Monitoring of Paddy and Maize Fields Using Sentinel-1 SAR Data and NGB Images: A Case Study in Papua, Indonesia

Abstract

This study addresses the question of how to evaluate the growth stage of food crops, for instance, paddy (Oryza sativa) and maize (Zea mays), from two different sensors in selected developed areas of Papua Province of Indonesia. Level-1 Ground Range Detected (L1 GRD) images from Sentinel-1 Synthetic Aperture Radar (SAR) data were used to investigate the growth of paddy and maize crops. An NGB camera was then used to obtain the Green Normalized Difference Vegetation Index (GNDVI), and the Enhanced Normalized Difference Vegetation Index (ENDVI) as in situ measurement. Afterwards, the results were analyzed based on the Radar Vegetation Index (RVI) and the Vertical-Vertical (VV) and Vertical Horizontal (VH) band backscatters at incidence angles of 30.55°–45.88°, and 30.59°–46.16° in 2021 and 2022, respectively. The findings showed that Sigma0_VV_db and sigma0_VH_db had a strong correlation (R2 above 0.900); however, polarization modification is required, specifically in the maize field. The RVI calculated and backscatter changes in this study were comparable to the in situ measurements, specifically those of paddy fields, in 2022. Even though the results of this study were not able to prove the RVI values from the two relative orbits (orbit31 and orbit155) due to the different angle incidences and the availability of the Sentinel-1 SAR data set over the study area, the division of SAR image data based on each relative orbit adequately represents the development of crops in our study areas. The significance of this study is expected to support food crop security and the implementation of development plans that contribute to the local government’s goals and settings.