Assessing Wildfire Risk in South Korea Under Climate Change Using the Maximum Entropy Model and Shared Socioeconomic Pathway Scenarios
For effective management and prevention, wildfire risk prediction needs to consider the substantial impacts of climate change on wildfire patterns. This study analyzed the probability of wildfire occurrence in South Korea using the Maximum Entropy (MaxEnt) model and predicted future wildfire occurre...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Atmosphere |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4433/16/1/5 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832589156207820800 |
|---|---|
| author | Jukyeong Choi Heemun Chae |
| author_facet | Jukyeong Choi Heemun Chae |
| author_sort | Jukyeong Choi |
| collection | DOAJ |
| description | For effective management and prevention, wildfire risk prediction needs to consider the substantial impacts of climate change on wildfire patterns. This study analyzed the probability of wildfire occurrence in South Korea using the Maximum Entropy (MaxEnt) model and predicted future wildfire occurrence under shared socioeconomic pathway (SSP) climate change scenarios. The model utilized historical fire occurrence data and was trained using 12 environmental variables encompassing climate, topography, vegetation, and socioeconomic factors. Future wildfire risk was predicted under the SSP2-4.5 and SSP5-8.5 scenarios for 2041–2060 and 2081–2100. Increased average temperature and solar radiation were key drivers of elevated wildfire risk, whereas increased precipitation and relative humidity reduced this risk. Under current conditions, 367,027 ha (6.52%) within the study area were classified as high-risk based on the MaxEnt model output (<i>p</i> > 0.6). Under both SSP scenarios, a decline in the at-risk area was observed over time. This study provides fundamental data for wildfire management and prevention strategies in South Korea and provides quantitative evidence on the potential impact of climate-related environmental changes on wildfires. |
| format | Article |
| id | doaj-art-f756c9541f114df68213bfa02e7babcb |
| institution | Kabale University |
| issn | 2073-4433 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj-art-f756c9541f114df68213bfa02e7babcb2025-01-24T13:21:40ZengMDPI AGAtmosphere2073-44332024-12-01161510.3390/atmos16010005Assessing Wildfire Risk in South Korea Under Climate Change Using the Maximum Entropy Model and Shared Socioeconomic Pathway ScenariosJukyeong Choi0Heemun Chae1Department of Forestry and Environmental Systems, Kangwon National University, Chuncheon 24341, Republic of KoreaDivision of Forest Science, Kangwon National University, Chuncheon 24341, Republic of KoreaFor effective management and prevention, wildfire risk prediction needs to consider the substantial impacts of climate change on wildfire patterns. This study analyzed the probability of wildfire occurrence in South Korea using the Maximum Entropy (MaxEnt) model and predicted future wildfire occurrence under shared socioeconomic pathway (SSP) climate change scenarios. The model utilized historical fire occurrence data and was trained using 12 environmental variables encompassing climate, topography, vegetation, and socioeconomic factors. Future wildfire risk was predicted under the SSP2-4.5 and SSP5-8.5 scenarios for 2041–2060 and 2081–2100. Increased average temperature and solar radiation were key drivers of elevated wildfire risk, whereas increased precipitation and relative humidity reduced this risk. Under current conditions, 367,027 ha (6.52%) within the study area were classified as high-risk based on the MaxEnt model output (<i>p</i> > 0.6). Under both SSP scenarios, a decline in the at-risk area was observed over time. This study provides fundamental data for wildfire management and prevention strategies in South Korea and provides quantitative evidence on the potential impact of climate-related environmental changes on wildfires.https://www.mdpi.com/2073-4433/16/1/5climate changewildfireMaxEntSSP scenariowildfire risk prediction |
| spellingShingle | Jukyeong Choi Heemun Chae Assessing Wildfire Risk in South Korea Under Climate Change Using the Maximum Entropy Model and Shared Socioeconomic Pathway Scenarios Atmosphere climate change wildfire MaxEnt SSP scenario wildfire risk prediction |
| title | Assessing Wildfire Risk in South Korea Under Climate Change Using the Maximum Entropy Model and Shared Socioeconomic Pathway Scenarios |
| title_full | Assessing Wildfire Risk in South Korea Under Climate Change Using the Maximum Entropy Model and Shared Socioeconomic Pathway Scenarios |
| title_fullStr | Assessing Wildfire Risk in South Korea Under Climate Change Using the Maximum Entropy Model and Shared Socioeconomic Pathway Scenarios |
| title_full_unstemmed | Assessing Wildfire Risk in South Korea Under Climate Change Using the Maximum Entropy Model and Shared Socioeconomic Pathway Scenarios |
| title_short | Assessing Wildfire Risk in South Korea Under Climate Change Using the Maximum Entropy Model and Shared Socioeconomic Pathway Scenarios |
| title_sort | assessing wildfire risk in south korea under climate change using the maximum entropy model and shared socioeconomic pathway scenarios |
| topic | climate change wildfire MaxEnt SSP scenario wildfire risk prediction |
| url | https://www.mdpi.com/2073-4433/16/1/5 |
| work_keys_str_mv | AT jukyeongchoi assessingwildfireriskinsouthkoreaunderclimatechangeusingthemaximumentropymodelandsharedsocioeconomicpathwayscenarios AT heemunchae assessingwildfireriskinsouthkoreaunderclimatechangeusingthemaximumentropymodelandsharedsocioeconomicpathwayscenarios |