Assessment of Forest Fire Vulnerability Prediction in Indonesia: Seasonal Variability Analysis Using Machine Learning Techniques

Author:

Karurung Wulan Salle,Lee Kangjae,Lee Wonhee

Publisher

Elsevier BV

Reference49 articles.

1. Assessing Sumatran Peat Vulnerability to Fire under Various Condition of ENSO Phases Using Machine Learning Approaches;L B Prasetyo;Forests,2022

2. Peatland Data Fusion for Forest Fire Susceptibility Prediction Using Machine Learning;N Hidayanto;2021 4th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2021,2021

3. Analysis of Forest and Land Fire with Hotspot Modis on Various Types of Land Cover in Central Kalimantan Province;I Afitah;AgBioForum,2021

4. A spatial model of forest and land fire vulnerability level in the Dairi district;A S Thoha;Biodiversitas,2021

5. GIS-based forest fire susceptibility assessment by random forest, artificial neural network and logistic regression methods;R Eslami;Journal of Tropical Forest Science,2021

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