Citation

Chew, Yee Jian and Ooi, Shih Yin and Pang, Ying Han (2021) Data Acquisition Guide for Forest Fire Risk Modelling in Malaysia. In: 2021 9th International Conference on Information and Communication Technology (ICoICT), 3-5 Aug. 2021, Yogyakarta, Indonesia.

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Abstract

Availability of remote sensing data (i.e., information captured from satellite) in conjunction with the usage of Geographic Information System (GIS) has made it feasible to deliver a fire model capable to segregate the area into a higher or lower risk fire region. The advancement of technologies has also inaugurated the possibility to incorporate remote sensing information and other ground data (e.g., meteorological data, distance to road data, etc.) by utilizing machine learning classifiers or deep learning algorithm to predict the forest fire occurrence. However, it should be highlighted that the data acquisition procedure may vary depending on the vicinity of the study area since some data are only obtainable from the specific government authority. In this paper, we will be disclosing some of the publicly accessible remote sensing data and some of the valuable data attainable from the Malaysian government that is useful for detecting forest fire in Malaysia. Additionally, previous studies and works that have employed the data source to map forest fire are also deliberated in this paper. Only the data that had been exploited in the past for Malaysia are discussed.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Fire risk assessment, Fire, Data Acquisition, Map, GIS
Subjects:	T Technology > TH Building construction > TH9025-9745 Protection of buildings Including protection from dampness, fire, burglary
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	04 Nov 2021 06:57
Last Modified:	04 Nov 2021 06:57
URII:	http://shdl.mmu.edu.my/id/eprint/9762

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