Relationship Between Hotspot and Geography-Meteorology Factors in Thailand and Neighboring Countries

Main Article Content

Santi Pailoplee
Thanchanok Ngernted

Abstract

Air pollution is a critical issue in many countries and has become a significant problem in Southeast Asia. Wildfires, agricultural burning, and biomass burning are major sources of pollution emissions. This study aims to analyze hotspot activity and examine the relationship between hotspots and geographic-meteorological factors in Thailand and neighboring countries. MODIS hotspot data were analyzed using the frequency-magnitude distribution (FMD) and geography-meteorology factors. The results indicate that areas with high hotspot activity were mainly found in northeastern to eastern Cambodia and northern Laos. Additionally, northern Laos and some pockets in Myanmar showed high hotspot intensity, capable of generating a maximum Fire Radiative Power (FRP)
>1,000 MW. The return periods for 8, 20, 40, and 120 MW were found to be 0.05, 0.1, 0.5, and 1 year, respectively. In the next 50 years, parts of Thailand, Myanmar, and Cambodia will have a 0–60% probability of experiencing 120 MW fires. Fires are more frequent at low elevations, on gentle slopes, and across all aspects (excluding flat areas). Moreover, higher elevations, steeper slopes, and southern aspects tend to experience more high-intensity fires. It can be inferred that fire intensity is not primarily influenced by temperature, precipitation, or relative humidity. Instead, other factors, such as fuel availability and human activities, may play a more significant role.

Article Details

How to Cite
Pailoplee, S., & Ngernted , T. (2025). Relationship Between Hotspot and Geography-Meteorology Factors in Thailand and Neighboring Countries. Bulletin of Earth Sciences of Thailand, 17(1). retrieved from https://ph01.tci-thaijo.org/index.php/bestjournal/article/view/261540
Section
Research Articles

References

Adab, H., Kanniah, K. D., & Solaimani, K. (2013). Modeling forest fire risk in the northeast of Iran using remote sensing and GIS techniques. Natural hazards, 65, 1723-1743. https://doi.org/

1007/s11069-012-0450-8

Adaktylou, N., Stratoulias, D., Borgman, J., Cha, S., Adiningrat, D. P., & Nuthammachot, N. (2024). Land Cover Disaggregated Fire Occurrence and Particulate Matter 2.5 Relationship in the Mekong Region: A Comprehensive Study. ISPRS International Journal of Geo-Information, 13(6), 206. https://doi.org/10.3390/ijgi13060206

Baltacı, U., & Yıldırım, F. (2020). Effect of slope on the analysis of forest fire risk. Hacettepe Journal of Biology and Chemistry, 48(4), 373-379. https://doi.org/10.15671/

hjbc.753080

Berčák, R., Holuša, J., Trombik, J., Resnerová, K., & Hlásny, T. (2024). A combination of human activity and climate drives forest

fire occurrence in central europe: the case

of the Czech Republic. Fire, 7(4), 109. https://doi.org/10.3390/fire7040109

Chaiboonsri, C., Eakkapun, P., Sirimongkonlertkun, N., Suksaroj, T. T., Nasanit, R., Apiratikul, R., ... & Pongpiachan, S. (2023). The Impact of PM2.5 on Socio-Economic of Thailand: The Perception Based on The Survey Data. NIDA Development Journal, 63(2), 106-124. https://doi.org/10.14456/ndj.2023.5

Chavanaves, S., Fantke, P., Limpaseni, W., Attavanich, W., Panyametheekul, S., Gheewala, S. H., & Prapaspongsa, T. (2021). Health impacts and costs of fine particulate matter formation from road transport in Bangkok Metropolitan Region. Atmospheric Pollution Research, 12(10), 101191. https://doi.org/10.1016/j.apr.2021.101191

Chen, H., Burnett, R. T., Kwong, J. C., Villeneuve, P. J., Goldberg, M. S., Brook, R. D., ... & Copes, R. (2013). Risk of incident diabetes in relation to long-term exposure to fine particulate matter in Ontario, Canada. Environmental health perspectives, 121(7), 804-810. https://doi.org/10.1289/ehp.1205958

Chorhirankul, N. (2017). Frequency-size distribution of the craters on mars. Chulalongkorn University. https://doi.org/

58837/CHULA.SP.2017.36

Dorodnykh, N., Nikolaychuk, O., Pestova, J.,

& Yurin, A. (2022). Forest Fire Risk Forecasting with the Aid of Case-Based Reasoning. Applied Sciences, 12(17), 8761. https://doi.org/10.3390/app12178761

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. https://doi.org/10.3390/rs141

Ganteaume, A., Camia, A., Jappiot, M., San-Miguel-Ayanz, J., Long-Fournel, M., & Lampin, C. (2013). A review of the main driving factors of forest fire ignition over Europe. Environmental management, 51, 651-662. https://doi.org/10.1007/s00267-012-

-z

Gedalof, Z. E. (2010). Climate and spatial patterns of wildfire in North America. The landscape ecology of fire, 89-115. Dordrecht: Springer Netherlands. https://doi.org/10.1007/

-94-007-0301-8_4.

Gu, Y., Fang, T., & Yim, S. H. L. (2024). Source emission contributions to particulate matter and ozone, and their health impacts in Southeast Asia. Environment international, 186, 108578. https://doi.org/10.1016/j.envint.

108578

Gutenberg, B., & Richter, C. F. (1944). Frequency of earthquakes in California. Bulletin of the Seismological society of America, 34(4), 185-188. https://doi.org/

1785/BSSA0340040185

Iaaich, H., Moussadek, R., Baghdad, B., Mrabet, R., Douaik, A., Abdelkrim, D., & Bouabdli, A. (2016). Soil erodibility mapping using three approaches in the Tangiers province–Northern Morocco. International Soil and Water Conservation Research, 4(3), 159-167. https://doi.org/ 10.1016/j.iswcr.2016.07.001

Ishimoto, M. and Iida, K. (1939). Observations of Earthquakes Registered with the Micro Seismograph Constructed Recently. Bulletin of the Earthquake Research Institute, 17, 443-478.

Li, R., Zhou, R., & Zhang, J. (2018). Function of PM2.5 in the pathogenesis of lung cancer and chronic airway inflammatory diseases. Oncology letters, 15(5), 7506-7514. https://doi.org/10.3892/ol.2018.8355

Kadir, E. A., Kung, H. T., AlMansour, A. A., Irie, H., Rosa, S. L., & Fauzi, S. S. M. (2023). Wildfire hotspots forecasting and mapping for environmental monitoring based on the long short-term memory networks deep learning algorithm. Environments, 10(7), 124. https://doi.org/10.3390/environments10070124

Kaiser, J. W., Heil, A., Andreae, M. O., Benedetti, A., Chubarova, N., Jones, L., Morcrette, J.J., Razinger, M., Schultz, M.G., Suttie, M., & Van Der Werf, G. R. (2012). Biomass burning emissions estimated with

a global fire assimilation system based on observed fire radiative power. Biogeosciences, 9(1), 527-554. https://doi.org/10.5194/bg-9-527-2012

Khamsiri, S. (2017). Frequency-size distribution of the craters on moon. Chulalongkorn University. https://doi.org/10.58837/CHULA

.SP.2017.71

Korontzi, S., McCarty, J., Loboda, T., Kumar, S., & Justice, C. (2006). Global distribution of agricultural fires in croplands from 3 years of Moderate Resolution Imaging Spectroradiometer (MODIS) data. Global Biogeochemical Cycles, 20(2). https://doi.org/

1029/2005GB002529

Kumar, S., & Kumar, A. (2022). Hotspot and trend analysis of forest fires and its relation to climatic factors in the western Himalayas. Natural Hazards, 114(3), 3529-3544. https://doi.org/10.1007/s11069-022-05530-5

Miller, M. R., & Newby, D. E. (2020). Air pollution and cardiovascular disease: car sick. Cardiovascular research, 116(2), 279-294. https://doi.org/10.1093/cvr/cvz228

Moran, J., NaSuwan, C., & Poocharoen, O. O. (2019). The haze problem in Northern Thailand and policies to combat it: A review. Environmental Science & Policy, 97, 1-15. https://doi.org/10.1016/j.envsci.2019.03.016

Nami, M. H., Jaafari, A., Fallah, M., & Nabiuni, S. (2018). Spatial prediction of wildfire probability in the Hyrcanian ecoregion using evidential belief function model and GIS. International journal of environmental science and technology, 15, 373-384. https://doi.org/10.1007/s13762-017-1371-6

Nonthapot, S., Sihabutr, C., & Lean, H. H. (2024). The effects of air pollution on tourism in Thailand. Geo Journal of Tourism and Geosites, 53(2), 522-527. https://doi.org/

30892/gtg.53215-1227

Olabarrieta, M., Valle-Levinson, A., Martinez, C. J., Pattiaratchi, C., & Shi, L. (2017). Meteotsunamis in the northeastern Gulf of Mexico and their possible link to El Niño Southern Oscillation. Natural hazards, 88, 1325-1346. https://doi.org/10.1007/s11069-017-2922-3

Pacaldo, R. S., Aydin, M., & Amarille, R. K. (2025). Forest fire and aspects showed no significant effects on most mineral soil properties of black pine forests. CATENA, 250, 108801. https://doi.org/10.1016/j.catena

.2025.108801

Pailoplee, S. (2017). Probabilities of Earthquake Occurrences along the Sumatra-Andaman Subduction Zone. Open Geosciences, 9(1), 53-60. https://doi.org/10.1515/geo-2017-0004

Pope Iii, C. A., Burnett, R. T., Thun, M. J., Calle, E. E., Krewski, D., Ito, K., & Thurston, G. D. (2002). Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. Jama, 287(9), 1132-1141. https://doi.org/10.1001/jama.287.9.1132

Prasertwiriya, K. (2020). Investigation of rainfall amounts in Thailand: Spatial Distribution. Chulalongkorn University. https://doi.org/10.58837/CHULA.SP.2020.229

Rogers, B. M., Balch, J. K., Goetz, S. J., Lehmann, C. E., & Turetsky, M. (2020). Focus on changing fire regimes: interactions with climate, ecosystems, and society. Environmental Research Letters, 15(3), 030201. https://doi.org/10.1088/1748-9326/

ab6d3a

Sjöström, J., & Granström, A. (2023). Human activity and demographics drive the fire regime in a highly developed European boreal region. Fire Safety Journal, 136, 103743. https://doi.org/10.1016/j.firesaf.2023.

Taghizadeh-Hesary, F., & Taghizadeh-Hesary, F. (2020). The impacts of air pollution on health and economy in Southeast Asia. Energies, 13(7), 1812. https://doi.org/10.3390/en1307

Vadrevu, K. P., Csiszar, I., Ellicott, E., Giglio, L., Badarinath, K. V. S., Vermote, E., & Justice, C. (2012). Hotspot analysis of vegetation fires and intensity in the Indian region. IEEE Journal of selected topics in applied Earth Observations and Remote Sensing, 6(1), 224-238. https://doi.org/10.1109/

JSTARS.2012.2210699

Wiemer, S. (2001). A software package to analyze seismicity: ZMAP. Seismological Research Letters, 72(3), 373-382. https://doi.

org/10.1785/gssrl.72.3.373

Xing, Y. F., Xu, Y. H., Shi, M. H., & Lian, Y. X. (2016). The impact of PM2. 5 on the human respiratory system. Journal of thoracic disease, 8(1), E69. https://doi.org/10.3978/

j.issn.2072-1439.2016.01.19

Yadav, R., Tripathi, J., Shanker, D., Rastogi, B., Das, M., & Kumar, V. (2011). Probabilities for the occurrences of medium to large earthquakes in northeast India and adjoining region. Natural Hazards, 56, 145-167. https://doi.org/10.1007/s11069-010-9557-y

Yang, Y., Zhang, X., & Fu, Y. (2022). Foreign tourists’ experiences under air pollution: Evidence from big data. Tourism Management, 88, 104423. https://doi.org/

1016/j.tourman.2021.104423