Long-Term NDVI-Based Analysis of Rice Growth Cycles in Malaysia Using Landsat Time-Series Data

Abstract

Rice is one of the key food crops in Malaysia and is cultivated under a double-cropping system that consists of a main season and an off-season. Continuous and long-term monitoring of rice growth is essential for understanding crop phenology and supporting future agricultural management and yield assessment. This study presents a long-term analysis of rice growth trends in Malaysia using the Normalized Difference Vegetation Index derived from Landsat satellite time-series data spanning January 2000 to December 2024. The study area covers approximately 10 km² of rice cultivation land located near Pekan, on the east coast of Peninsular Malaysia. Monthly NDVI composites were generated from Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI, and Landsat 9 OLI-2 surface reflectance products, with cloud-contaminated pixels removed using quality assessment information. The results reveal a clear bimodal NDVI pattern that corresponds to Malaysia’s double-cropping rice system, with peak NDVI values occurring during the off-season (May–June) and main season (October–November). Seasonal NDVI variations reflect distinct rice growth stages, including tillering, heading, and harvesting periods. The findings demonstrate the capability of long-term Landsat NDVI data to effectively capture rice growth dynamics and seasonal cycles. This study provides a quantitative baseline for future research on rice growth stage modeling, pest and disease monitoring, and yield estimation using satellite-based observations.