Detail Abstract

Monitoring rice growth and predicting rice biomass by Sentinel-2 data at Giao Thuy, Nam Dinh

Abstract

This study aims to monitor the growth of rice using the normalized difference vegetation index (NDVI) and to determine equations for predicting rice biomass at Giao Thuy, Nam Dinh. The field data is divided into two data sections for calibration and data to evaluate a general linear model. Twenty sample plots at pre-harvest time were collected, 15 of which were used for model calibration and 5 plots for model evaluation. The study used remote sensing data (Sentinel-2) for all the covered study areas in the 2020 critical period for rice growth (January to June), combined monthly composite images of vegetation indices as input features, and some seasonal analysis to assist in determining the rice-producing region, and thence determination equations for predicting rice biomass. From the image, the rice-producing region has been zoned to calculate the biomass in the heading of rice. The results are as follows: (1) The heading and flowering stage of vu Chiem in 2020 is characterized by the maximum NDVI, and at the maturity stage, NDVI decreased continuously. The NDVI was 0.75 and 0.72 in the heading stage and flowering stage, respectively; (2) Additionally, to estimate above ground biomass (AGB) of rice, the Sentinel- 2 NDVI index was better in the heading stage: the coefficient of determination (R²) =  0.885 and root mean square error (RMSE) = 30.2ton/ha, and regression analysis between NDVI and AGB for the equation is AGB = 346.45*NDVI – 156.98; (3) the relationship between NDVI and AGB can be used to monitor the growth of rice plants from which to determine when the biomass value is highest during the period.