Extraction of Maize Growth Stages in the Sanjiang Plain of China from 2003 to 2022 and Their Spatio-temporal Changes in Response to Meteorological Variables

Huichun Ye¹Bingrui Zhang²Shanyu Huang³Chaojia Nie²Peng Wei²Minghao Qin²Hongye Wang^4*

• ¹Aerospace Information Research Institute, Chinese Academy of Sciences (CAS), Beijing, China
• ²International Research Center of Big Data for Sustainable Development Goals (CBAS), Beijing, Beijing Municipality, China
• ³Beijing Keda Tongrui Technology Co., Ltd,, Beijing, China
• ⁴Cultivated Land Quality Monitoring and Protection Center, Ministry of Agriculture and Rural Affairs, Beijing, China

How to quickly monitor the growth process of maize on a large scale is crucial for regional maize growth assessment, yield estimation, and farmland management. This article takes the Sanjiang Plain in Northeast China as the research area, which is the main grain production area in China. Using MODIS NDVI time series data and Savitzky Golay and Whittaker filtering techniques, a remote sensing extraction method for key growth stages of maize (i.e., jointing stage, tasseling stage, and maturity stage) was established. The spatiotemporal characteristics of these growth stages from 2003 to 2022 were analyzed, alongside their meteorological influences. Results show the Whittaker filter achieves high accuracy, with errors under 8 days. Jointing stages typically fall between June 9 th and June 25 th , tasseling stages between July 20 th and August 5 th , and maturity stages between September 2 13 th and September 29 th . From 2003 to 2022, jointing and tasseling stages advanced by 0.43 and 0.19 days/year, respectively, while the maturity stage was delayed by 0.38 days/year, indicating an extended growing season correlated with rising surface temperatures and precipitation in the preceding month. These findings offer theoretical and technical guidance for crop growth monitoring, yield assessment, and farmland management.