Modelling and analysis impact of El Nino and IOD to land and forest fire using polynomial and generalized logistic function: cases study in South Sumatra and Kalimantan, Indonesia

Nurdiati, Sri; Sopaheluwakan, Ardhasena; Julianto, Mochamad Tito; Septiawan, Pandu; Rohimahastuti, Fadillah

doi:10.1007/s40808-021-01303-4

Cited by 7 publications

(3 citation statements)

References 58 publications

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“…This result is in line with previous research [28] and relates to the location of the IOD, which is closer to southern Sumatra than Kalimantan. The proportion of quantitative representation between the ENSO and IOD impact is more balanced in South Sumatra [81]. Meanwhile, it is dominated by the ENSO in Kalimantan.…”

Section: Discussionmentioning

confidence: 95%

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Joint Pattern Analysis of Forest Fire and Drought Indicators in Southeast Asia Associated with ENSO and IOD

2022

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Land and forest fires in Southeast Asia often coincide with severe dry seasons in the specific region caused by the warm phase of an El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). This research aims to identify and quantify the ENSO–IOD effect on a joint pattern between the dry season and land and forest fires in Southeast Asia. This research provides a quantitative result which represents the ENSO–IOD’s impact in Southeast Asia for hotspots, dry spells, and precipitation anomalies. The methods used in this research are singular value decomposition, probability density skill score, and coherence analysis. Cambodia, Myanmar, and Thailand gave a similar result with less than a 25% increasing severity in the hotspots from normal to either El Niño, positive IOD, or El Niño–positive IOD years. The maximum increase in hotspot severity in North Sumatra was 13.06% and happened during a weak El Niño and positive IOD. Meanwhile, South Sumatra had a maximum accumulation of more than 89% and Kalimantan had more than a 72% increase during the strong El Niño in 2015. Even though the relationship between the ENSO and IOD was inconsistent, the occurrence of both phenomena in the same year can lead to fires and need to be considered.

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Section: Discussionmentioning

confidence: 95%

“…Not only the severity of the dry season, but the number of hotspots that occur in the southern part of Sumatra and Kalimantan are also affected by the strength of El Niño and positive IOD [80,81]. However, the impact of positive IOD in Kalimantan is not as high as in southern Sumatra.…”

Section: Discussionmentioning

confidence: 99%

Joint Pattern Analysis of Forest Fire and Drought Indicators in Southeast Asia Associated with ENSO and IOD

2022

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“…Not only El Nino event, but positive IOD (Indian Ocean Dipole) index also gives a higher potential for forest fires [7]. Study from [8] estimated the possibility of extreme fires in Sumatra during the positive IOD and in Borneo during the El Nino period. Moreover, low rainfall and relative humidity as well as high air temperature and strong wind speed make the severity of forest fires increase [9].…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Machine Learning-based Forest Fire Characteristics in Sumatra and Borneo

Shabrina

Wahyuni

Latifah

2023

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Sumatra and Borneo are areas consisting of rainforests with a high vulnerability to fire. Both areas are in the tropics which experience rainy and dry seasons annually. The long dry season such as in 2019 triggered forest and land fires in Borneo and Sumatra, causing haze disasters in the exposed areas. This indicates that climate variables play a role in burning forests and land in Borneo and Sumatra, but how climate affects the fires in both areas is still questionable. This study investigates the climate variables: temperature, humidity, precipitation, and wind speed in relation to the fire’s characteristics in Borneo and Sumatra. We use the Random Forest model to determine the characteristics of forest fires in Sumatra and Borneo based on the climate variables and carbon emission levels. According to the model, the fire event in Sumatra is slightly better predicted than in Borneo, indicating a climate-fire dependence is more prominent in Sumatra. Nevertheless, a maximum temperature variable is seemingly an important indicator for forest and land fire in both domains as it gives the largest contribution to the carbon emission.

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Prediction and driving factors of forest fire occurrence in Jilin Province, China

Gao,

Shan,

Liu

et al. 2023

J. For. Res.

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Modelling and analysis impact of El Nino and IOD to land and forest fire using polynomial and generalized logistic function: cases study in South Sumatra and Kalimantan, Indonesia

Cited by 7 publications

References 58 publications

Joint Pattern Analysis of Forest Fire and Drought Indicators in Southeast Asia Associated with ENSO and IOD

Joint Pattern Analysis of Forest Fire and Drought Indicators in Southeast Asia Associated with ENSO and IOD

Comparative Analysis of Machine Learning-based Forest Fire Characteristics in Sumatra and Borneo

Prediction and driving factors of forest fire occurrence in Jilin Province, China

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