Joint Spatio-Temporal Analysis of Various Wildfire and Drought Indicators in Indonesia

Nurdiati, Sri; Sopaheluwakan, Ardhasena; Septiawan, Pandu; Ardhana, Muhammad Reza

doi:10.3390/atmos13101591

Cited by 3 publications

(1 citation statement)

References 66 publications

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“…Based on rainfall patterns, the rainy season usually occurs in the period of October -April and is characterized by high rainfall. The dry season generally occurs in May -September and was characterized by low rainfall (Nurdiati et al, 2022).…”

Section: Study Areamentioning

confidence: 99%

Analysis of Carbon Dioxide Emission from Forest Fires based on Fire Radiative Power in Riau

Kusuma,

Rohmawati,

Risdiyanto

2023

Agromet

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Riau is one of the susceptible regions in Indonesia, which faces frequent land and forest fires. Fires occur in various land covers and soil types, both peat and mineral soils, which emitted huge carbon to the atmosphere. Forest fires emit greenhouse gases, including carbon dioxide (CO2). The objective of the research was to quantify CO2 from land and forest fires. The quantification emission was for 2016 – 2018 based on the fire radiant power (FRP) dataset along with the buffer methodology for assessing fire-affected land extents across different land covers. The FRP dataset we used to be only at a confidence level of 70% or higher, which represents hotspots. The results revealed large numbers of FRP focal points (> 1000) that can be identified as fires for 2016 and 2018, whereas only small numbers (121) were identified for 2017. Then we quantified the area burned of 95,396 Ha in Riau for 2016, which was double to the 2018’s area burned. Further, this burning contributed to CO2 emission equal to 313,456 tCO2 for 2016. Emission in 2017 was a relatively low as not many observed fires detected.

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Section: Study Areamentioning

confidence: 99%

Analysis of Carbon Dioxide Emission from Forest Fires based on Fire Radiative Power in Riau

Kusuma,

Rohmawati,

Risdiyanto

2023

Agromet

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Squirrels in the Tropics: A Specific Synthesis of their Fate, Stress, Declines, and Extinctions

Steiner

Huettmann

2023

Sustainable Squirrel Conservation

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Probabilistic Hotspot Prediction Model Based on Bayesian Inference Using Precipitation, Relative Dry Spells, ENSO and IOD

et al. 2023

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Increasing global warming can potentially increase the intensity of ENSO and IOD extreme phenomena in the future, which could increase the potential for wildfires. This study aims to develop a hotspot prediction model in the Kalimantan region using climate indicators such as precipitation and its derivatives, ENSO and IOD. The hotspot prediction model was developed using Principal Model Analysis (PMA) as the initial model basis. The overall model performance is evaluated using the concept of Cross-Validation. Furthermore, the model’s performance will be improved using the Bayesian Inference principle so that the average performance increases from 28.6% to 61.1% based on the model’s coefficient of determination (). The character of each year in the model development process is also evaluated using the concept of cross validation. Since the climate indicator we used was integrated with the ENSO and IOD index, model performance is strongly influenced by the ENSO and IOD phenomena. To obtain better performance when estimating future forest fires (related to El Niño and positive IOD), years with a high number of hotspots and coinciding with the occurrence of El Niño and IOD are better used as early model years (PMA). However, the model tends to overestimate the hotspot value, especially with a lower strength El Niño and positive IOD. Therefore, years with a low number of hotspots, as in normal years and La Niña, are better used in the model performance improvement stage (Bayesian Inference) to correct the overestimation.

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Joint Spatio-Temporal Analysis of Various Wildfire and Drought Indicators in Indonesia

Cited by 3 publications

References 66 publications

Analysis of Carbon Dioxide Emission from Forest Fires based on Fire Radiative Power in Riau

Analysis of Carbon Dioxide Emission from Forest Fires based on Fire Radiative Power in Riau

Squirrels in the Tropics: A Specific Synthesis of their Fate, Stress, Declines, and Extinctions

Probabilistic Hotspot Prediction Model Based on Bayesian Inference Using Precipitation, Relative Dry Spells, ENSO and IOD

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