Growth models and age estimation of rice using multitemporal vegetation index on landsat 8 imagery

Abstract

Age and growth are two essential rice biophysics parameters used to determine the health parameters and production rate. The spatial data of both parameters can utilize remote sensing technology, which in turn makes use of several vegetation indices to achieve accurate estimation. However, due to the rapid changes in rice plants' characteristics, it is essential to study vegetation index utilization using a multitemporal method to improve its accuracy. Therefore, this research uses a multitemporal Enhanced Vegetation Index (EVI) to estimate rice's age and growth model. The multitemporal EVI patterns were observed to estimate the Time Early Planting (TEP) and the maximum EVI value of rice in an area. The results showed that the maximum EVI value in the rice fields of Demak Regency has a class range of 0.4 to more than 0.9. The highest value is in the class of 0.80 - 0.85 covering 12023.28 ha, followed by 0.75 - 0.80 at 11834.19 ha. Furthermore, the multitemporal EVI method on Landsat 8 images was used to estimate the rice age with accuracy or RMSE of 7.7 days. The result also showed that this value is good enough because the RMSE is still in the same range of paddy growth phases.