Determination of the most suitable indicator area and remote-sensing-based indices for early yield warning for winter–spring rice in the Central Highlands, Vietnam

Abstract

Our study aimed to determine the most suitable indicator area and a remote sensing-based index (RSI) for warning winter–spring rice yield in the Central Highlands, Vietnam. Rice yield and RSIs, including vegetation condition index (VCI), temperature condition index, vegetation health index, and temperature-vegetation dryness index, in the period 2000 to 2020 were analyzed. Mann–Kendall nonparametric test and Sen’s slope were used to determine the trends of rice yield and RSIs. Meanwhile, multiple correlation coefficients were used to determine the most suitable indicator area and RSI for rice yield warning, and stepwise linear regression was used to evaluate the reliability of their warning ability. Research results showed that VCI was the most suitable RSI for early rice yield warning. The indicator area identified based on VCI occupied 5% of the area of the Central Highlands. This area had more difficult farming conditions than the rice-growing area and crops grown in it were also sensitive to water sources. Furthermore, the results also indicated that the VCI of the indicator area could predict rice yield from 1 to 3 months before harvest. The forecast accuracy depended on the sensitivity of rice yield to VCI and the stability of rice yield in each province.