MCD64A1 Burnt Area Dataset Assessment using Sentinel-2 and Landsat-8 on Google Earth Engine: A Case Study in Rompin, Pahang in Malaysia

TL;DR

This study evaluates the effectiveness of the MCD64A1 burnt area dataset in detecting small-scale fires in Peninsular Malaysia using Google Earth Engine, validated against Sentinel-2 and Landsat-8 imagery.

Contribution

The paper assesses the suitability of MCD64A1 for burnt area detection in Malaysia and demonstrates its practical application with a case study in Rompin.

Findings

MCD64A1 effectively identifies historical fires in Peninsular Malaysia.

Validation shows good agreement between MCD64A1 and surface reflectance imagery.

Additional case studies are recommended for broader validation.

Abstract

This research paper intends to explore the suitability of adopting the MCD64A1 product to detect burnt areas using Google Earth Engine (GEE) in Peninsular Malaysia. The primary aim of this study is to find out if the MCD64A1 is adequate to identify the small-scale fire in Peninsular Malaysia. To evaluate the MCD64A1, a fire that was instigated in Rompin, a district of Pahang on March 2021 has been chosen as the case study in this work. Although several other burnt area datasets had also been made available in GEE, only MCD64A1 is selected due to its temporal availability. In the absence of validation information associated with the fire from the Malaysian government, public news sources are utilized to retrieve details related to the fire in Rompin. Additionally, the MCD64A1 is also validated with the burnt area observed from the true color imagery produced from the surface reflectance of Sentinel-2 and Landsat-8. From the burnt area assessment, we scrutinize that the MCD64A1 product is practical to be exploited to discover the historical fire in Peninsular Malaysia. However, additional case studies involving other locations in Peninsular Malaysia are advocated to be carried out to substantiate the claims discussed in this work.