص آماری (SI) و سیستم اطلاعات جغرافیایی (GIS) شد. در این پژوهش، به‌منظور ترسیم نقشه خطر آتش‌سوزی از 6 پارامتر شامل 3 متغیر طبیعی درصد شیب، جهت شیب، ارتفاع و سه متغیر انسانی فاصله از نزدیکترین روستا، فاصله از نزدیکترین جاده و فاصله از نزدیکترین زمین کشاورزی استفاده شد. از 1124 مورد آتش سوزی، 70 درصد داده‌ها (787 مورد) برای مدلسازی و 30 درصد (337 مورد) برای صحت سنجی مدل استفاده گردید. نتایج پژوهش نشان داد که حدود 50 درصد از مساحت استان کردستان (14400 کیلومترمربع) در کلاس خطر آتش‌سوزی زیاد و خیلی زیاد قرار دارند. همچنین یافته‌های حاکی از دقت بالای مدل شاخص آماری در شناسایی مناطق دارای خطر آتش‌سوزی با دقت 5/93 درصد (315 مورد از 337 مورد آتش سوزی) بود | ||
| کلیدواژه‌ها | ||
| مدل شاخص آماری؛ آتش‌سوزی؛ جنگلها و مراتع؛ سیستم اطلاعات جغرافیایی؛ استان کردستان | ||
| عنوان مقاله [English] | ||
| Fire risk assessment of Kurdistan province natural areas using statistical index method | ||
| نویسندگان [English] | ||
| Negar Hedayati1؛ Hamed Joneidi1؛ Shirko Ebrahimi Mohammadi2 | ||
| 1Department of Rangeland and watershed management, faculty of Natural resources, University of Kurdistan, Sanandaj, Iran. | ||
| 2Department of Range and Watershed engineering, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran | ||
| چکیده [English] | ||
| Fire is considered as one of the main causes of disruption and change in natural ecosystems. Identifying the effective factors in the occurrence of a fire and providing a spatial pattern of its risk is one of the basic tools for achieving fire control. The statistics showed that 1124 incidents of fire caused to burning of 7364 hectares of forests and rangelands in Kurdistan province, between 2006 and 2015. Therefore, in this research, a fire risk map was developed in natural areas in Kurdistan province using statistical index method (SI) and Geographic Information System (GIS). In this study, in order to prepare a fire hazard map, six parameters including three natural variables: slope percentage, aspect, elevation and three human variables, distance from the village, distance from the road and distance from the agricultural land were used. From all of 1124 fire cases, 70% of the data (787 cases) were used for modeling and 30% (337 cases) were used for model verification. The results showed that about 50% of the area of Kurdistan province (14400 km2) is in high and very high fire hazard classes. Also, findings showed the high accuracy of the statistical index method in identifying areas with a fire hazard with a precision of 93.5% (315 out of 337 cases of fire). | ||
| کلیدواژه‌ها [English] | ||
| statistical Index, Fire, forest and rangeland, GIS, Kurdistan province | ||
| مراجع | ||
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Ager, A.A., Barros, A.M.G. Day, M.A., Preisler, H.K., Spies, Th.A., and Bolte, J., 2018. Analyzing fine-scale spatiotemporal drivers of wildfire in a forest landscape model. Ecological Modelling. 384, 87-102. Ajin, R.S., Loghin, A.M., Vinod, P.G., and Jacob, M.K., 2016. Forest fire risk zone mapping using RS and GIS techniques: a study in Achankovil forest division, Kerala, India. Journal of Earth, Environment and Health Sciences, 2(3): 109-115. Cao, Ch., Xu, P., Wang, Y., Chen, J., Zheng, L., and Niu, C. 2016. Flash Flood Hazard Susceptibility Mapping Using Frequency Ratio and Statistical Index Methods in Coalmine Subsidence Areas. Sustainability, 8(948), 1-18. Cerda, A., and Robichaud, P.R. 2009. Fire effects on soils and restoration strategies. Science Publishers, Enfield, New Hampshire, 1- 605p. Chandra, S., 2005. Application of remote sensing and GIS technology in forest fire risk modeling and management of forest fires: A case study in the Garhwal Himalayan Region: 1239-1254. In: Van Oosterom, P., Zlatanova, S. and Fendel, M.E. (Eds.). Geo-information for disaster management. Springer, Berlin, Heidelberg, 1434 p. de Torres Curth, M., Biscayart, C., Ghermandi, L., Pfister, G., 2012. Wildland-urban interface fires and socioeconomic conditions: A case study of a Northwestern Patagonia city. Environ. Manage. 49, 876-891p. Dimopoulou, M. and and Giannikos, I. 2004. Towards an integrated framework for forest fire control. European Journal of Operational Research, 2, 476-486. Dong, X., Li-min, D., Gue- fan, Sh., Lei, T. and 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. Ebrahimi Mohammadi, Sh., Azari, M., and Manoochehri, E. 2016. Effects of Fire on Soil Properties, Erosion and Hydrologic Regime of Zrebar Lake Watershed. Journal of Water and Soil, 30(2), 618-631. (in Persian). Erten, E., Kurgun,V. and Musaoglue, N., 2004. Forest fire risk zone mapping from satellite imagery and GIS a case study. Proceedings of 20th Congress of ISPRS, Istanbul, Turkey, 29 Eskandari, S. 2015. Investigation on the relationship between climate change and fire in the forests of Golestan Province. Iranian Journal of Forest and Range protection research, 13(1), 1-10. (in Persian). Garavand, S., Yaralli, N., Sadeghi, H. 2013. Spatial pattern and mapping fire risk occurrence at natural lands of Lorestan province. Iranian journal of Forests and Poplar Research. 21(2), 231-242. (in Persian). Ghaemi Rad, T., and Karimi, M. 2015. Evaluating and Comparing the Results of Forest Fire Spreading Model Optimization based on Cellular Automata using PSO and ABC Algorithms. Scientific-Research Quarterly Geographical Data (SEPEHR), 24(93), 65-76. (in Persian). Hedayati, S.N. 2018. The role of climatic factors on Rangelande fire in Kurdistan province. M.Sc Thesis, Department of Rangeland and Watershed Management, Faculty of Natural Resources, University of Kurdistan. (in Persian). Jafarzadeh, A.A., Ahmadi, R., Fathi, H., and Naderi, M. 2016. Preparation of forest fire risk maps using logistic regression in GIS environment (Case study: Ilam forests). Forest strategical approchment journal. 1(2), 34-45. (in Persian). Jaiswal, R. K., Mukerjee, S., Raju, D. K. and Saxana, R., 2002. Forest fire risk zone mapping from satellite imagery and GIS. International Journal of Applied Earth observation and Geoinformation, 4: 1-1. Janbaz Ghobadi, Gh., Gholizadeh, B., and Majidi Dashliburun, O. 2012. Forest Fire Risk Zone Mapping From Geographic Information System in Northern Forests of Iran (Case study, Golestan province). International Journal of Agriculture and Crop Sciences (IJACS), 4(12), 818-824. (in Persian). Khanmohammadi, M., Rahimi, M., and Kartoolinezhad, D. 2016. Wildfires Risk Assessment of North-East Hyrcanyan Forests of Iran by using Keetch-Byram and Mc-Arthur Indices. Iranian Journal of Forest and Range protection research, 1(14), 48-57. (in Persian). Martinez, J., Vega-Garcia, C., Chuvieco, E., 2009. Human-caused wildfire risk rating for preventionplanning in Spain. J. Environ. Manage. 90, 1241-1252. Mohammadi Sarvaleh, F., Pir bavaghar, M., and Shabanian, N. 2014. Application of artificial neural network for forest fire risk mapping based on physiographic, human and climate factors in Sarvabad, Kurdistan province. Iranian Journal of Forest and Range protection research, 11(2), 97-107. (in Persian). Mozafari, Gh., and Safarpour, F. 2013. The Ecological Model of Pastures Zoning of Kurdistan Province Emphasizing on the Climatic Elements of Temperature and Precipitation. Geography and Sustainability of Environment, 3(6), 23-39. (in Persian). Nasr Azadani, A., Ghazi Fard, A., Shirani, K., and Safaei, H. 2013. Evaluating of Bivariate Statistical Analysis Method, by using GIS in Dez Olya Basin. Journal of Geospatial Information Technology, 1(1), 65-80. (in Persian). Poorhashemi, S., Amirahmadi, A., and Akbari, E. 2014. Selection of appropriate model between bivariate statistical methods for zoning of landslide hazard in GIS environment. Arid Regions Geographic Studies. 4(15), 71-89. (in Persian). Pyne, SJ, PL Andrews, and RD Laven. 1996. Introduction to Wildland Fire. 2nd ed. John Wiley & Sons, Inc. NY. Razavi Termeh, S.V., Mesgari, M.S., and kazemi, K. 2017. Evaluation and comparison of frequency ratio, statistic index and entropy methods for groundwater potential mapping using GIS (Case Study: Jahrom Township). ECOhydrology, 4(3), 725-736. (in Persian). Said, S.N.M.B.M., Zahran, E.S.M.M., and Shams, S. 2017. Forest Fire Risk Assessment Using Hotspot Analysis in GIS. The Open Civil Engineering Journal, 11, 786-801. Satir, O., Berberoglu, S., and Donmez, C. 2016. Mapping regional forest fire probability using artificial neural network model in a Mediterranean forest ecosystem. Geomatics, Natural Hazards and Risk, 7(5), 1645-1658. Somashekar, R., Ravikumar, P., Mohankumar, C., Prakash, K. and Nagaraja, B., 2009. Burnt area mapping of Bandipur National Park, India using IRS1C/1D LISS III data. Journal of the Indian Society of Remote Sensing. 37: 37-5. Vadrevu, K.P., Eaturu, A., and Badarinath, K.V.S. 2010. Fire risk evaluation using multicriteria analysis-a case study. Environmental Monitoring Assessment. 166 (1-4), 223-239. Van Westen, C.J. 1997. Statistical landslide hazard analysis, ILWIS 2.1 for Windows application guide, ITC Publication, Enschede, pp 73–84. Viegas, D. 2004. Slope and wind effect on fire propagation. International Journal of Wild Land Fire, 13, 143-156. Yakubu, L., Mireku-Gyimah, D., and Duker, A.A. 2015. Review of methods of modeling forest fire risk and hazard. African Journal of Environmental Science and Technology. 9(3), 155-165. You, W., Lin, L., Wu, Liyun., Ji, Zh., Yu, J., Zhu, J., Fan, Y., and He, D. 2017. Geographical information system-based forest fire risk assessment integrating national forest inventory data and analysis of its spatiotemporal variability. Ecological Indicators, 77, 176-184. Zarekar, A., Kazemi Zamani, B., Ghorbani, S., Ashegh Moalla, M., and Jafari, H.R. 2013. Mapping Spatial Distribution of Forest Fire using MCDM and GIS (Case Study: Three Forest Zones in Guilan Province). Iranian Journal of Forest and Poplar Research, 21(2), 218-230. (in Persian). | ||
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