Detection of Corn Phenological Stages with Landsat Satellite Imagery: A Case Study in Ngawi Regency, Indonesia

This study explores how to use the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) to combine Landsat and MODIS images and track the growth stages of corn using the vegetation index (NDVI) and the water index (NDWI). The idea was implemented in Ngawi Regency as it is a major contributor to corn production in East Java, Indonesia. Based on spectral index analysis, interviews with local farmers, and data from the Ngawi Food Security and Agriculture Office, the fused images identified two cycles of corn planting and harvesting per year. The first cycle occurred in October–January with the following corn phenology phases: early vegetative (NDVI ~0.3), late vegetative (NDVI ~0.6), early generative (NDVI ~0.8), and late generative (NDVI ~0.7, harvest). The second cycle occurred in February-May/June with the following corn phenology phases: early vegetative (NDVI ~0.3-0.4), late vegetative (NDVI ~0.6-0.7), early generative (NDVI ~0~0.8), and late generative (NDVI ~0.5-0.7, harvest). The results showed that the corn area in May 2019, June 2022, and May 2023 was mostly in the early generative and late generative phases, respectively, covering about 219.15, 178.74, and 236.43 ha from Landsat imagery and 200.88, 180.18, and 205.92 ha from ESTARFM fusion imagery. Despite the differences between Landsat images and ESTARFM fusion images, in detecting the total area of corns, the ESTARFM model successfully predict the corn phenology pattern in Ngawi.