Abstract
Rice fields play a crucial role in ensuring food security in a region. However, a major challenge is preventing the conversion of rice fields, which can jeopardize food availability. Therefore, it is essential to rapidly and accurately map rice field areas to precisely detect changes. An effective approach involves remote sensing technology and cloud computing. This research aims to map rice fields in Sidenreng Rappang Regency using Landsat-8 data with the random forest method on the Google Earth Engine platform. This method has proven efficient in image classification and yields accurate land mapping. In this study, Landsat-8 data serves as the primary source, with random forest classifying areas as rice fields. The main finding indicates that the total area of rice fields in Sidenreng Rappang Regency reaches 51,480.43 hectares. Validation using data from the Central Statistics Agency (BPS) reveals a difference in area of 0.67%, while regression analysis demonstrates a strong correlation between mapping data and BPS data, with an R-squared value of 0.9455.
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