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Accurate estimate of the seasonal leaf area index (LAI) in croplands is required for understanding not only intra- and inter-annual crop development, but also crop management. Lack of consideration in different growth phases in the relationship between LAI and vegetation indices (VI) often results in unsatisfactory estimation in the seasonal course of LAI. In this study, we partitioned the growing season into two phases separated by maximum VI (    VI max    ) and applied the general regression model to the data gained from two phases. As an alternative method to capture the influence of seasonal phenological development on the LAI-VI relationship, we developed a consistent development curve method and compared its performance with the general regression approaches. We used the Normalized Difference VI (NDVI) and the Enhanced VI (EVI) from the rice paddy sites in Asia (South Korea and Japan) and Europe (Spain) to examine its applicability across different climate conditions and management cycles. When the general regression method was used, separating the season into two phases resulted in no better estimation than the estimation obtained with the entire season observation due to an abrupt change in seasonal LAI occurring during the transition between the before and afterVI max    . The consistent development curve method reproduced the seasonal patterns of LAI from both NDVI and EVI across all sites better than the general regression method. Despite less than satisfactory estimation of a localLAI max    , the consistent development curve method demonstrates improvement in estimating the seasonal course of LAI. The method can aid in providing accurate seasonal LAI as an input into ecological process-based models

Evaluation of a Phenology-Dependent Response Method for Estimating Leaf Area Index of Rice Across Climate Gradients