Volume 24, Issue 75 (12-2024)
jgs 2024, 24(75): 480-492 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Alinia A, Gandomkar A, Abasi A. (2024). Time Series Trend Analysis of Fire Frequency in Natural Resources Relative to Vegetation Canopy Cover using MODIS Data Products (Case Study: Lorestan Province). jgs. 24(75), 480-492. doi:10.61186/jgs.24.75.23
URL: http://jgs.khu.ac.ir/article-1-4196-en.html
URL: http://jgs.khu.ac.ir/article-1-4196-en.html
1- PhD student in climatology, Department of Geography, Najafabad Branch, Islamic Azad University, Najafabad, Iran., Islamic Azad University
2- Associate Professor, Department of Geography, Najafabad Branch, Islamic Azad University, Najafabad, Iran., Islamic Azad University ,aagandomkar@gmail.com
3- Assistant Professor, Department of Geography, Najafabad Branch, Islamic Azad University, Najafabad, Iran., Islamic Azad University
2- Associate Professor, Department of Geography, Najafabad Branch, Islamic Azad University, Najafabad, Iran., Islamic Azad University ,
3- Assistant Professor, Department of Geography, Najafabad Branch, Islamic Azad University, Najafabad, Iran., Islamic Azad University
Abstract: (3094 Views)
The main goal of this research is to analyze the time series trend of fire events in natural areas and reveal the relationship between these fire events and vegetation levels in Lorestan province. In this regard, the data of the fire product of the Madis sensor (MOD14A1) and the vegetation product (MOD13A3) of the Madis sensor were used during the statistical period of 2000-2020. The monthly and annual spatial distribution of fires in Lorestan province was investigated. Cross-information matrix analysis and spatial correlation matrix were used to reveal the relationship between fire occurrences and vegetation. The results showed that more than 70% of the total frequency of fire occurrences in natural resources fields (fires with code 2) in Lorestan province is related to June and then July. In terms of the long-term trend, the 21-year trend of the frequency of fire incidents in the province showed that the frequency of incidents in the natural resources areas of the province has generally increased with an annual slope of 3 incidents. The results of the correlation analysis between the monthly vegetation cover and the annual frequency of fire occurrences showed that the fire occurrences in the province showed a significant correlation with the vegetation cover changes in 4 months of the growing period, i.e. from May to August. Cross-matrix analysis between the spatial distribution of fire occurrence foci and NDVI index, both of which were products of MODIS measurement, indicated that, in general, the highest frequency of fire occurrences in Lorestan province in the period from May to August corresponds to Greenness range was 0.15 to 0.22. This range of vegetation generally corresponded to rainfed lands, weak pastures and low-density forest patches
Type of Study: Research |
Subject:
climatology
References
1. اسکندری، سعیده؛ اوالدی قادیکالیی، جعفر؛ جلیلوند، حمید و سراجیان، محمدرضا (1396). مدل‌سازی و پیش‌بینی خطر آتش‌سوزی در جنگل‌های بخش سه نکا - ظالم رود با استفاده از سامانه اطلاعات جغرافیایی. فصلنامه علمی - پژوهشی تحقیقات جنگل و صنوبر ایران، 21، 230-217.
2. اسکندری؛ سعیده (1394). آتش‌سوزی جنگل؛ تغییر اقلیم؛ تعداد آتش‌سوزی؛ وسعت آتش‌سوزی؛ جنگل‌های گلستان. دو فصلنامه علمی پژوهشی تحقیقات حمایت و حفاظت جنگل‌ها و مراتع ایران، 13(1)، 10-1.
3. آقازاده، فیروز (1399). به شناسایی بلادرنگ آتش‌سوزی جنگل و مراتع با استفاده از داده‌های NOAA/AVHRR منطقه موردمطالعه: پناهگاه حیات‌وحش پیامک ی. نشریه تحلیل فضایی مخاطرات محیطی، 7(1)، 1-14.
4. جانبار قبادی؛ غلامرضا (1398). بررسی مناطق خطر آتش‌سوزی جنگل در استان گلستان، بر اساس شاخص خطر آتش‌سوزی با بهره‌گیری از تکنیک GIS. نشریه تحلیل فضایی مخاطرات محیطی، 6(3). 89-102.
5. زرعکار، آزاده؛ کاظمی زمانی، بهاره؛ قربانی، ساره؛ عاشق معال، مریم و جعفری، حمیدرضا (1392). تهیه نقشه پراکندگی فضایی خطر آتش‌سوزی جنگل با استفاده از روش تصمیم‌گیری چندمعیاره و سامانه اطلاعات جغرافیایی (مطالعه موردی: سه حوزه جنگلی در استان گیلان). فصلنامه تحقیقات جنگل و صنوبر ایران، 21(2)، 218 -230.
6. مولودی، گلاله؛ خورانی، اسداله و مرادی، عباس (1395). اثر تغییر اقلیم بر امواج گرمایی سواحل شمالی خلیج‌فارس. مجله تحلیل فضایی مخاطرات محیطی، 3(1)، 1-14.
7. Aghazadeh, F. (2019). Real-time identification of forest and pasture fires using NOAA/AVHRR data. Journal of Spatial Analysis of Environmental Hazards, 7(1), 1-14. (In Persian)
8. Beltrami, H. & R. N, Harris. (2001). Inference of climate change from geothermal data, Global Planet. Change, 29, 148-352. [DOI:10.1016/S0921-8181(01)00085-6]
9. Chen, F. Niu, Sh. Tong, X. Zhao, J. Sun, Y. & He, T. (2014). The impact of precipitation regimes on forest fires in Yunnan Province, Southwest China. The Scientific World Journal, 1-9. [DOI:10.1155/2014/326782]
10. Eskandari, S. & Chuvieco, E. (2015). Fire danger assessment in Iran based on geospatial information. International Journal of Applied Earth Observation and Geoinformation, 42, 57-64. [DOI:10.1016/j.jag.2015.05.006]
11. Eskandari, S. (2014). forest fire; climate change; number of fires; extent of fire; The forests of Golestan. Bi-Quarterly Journal of Scientific Research on the Support and Protection of Iran's Forests and Rangelands, 13(1), 1-10. (In Persian)
12. 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)
13. Eskandari, S. Oaldi Qadikalii, J. Jalilund, H. & Sarajian, M. R. (2016). Modeling and forecasting the risk of fire in the forests of Se Neka-Zalemroud sector using geographic information system. Iranian Forest and Spruce Research Quarterly, 21, 230-217. (In Persian)
14. Hong, H. Naghibi, S. A. Moradi Dashtpagerdi, M. Pourghasemi, H. R. & Chen, W. (2017). A comparative nassessment between linear and quadratic discriminant analyses (LDA-QDA) with frequency ratio and weights-of-evidence models for forest fire susceptibility mapping in China. Arabian Journal of Geosciences, 10, 1-14. [DOI:10.1007/s12517-017-2905-4]
15. Janbaz Qobadi; Gh. (2018). Investigation of forest fire risk areas in Golestan province, based on fire risk index using GIS technique. Journal of Spatial Analysis of Environmental Hazards, 6(3). 89-102. (In Persian) [DOI:10.29252/jsaeh.6.3.89]
16. Kassomenos, Pavlos. (2010). Synoptic circulation control on wild fire occurrence, Physics and Chemistry of the Earth, 35. [DOI:10.1016/j.pce.2009.11.008]
17. Leblon, B. García, PAF. Oldford, S. Maclean, DA. & Flannigan, M. (2007). Using cumulative NOAA-AVHRR spectral indices for estimating fire danger codes in northern boreal forests. International journal of applied earth observation and Geoinformation, 9(3), 335-342. [DOI:10.1016/j.jag.2006.11.001]
18. Maeda, E. E. Formaggio, R. A. Shimabukuro, Y. E. Shimabukuro, Y. E. Arcoverde, G. F. B. & Hansen, M. C. (2009). Predicting forest fire in the Brazilian Amazon using MODIS imagery and artificial neural networks. International Journal of Applied Earth Observation and Geoinformation,11, 265-272. [DOI:10.1016/j.jag.2009.03.003]
19. Mulodi, G. Khorani, E. & Moradi, A. (2015). The effect of climate change on heat waves on the northern coasts of the Persian Gulf. Journal of Spatial Analysis of Environmental Hazards, 3(1), 1-14. (In Persian) [DOI:10.18869/acadpub.jsaeh.3.1.1]
20. Na, L. Zhang, J. Bao, Y. Bao, Y. Na, R. Tong, S. & Si, A. (2018). Himawari-8 Satellite Based Dynamic Monitoring of Grassland Fire in China-Mongolia Border Regions. Sensors, 18(1), 276. [DOI:10.3390/s18010276] [PMID] []
21. Pereira, Mário G. Trigo, R. M. da Camara, C. Pereira, J. M.C. & Leite, S. M. (2005). Synoptic patterns associated with large summer forest fires in Portugal, Agricultural and Forest Meteorology, 129, 1-2. [DOI:10.1016/j.agrformet.2004.12.007]
22. Pourtaghi, ZS. Pourghasemi, HR. & Rossi, M. (2015). Forest fire susceptibility mapping in the Minudasht forests, Golestan province, Iran. Environmental Earth Sciences, 73(4), 1515-1533. [DOI:10.1007/s12665-014-3502-4]
23. Sarkargar Ardakani, A. (2007). Analysis of radiometric- spatial characteristics of fire and its Application in identification and separation by remote sensing data. PhD thesis, Faculty of Engineering, Khaje- Nasir- Toosi University, 290.
24. Yin, H. Kong, FH. & Li, XZ. (2004). RS and GIS based forest fire zone mapping in Dahinggan Mountains. Chinese Geographical Science, 14 (3), 251- 25. [DOI:10.1007/s11769-003-0055-y]
25. Zarekar, A. Kazemi Zamani, B. Qurbani, S. Asheq Maal, M & Jafari, H. (2012). Preparation of forest fire risk spatial distribution map using multi-criteria decision making method and geographic information system (case study: three forest areas in Gilan province). Iranian Forest and Spruce Research Quarterly, 21(2), 218-230. (In Persian)
26. Zumbrunnen, T. Pezzattic, G. B. Menéndezd, P. Bugmann, H. Bürgia, M. & Conederac, M. (2011). Weather and human impacts on forest fires: 100 years of fire history in two climatic regions of Switzerland. Forest Ecology and Management, 261, 2188-2199. [DOI:10.1016/j.foreco.2010.10.009]
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
This work is licensed under a Creative Commons — Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)