IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i9p5494-d807906.html
   My bibliography  Save this article

Deep Learning-Based Projection of Occurrence Frequency of Forest Fires under SSP Scenario: Exploring the Link between Drought Characteristics and Forest Fires

Author

Listed:
  • Jang Hyun Sung

    (Ministry of Environment, Han River Flood Control Office, Seoul 06501, Korea)

  • Seung Beom Seo

    (International School of Urban Sciences, University of Seoul, Seoul 02504, Korea)

  • Young Ryu

    (Operational Systems Development Department, National Institute of Meteorological Research, Seogwipo-si 63568, Korea)

Abstract

The occurrence frequency of forest fires (OF) can be estimated using drought features because droughts are affected by climatic conditions. Previous studies have improved OF estimation performance by applying the meteorological drought index to climatic conditions. It is anticipated that the temperature will rise in South Korea in the future and that drought will become severe on account of climate change. The future OF is expected to change accordingly. This study used the standard precipitation index, relative humidity, and wind speed as predictor variables for a deep-learning-based model to estimate the OF. Climate change scenarios under shared socioeconomic pathways were used to estimate future OF. As a result, it was projected that the OF in the summer season will increase in the future (2071–2100). In particular, there will be a 15% increase in July compared to the current climate. A decrease in relative humidity and increase in wind speed will also affect the OF. Finally, drought severity was found to be the most influential factor on the OF among the four drought characteristics (severity, duration, intensity, and inter-arrival), considering inter-model variability across all global climate models.

Suggested Citation

  • Jang Hyun Sung & Seung Beom Seo & Young Ryu, 2022. "Deep Learning-Based Projection of Occurrence Frequency of Forest Fires under SSP Scenario: Exploring the Link between Drought Characteristics and Forest Fires," Sustainability, MDPI, vol. 14(9), pages 1-17, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5494-:d:807906
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/9/5494/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/9/5494/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jin Hyuck Kim & Jang Hyun Sung & Eun-Sung Chung & Sang Ug Kim & Minwoo Son & Mohammed Sanusi Shiru, 2021. "Comparison of Projection in Meteorological and Hydrological Droughts in the Cheongmicheon Watershed for RCP4.5 and SSP2-4.5," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    2. Shuqi Ma & Qianyi Liu & Yudong Zhang, 2021. "A prediction method of fire frequency: Based on the optimization of SARIMA model," PLOS ONE, Public Library of Science, vol. 16(8), pages 1-13, August.
    3. Jang Hyun Sung & Eun-Sung Chung & Shamsuddin Shahid, 2018. "Reliability–Resiliency–Vulnerability Approach for Drought Analysis in South Korea Using 28 GCMs," Sustainability, MDPI, vol. 10(9), pages 1-16, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohammad Ahsan Uddin & ASM Maksud Kamal & Shamsuddin Shahid & Eun-Sung Chung, 2020. "Volatility in Rainfall and Predictability of Droughts in Northwest Bangladesh," Sustainability, MDPI, vol. 12(23), pages 1-20, November.
    2. Mohamed Salem Nashwan & Shamsuddin Shahid & Eun-Sung Chung, 2020. "High-Resolution Climate Projections for a Densely Populated Mediterranean Region," Sustainability, MDPI, vol. 12(9), pages 1-22, May.
    3. Jang Hyun Sung & Minsung Kwon & Jong-June Jeon & Seung Beom Seo, 2019. "A Projection of Extreme Precipitation Based on a Selection of CMIP5 GCMs over North Korea," Sustainability, MDPI, vol. 11(7), pages 1-17, April.
    4. Mohammed Sanusi Shiru & Shamsuddin Shahid & Inhwan Park, 2021. "Projection of Water Availability and Sustainability in Nigeria Due to Climate Change," Sustainability, MDPI, vol. 13(11), pages 1-16, June.
    5. Mahiuddin Alamgir & Morteza Mohsenipour & Rajab Homsi & Xiaojun Wang & Shamsuddin Shahid & Mohammed Sanusi Shiru & Nor Eliza Alias & Ali Yuzir, 2019. "Parametric Assessment of Seasonal Drought Risk to Crop Production in Bangladesh," Sustainability, MDPI, vol. 11(5), pages 1-17, March.
    6. Zhenya Li & Zulfiqar Ali & Tong Cui & Sadia Qamar & Muhammad Ismail & Amna Nazeer & Muhammad Faisal, 2022. "A comparative analysis of pre- and post-industrial spatiotemporal drought trends and patterns of Tibet Plateau using Sen slope estimator and steady-state probabilities of Markov Chain," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 113(1), pages 547-576, August.
    7. Jin Hyuck Kim & Jang Hyun Sung & Eun-Sung Chung & Sang Ug Kim & Minwoo Son & Mohammed Sanusi Shiru, 2021. "Comparison of Projection in Meteorological and Hydrological Droughts in the Cheongmicheon Watershed for RCP4.5 and SSP2-4.5," Sustainability, MDPI, vol. 13(4), pages 1-22, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5494-:d:807906. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.