Improving the matching degree between remotely sensed phenological dates and physiological growing stages of soybean by a dynamic offset-adjustment strategy

Abstract

Crop phenology provides crucial information for determining the appropriate timing of farm management practices and predicting crop yields. Satellite remote sensing has become a burgeoning tool for rapid phenological monitoring over wide spatial regions. However, there are significant timing gaps between the satellite-based phenological feature points and ground-observed physiological growing stages of the target. In this study, a dynamic offset-adjustment strategy that aims to improve the matching degree of the above two is proposed and tested with soybean across 16 states in the United States. A series of remotely sensed phenological transition dates that are characteristics of key growing stages of soybean were retrieved using MODIS time series data over the period 2000–2020 and the offset adjustments to the dates were identified by dynamically adjusting offset values till the minimum RMSE between the remote sensing-based and the ground-observed dates of physiological growing stages were obtained. The results indicated that the offset-adjustment strategy can significantly improve the alignments between remotely sensed phenological dates and field-based physiological growing stages of soybean in contrast to these without taking adjustment, with the average RMSE dropping by 58.58 %, 51.59 %, 31.15 %, 25.33 %, 24.67 % in the downturn, peak of season (POS), upturn, stabilization and recession dates, respectively. Among tested remotely sensed characteristics, the end of season (EOS) dates show the greatest alignment with its corresponding physiological growing stage, i.e., the dropping leaves stage. Comparison of the performance of the upturn date and start of season (SOS) in monitoring the date of the emerged stage indicates that the later one exhibits a better consistency with the ground-observed emerged stage after taking the adjustment, with the average RMSE dropping by 56.52 %. The proposed offset-adjustment strategy offers an approach for adjusting remotely sensed characteristics so to make them more consistent with the ground-observed crop physiological growing stages.