Mapping Rice Phenology Using MODIS Products in An Giang Province, Mekong River Delta, Vietnam

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides consistent long-term satellite observations that are valuable for rice mapping and production estimation through phenology extraction. This study evaluates the effectiveness of three MODIS products, MOD09GQ (1-day), MOD09Q1 (8-day), and MOD13Q1 (16-day), for mapping rice phenology in An Giang Province, a key rice-producing region in Vietnam’s climate-sensitive Mekong River Delta (MRD). The analysis focuses on rice cropping seasons from 2019 to 2021, using time series of the Normalized Difference Vegetation Index (NDVI) to capture temporal and spatial variations in rice growth dynamics. To address data gaps due to persistent cloud cover and sensor-related noises, smoothing techniques, including the Double Logistic Function (DLF) and Savitzky–Golay Filtering (SGF), were applied. Thirteen phenological parameters were extracted and used as inputs to an unsupervised K-Means clustering algorithm, enabling the classification of distinct rice growth patterns. The results show that DLF-processed MOD09GQ data most accurately reconstructed NDVI time series and captured short-term phenological transitions, outperforming coarser-resolution products. The resulting phenology maps could be used to correlate the influence of anthropogenic factors, such as the widespread adoption of short-duration rice varieties and shifts in water management practices. This study provides a robust framework for phenology-based rice mapping to support food security, sustainable agricultural planning, and climate resilience in the MRD.