Investigating the trend of wildfires and its relationship with climate variables using satellite data (case study: Mazandaran province)

Bahrami-Pichaghchi, Hadigheh; Norooz-Valashedi, Reza; Gholami Sefidkouhi, Mohammad Ali

doi:10.22111/jneh.2023.45573.1967

Investigating the trend of wildfires and its relationship with climate variables using satellite data (case study: Mazandaran province)

Document Type : Research Article

Authors

¹ PhD Student of Agrometeorology, Water Engineering Department, Sari Agricultural Sciences and Natural Resources University, Sari, Iran

² Assistant Professor of Agrometeorology, Water Engineering Department, Sari Agricultural Sciences and Natural Resources University, Sari,, Iran

³ Associate Professor of Irrigation, Water Engineering Department, Sari Agricultural Sciences and Natural Resources University, Sari, Iran

10.22111/jneh.2023.45573.1967

Abstract

Wildfires are one of the critical environmental issues that cause financial and human losses. This harmful phenomenon endangers the lives of humans and creatures and is one of the factors of global warming. Its quick detection is a key element in controlling such a phenomenon. Therefore, this research aims to investigate the trend of active vegetation fire spots and its relationship with climatic variables using satellite data in Mazandaran province. So, while checking the efficiency of remote sensing data, practical measures can be taken to control and monitor this destructive phenomenon in a precise location and time. Therefore, in this research, meteorological data with daily scale, Brightness temperature 31 (BRIGHT_T31), and Fire Radiative Power (FRP) of MODIS sensors were used in the period from 2001 to 2022. The results showed that the most occurrences of vegetation fires were in the east of Mazandaran in the altitude classes of 0-500 meters and the lowest frequency was related to the altitude classes of 2500-5600 meters. Most of the vegetation fire incidents occurred in the hot and dry months of the year in the eastern strip of Mazandaran. The Petit homogeneity test was used to check the change point of fire. The results of the Petit homogeneity test presented the trend change point in an upward direction in July 2011 for the BRIGHT_T31 profile at the 95% confidence level. Spearman's non-parametric test was used to investigate the correlation between climatic parameters and the number of fires. Correlation results showed a significant relationship between climate parameters with a daily scale (Temperature, Precipitation, Relative Humidity, Sunshine Hours) and FRP and BRIGHT_T31 profiles at the 90% confidence level. So, temperature has been the most effective meteorological component of forest fires. As a result, fire events are strongly related to weather conditions.

Keywords

Main Subjects

Environmental Hazards

References

References (in Persian)

Aazami, J., & Pourhashemzehi, S. (2018). The Effect of Arson in Agriculture on the Environment (Case study: Esfahan Province). Human & Environment, 16(3), 113-124. [In Persian]

Abbaszadeh Tehrani, N., Morovati, A., Khanbani, S., & Janalipour, M. (2021). Evaluating Performance of Support Vector Machine and Random Forest Classifiers in Monitoring Wildfire from pre-and post-event Landsat8 Satellite Images. Environmental Management Hazards, 8(2), 117-133. [In Persian]

Abedini, M., Shishegaran, M., & Ghale, E. (2022). Monitoring and Estimating the Fire-Affected Areas of the Zagros Mountains Using Landsat Satellite Images. Geography and Environmental Planning, 33(4), 49-62. [In Persian]

Ahmadi, M., Shojaeizadeh, K., & Dadashi-Roudbari, A. (2022). Investigating the relationship between vegetation indices and the occurrence of wildfire in the vegetation areas of Iran. Journal of Geography and Environmental Hazards. 10.22067/GEOEH.2022.78468.1276. [in Persian]

Aleemahmoodi Sarab, S., Feghhi, J., Jabbarian Amiri, B., Danehkar, A., & Attarod, P. (2013). Applying the regression models to assess the influences of climate factors on forest fires (case study: Izeh). Journal of Natural Environment, 66(2), 191-201. [in Persian]

Azizi, M., Khosravi, M., & Pourreza, M. (2020). Frequency of fire incidence concerning Zagros forests and rangelands physiography (Kermanshah province) using MODIS active fire data. Iranian Journal of Forest and Range Protection Research, 18(1). https://doi.org/10.22092/ijfrpr.2020.342093.1421. [in Persian]

Bahrami Pichaghchi, H., Raeini-Sarjaz, M., & Norooz Valashedi, R. (2020). Investigation of the effect of global warming on temporal and spatial changes of snow cover and its durability in the northern slope of Central Alborz. Journal of Agricultural Meteorology, 8(1), 15-25. [in Persian]

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). [In Persian]

Eskandari, S., & Eskandari, S. (2021). Fire of Iranian forests, consequences, opposition methods, and solutions. Human & Environment, 19(1), 175-187. [In Persian]

Eskandari, S., & Jalilvand, H. (2017). Effect of weather changes on fire regime of Neka and Behshahr forests. Iranian Journal of Forest and Range Protection Research, 15(1), 30-39. [In Persian]

Ghanbari Motlagh, M., & Amraei, B. (2020). Detecting the Spatiotemporal Relationship of Vegetation Changes with Climatic Elements in Mazandaran Province. Geography and Environmental Sustainability, 10(2), 37-55. [In Persian]

Khalatbari Limaki, M., Es-hagh-Nimvari, M., Alavi, S. J., Mataji, A., & Kazemnezhadad, F. (2023). Elevational shift of Carpinus betulus L. under the future climate change in northern Iran. Journal of Renewable Natural Resources Research, 13(2), 71-85. [In Persian]

Kouhani, M., Kiani, A., & Ebrahimian Ghajari, Y. (2023). Using satellite images for long-term analysis of vegetation changes and detection of vegetation anomalies with the help of meteorological data. Scientific-Research Quarterly of Geographical Data (SEPEHR). https://doi.org/10.22131/sepehr.2023.1982943.2932. [In Persian]

Pourshakouri, F., Darvishsefat, A. A., Samadzadegan, F., Attarod, P. A., & Selyari, J. S. (2014). Assessment of active fire detection algorithm for fire detection in natural resources using MODIS images (case study: Golestan National Park). Journal of Wood and Forest Science and Technology, 20(4), 81-97. [In Persian]

Sharifnejad, T., Nehzak, H. K., & Varamesh, S. (2022). Assessing the capability of Modis fire detector products in identifying fires in Golestan State. Journal of Natural Environmental Hazards, 10(30), 1-1. [In Persian]

Sheikhi, M. Kabuli, S. Rahimi, M. Yazdani, M. Moafi, M. (2012). Investigating the risk of forest fire using indicators based on climatic parameters (case study: Mazandaran province, Parsa, Master's degree, Department of Desertification, Faculty of Desertology, Semnan University. [In Persian]

Shojaeizadeh, K., Ahmadi, M., & Dadashi-Roudbari, A. (2022). Spatiotemporal changes of forest fire in vegetation areas of Iran based on MODIS sensor. Journal of Natural Environmental Hazards, 36(12), 1-1. [In Persian]

References (in English)

Al-Kahlout, M. M., Ghaly, A. M. A., Mudawah, D. Z., & Abu-Naser, S. S. (2020). Neural network approach to predict forest fires using meteorological data. International Journal of Academic Engineering Research (IJAER), 4(9).

Arnell, N., Freeman, A., & Gazzard, R. (2021). The effect of climate change on indicators of fire danger in the UK. Environmental Research Letters, 16(4), 044027.

De Angelis, A., Ricotta, C., Conedera, M., & Pezzatti, G. B. (2015). Modeling the meteorological forest fire niche in heterogeneous hydrologic conditions. PloS one, 10(2), e0116875.

Engel, C. B., Jones, S. D., & Reinke, K. J. (2022). Fire Radiative Power (FRP) Values for Biogeographical Region and Individual Geostationary HHMMSS Threshold (BRIGHT) Hotspots Derived from the Advanced Himawari Imager (AHI). Remote Sensing, 14(11), 2540.

Fu, Y., Li, R., Wang, X., Bergeron, Y., Valeria, O., Chavardès, R. D., Wang, Y., & Hu, J. (2020). Fire detection and fire radiative power in forests and low-biomass lands in Northeast Asia: MODIS versus VIIRS Fire Products. Remote Sensing, 12(18), 2870.

Giglio, L., Schroeder, W., Hall, J., & Justice, C. MODIS Collection 6 Active Fire Product User’s Guide Revision B. 2018. In: NASA.

Kumari, B., & Pandey, A. C. (2020). MODIS-based forest fire hotspot analysis and its relationship with climatic variables. Spatial Information Research, 28(1), 87-99.

Labib, S., & Harris, A. (2018). The potentials of Sentinel-2 and LandSat-8 data in green infrastructure extraction, using object-based image analysis (OBIA) method. European Journal of Remote Sensing, 51(1), 231-240.

Lafon, C. W., & Grissino-Mayer, H. D. (2007). Spatial patterns of fire occurrence in the central Appalachian Mountains and implications for wildland fire management. Physical Geography, 28(1), 1-20.

Li, F., Zhang, X., & Kondragunta, S. (2020). Biomass burning in Africa: An investigation of fire radiative power missed by MODIS using the 375 m VIIRS active fire product. Remote Sensing, 12(10), 1561.

Masinda, M. M., Li, F., Qi, L., Sun, L., & Hu, T. (2022). Forest fire risk estimation in a typical temperate forest in Northeastern China using the Canadian forest fire weather index: a case study in autumn 2019 and 2020. Natural hazards, 111(1), 1085-1101.

Partal, T., & Kahya, E. (2006). Trend analysis in Turkish precipitation data. Hydrological Processes: An International Journal, 20(9), 2011-2026.

Pettitt, A. N. (1979). A non‐parametric approach to the change‐point problem. Journal of the Royal Statistical Society: Series C (Applied Statistics), 28(2), 126-135.

Wooster, M. J., Roberts, G., Perry, G., & Kaufman, Y. (2005). Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release. Journal of Geophysical Research: Atmospheres, 110(D24).

Zare Chahouki, M. (2010). Data analysis in natural resources research using SPSS software. Academic, Tehran.

Zeng, A.-C., Cai, Q.-J., Su, Z.-w., Guo, X.-B., Jin, Q.-F., & Guo, F.-T. (2020). Seasonal variation and driving factors of forest fire in Zhejiang Province, China, based on MODIS satellite hot spots. Ying Yong Sheng tai xue bao= The Journal of Applied Ecology, 31(2), 399-406.