اسکندری، سعیده؛ اسکندری، سمانه؛1400. آتشسوزی جنگل‌های ایران، پیامدها، روش‌های مقابله و راهکارها. انسان و محیط‌زیست. شماره 56. صص 187-175. https://he.srbiau.ac.ir/article_10459.html
جانباز قبادی، غلامرضا؛ 1398. بررسی مناطق خطر آتشسوزی جنگل در استان گلستان بر اساس شاخص خطر آتشسوزی با بهرهگیری از تکنیک GIS. تحلیل فضایی مخاطرات محیطی. دوره 6. شماره 3. صص 102-89.https://doi.org/10.29252/jsaeh.6.3.89
حیدری، مهدی؛ عطار روشن، سینا؛ جافریان، الهام؛ عبیات، محمد؛ 1400. مدل‌سازی و پهنه‌بندی مناطق مستعد آتشسوزی در جنگل‌های زاگرس با استفاده از سامانه اطلاعات جغرافیایی بر پایه رگرسیون لجستیک. جغرافیا و مخاطرات محیطی. دوره 10. شماره 2. صص 58-43.
زارع چاهوکی، محمدعلی؛ 1398. معیارها و شاخص‌های مؤثر در ارزیابی پایداری منابع طبیعی. پژوهشهای راهبردی در علوم کشاورزی و منابع طبیعی. دوره 4. شماره 1. صص 16-1.
شریف نژاد، طوبی؛ خاوریان نهزک، حسن؛ ورامش، سعید؛ 1400. ارزیابی قابلیت محصولات آتش سنجنده مادیس در شناسایی آتش‌‌سوزی‌‌ها در استان گلستان.
مخاطرات محیط طبیعی. دوره 10. شماره 30. صص 16-1.
https://doi.org/10.22111/jneh.2021.34138.1661
عابدی قشلاقی، حسن؛ ولی زاده، خلیل؛ 1397. ارزیابی و پهنه بندی خطر آتشسوزی جنگل با استفاده از تکنیکهای تصمیمگیری چند معیاره و GIS. مخاطرات طبیعی. دوره 7. شماره 15. صص 66-49.
علی‌نیا، اکرم؛ گندمکار، امیر؛ عباسی، علیرضا؛ 1400. تحلیل زمانی - مکانی رخدادهای مخاطره آتش‌سوزی‌های طبیعی در استان لرستان با استفاده از محصولات سنجندة مادیس. جغرافیا و پایداری محیط. دوره 11. شماره 1. صص 127-113.
مرکز پژوهشهای مجلس شورای اسلامی؛ 1399. علل، آثار، چالش‌ها و راهکارهای مقابله با آتش‌سوزی‌های جنگل‌ها و مراتع کشور. معاونت پژوهشهای تولیدی و زیربنایی. شماره مسلسل: 17288. 65 ص.
Abedi Gheshlaghi, H., Feizizadeh, B., Blaschke, T., 2020. GIS-based forest fire risk mapping using the analytical network process and fuzzy logic. Journal of Environmental Planning Management, 63, 481–499.
https://doi.org/10.1080/09640568.2019.1594726
Ågren, A.M., Lidberg, W., Strömgren, M., Ogilvie, J., Arp, P.A., 2014. Evaluating digital terrain indices for soil wetness mapping–a Swedish case study. Hydrology and Earth System Sciences. 18(9): 3623–34.
https://doi.org/10.5194/hess-18-3623-2014, 2014
Ajin, R.S., Loghin, A.M., Vinod, P.G., Jacob, M.K., 2017. 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, 23: 109–115.
https://doi.org/10.4103/2423-7752.199288
Ayanlade, A., 2016. Variation in diurnal and seasonal urban land surface temperature: landuse change impacts assessment over Lagos metropolitan city. Modeling Earth Systems and Environment. 2, 193.
https://doi.org/10.1007/s40808-016-0238-z
Busico, G., Giuditta, E., Kazakis, N., Colombani, N., 2019. A Hybrid GIS and AHP Approach for Modelling Actual and Future Forest Fire Risk Under Climate Change Accounting Water Resources Attenuation Role. Sustainability. 11(24), 7166.
https://doi.org/10.3390/su11247166
Chuvieco, E., Aguado, I., Yebra, M., Nieto, H., Salas, J., Martín, M.P., Vilar, L., Martínez-Vega, J., Martín, S., Ibarra, P., et al. 2010. Development of a framework for fire risk assessment using remote sensing and geographic information system technologies. Ecological Modelling. 221: 46–58.
https://doi.org/10.1016/j.ecolmodel.2008.11.017
Çolak, E., Sunar, F., 2020. Evaluation of forest fire risk in the Mediterranean Turkish forests: A case study of Menderes region, Izmir. International Journal of Disaster Risk Reduction. 45, 101479.
https://doi.org/10.1016/j.ijdrr.2020.101479
Conrad, O., Bechtel, B., Bock, M., Dietrich, H., Fischer, E., Gerlitz, L., Wehberg, J., Wichmann, V., Böhner, J., 2015. System for Automated Geoscientific Analyses (SAGA) v. 2.1.4, Geosci. Model Dev., 8, 1991-2007.
https://doi.org/10.5194/gmd-8-1991-2015
Erdin, C., Çağlar, M., 2021. Rural Fire Risk Assessment in GIS Environment Using Fuzzy Logic and the AHP Approaches. Polish Journal of Environmental Studies, 30(6), 4971-4984.
https://doi.org/10.15244/pjoes/136009
Eskandari, S., Miesel, JR., 2017. Comparison of the fuzzy AHP method, the spatial correlation method, and the Dong model to predict the fire high-risk areas in Hyrcanian forests of Iran. Geomatics, Natural Hazards and Risk, 8:2, 933-949.
https://doi.org/10.1080/19475705.2017.1289249
Faramarzi, H., Hosseini, SM., Pourghasemi, HR., Farnaghi, M., 2021. Forest fire spatial modelling using ordered weighted averaging multi-criteria evaluation. Journal of Forest Science, 67, 87−100. https://doi.org/10.17221/50/2020-JFS
Fassnacht, F., Schmidt-Riese, E., Kattenborn, T., Hernández, J., 2021. Explaining Sentinel 2-based dNBR and RdNBR variability with reference data from the bird’s eye (UAS) perspective. International Journal of Applied Earth Observation and Geoinformation, 95, 102262.
https://doi.org/10.1016/j.jag.2020.102262
Hislop, S., Haywoodc, A., Jonesa, S., Soto-Berelova,M., Skidmore A., Nguyena, T., 2020. A satellite data driven approach to monitoring and reporting fire disturbance and recovery across boreal and temperate forests. International Journal of Applied Earth Observation Geoinformation. 87.
https://doi.org/10.1016/j.jag.2019.102034
Jaafari, A., Mafi-Gholami, D., Pham, B.T., Tien Bui, D., 2019. Wildfire probability mapping: Bivariate vs. multivariate statistics. Remote Sensing.
11
, 618.
https://doi.org/10.3390/rs11060618
Li, J., Zhao, Y., Zhang, A., Song, B., Hill, R.L., 2021. Effect of grazing exclusion on nitrous oxide emissions during freeze-thaw cycles in a typical steppe of Inner Mongolia. Agriculture Ecosystem Environment. 307, 107217.
https://doi.org/10.1016/j.agee.2020.107217
Masinda, M.M., Sun, L., Wang, G., Hu, T., 2021. Moisture content thresholds for ignition and rate of fire spread for various dead fuels in northeast forest ecosystems of China. Journal of Forestry Research. 32: 1147–1155.
https://doi.org/10.1007/s11676-020-01162-2
Mattivi, P., Franci, F., Lambertini, A. Bitelli, G., 2019. TWI computation: a comparison of different open source GISs. Open Geospatial Data, Software and Standards. 4, 6.
https://doi.org/10.1186/s40965-019-0066-y
Novo, A., Fariñas-Álvarez, N., Martínez-Sánchez, J., González-Jorge, H., Fernández-Alonso, JM., Lorenzo, H., 2020. Mapping forest fire risk—a case study in Galicia (Spain). Remote Sensing. 12(22):1–20.
https://doi.org/10.3390/rs12223705
Nuthammachot, N., Stratoulias, D. 2021. A GIS-and AHP-based approach to map fire risk: A case study of Kuan Kreng peat swamp forest, Thailand. Geocarto International., 36, 212–225.
https://doi.org/10.1080/10106049.2019.1611946
Pham, B.T., Jaafari, A., Phong, T.V., Yen, H., Tuyen, T., Luong, V., Nguyen, H.D., Le, H.V., Foong, L.K., 2021. Improved flood susceptibility mapping using a best first decision tree integrated with ensemble learning techniques. Geoscience Frontiers. 12, 101105.
https://doi.org/10.1016/j.gsf.2020.11.003
Piao, Y., Lee, D., Park, S., Gul, H. Jin, Y., 2022. Forest fire susceptibility assessment using google earth engine in Gangwon-do, Republic of Korea. Geomatics, Natural Hazards and Risk. 13(1): 432-450.
https://doi.org/10.1080/19475705.2022.2030808
Pourghasemi, H.R., 2015. GIS-based forest fire susceptibility mapping in Iran a comparison between evidential belief function and binary logistic regression models. Scandinavian Journal of Forest Research, 9(3), 155–165.
https://doi.org/10.1080/02827581.2015.1052750
Pourghasemi, H.R., Beheshtirad, M., Pradhan, B., 2016. A comparative assessment of prediction capabilities of modified analytical hierarchy process (MAHP) and Mamdani fuzzy logic models using Netcad-GIS for forest fire susceptibility mapping. Geomatics, Natural Hazards and Risk, 7(2):861–885.
https://doi.org/10.1080/19475705.2014.984247
Saaty, L.T., 1984. The Analytic Hierarchy Process: Decision Making in Complex Environments. In: Avenhaus, R., Huber, R.K. (eds) Quantitative Assessment in Arms Control. Springer, Boston, MA.
https://doi.org/10.1007/978-1-4613-2805-6_12
Tomar, J.S., Kranjcic, N., Ðurin, B., Kanga, S., Singh, S.K. 2021. Forest Fire Hazards Vulnerability and Risk Assessment in Sirmaur District Forest of Himachal Pradesh (India): A Geospatial Approach. ISPRS International Journal of Geo-Information. 10, 447.
https://doi.org/10.3390/ijgi10070447
Yathish, H., Athira, K.V., Preethi, K., Pruthviraj, U., Shetty, A., 2019. A Comparative Analysis of Forest Fire Risk Zone Mapping Methods with Expert Knowledge. Journal of the Indian Society of Remote Sensing. 47: 2047-2060.
https://doi.org/10.1007/s12524-019-01047-w
Zareian, G.R., Azadi, A. and Shakeri, S., 2021. Evaluation of soil fertility map for bean cultivation in Eghlid Plain by using Hybrid Fuzzy-AHP and GIS techniques. Iran Agricultural Research, 40(1):101-112. https:// iar.shirazu.ac.ir/ article_ 6291_ 533038d9a 7eeebb64d797f9eb3b6d291.pdf?lang=fa
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