Monitoring rice lodging grade via Sentinel-2A images based on change vector analysis

ABSTRACT

Lodging stress influences the yield, quality, and mechanical harvesting ability of rice (Oryza sativa L.). It is of great significance for the quantitative and objective evaluation of rice yield loss to obtain the rice lodging distribution and grade information rapidly and nondestructively. The purpose of this paper was to establish a remote sensing monitoring method for the grade of rice lodging based on change vector analysis via Sentinel-2A images before and after lodging. Taking the lodging ratio (LR) of rice in the parcel as the characterization index, the changes in spectral reflectance and vegetation index of the rice canopy under different lodging grade stresses were analyzed. A 7-dimensional space vector was composed of a canopy spectral reflectance and vegetation index. A new angle vector was formed by the angle between each vector object and the axis of the canopy spectrum (vegetation index). Based on the difference in feature vectors before and after lodging, a lodging grade monitoring model based on rice parcels was constructed, and the accuracy of the model was verified using field observations. The results showed that the spectral reflectance of the rice canopy after lodging increased with the increase in lodging stress. The difference in vegetation index before and after lodging increased with the increase in lodging severity. Based on the change in the magnitude of the canopy spectral reflectance and its angle vector, and the vegetation index and its angle vector, the R² of the rice lodging model was 0.66, 0.66, 0.60, and 0.59, respectively, and the RMSE values were 21.03%, 20.37%, 22.13%, and 22.84%, respectively. Therefore, the accuracy of the model constructed using the vegetation index was the highest. The canopy spectral reflectance and difference in the vegetation index of rice changed regularly with lodging grade stress. The model based on the change magnitude of the vegetation index could effectively realize remote sensing monitoring of the grade of rice lodging in Wuchang.

Key words:

• rice
• lodging grade
• parcel
• Sentinel-2A
• change vector analysis (CVA)

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was supported by the National Key Research and Development Program of China (2019YFD1101102-3), the National Natural Science Foundation of China (41571323), the Beijing Talents Project (2020A58), Science and Technology Planning Project of Guangdong - Construction of New Research & Development Institutions in Northwest of East Guangdong (2019B090905006). We are very grateful to the people who supported us in the field data collection