Analysing causal factors of peatland wildfires: a knowledge-based approach

Ariesta Lestari, Grace Rumantir, Nigel Tapper, Bambang H. Saharjo, Aswin Usup, Laura Graham, Andrew P. Vayda, Nina Yulianti, Rony Teguh

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1 Citation (Scopus)


When dealing with environmental problems, complexity and uncertainty have become barriers to obtaining reliable information to facilitate good decision-making in fire prevention. This paper proposes and tests a workflow to build the structure of a causal model as a decision support system for fire prone peatlands. We extend the generic process of developing a causal model by incorporating knowledge gained from the literatures and from human experts. We outline the process of automatically generating the relevant variables through literature reviews and constructing a causal model using an online survey and discussions with domain experts. We demonstrate that the structure of the causal model developed can provide logical inferences on the spatial and temporal behaviours of these wildfires.

Original languageEnglish
Title of host publicationProceedings of PACIS2018
Subtitle of host publicationPacific Asia Conference on Information Systems (PACIS)
EditorsMotonari Tanabu, Dai Senoo
Place of PublicationAtlanta Georgia USA
PublisherAssociation for Information Systems
Number of pages14
ISBN (Electronic)9784902590838
Publication statusPublished - 2018
EventPacific Asia Conference on Information Systems 2018 - Yokohama, Japan
Duration: 26 Jun 201830 Jun 2018
Conference number: 22nd (Website) (Proceedings)


ConferencePacific Asia Conference on Information Systems 2018
Abbreviated titlePACIS 2018
Internet address


  • Causal model
  • Decision
  • Knowledge-based
  • Peatland
  • Wildfires

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