Data Acquisition Guide for Forest Fire Risk Modelling in Malaysia

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.