Study on Rice Phenological Differences under Heavy Metal Stress by Using Multi-source Remote Sensing Time-Series Images

Abstract

Heavy metal pollution is surveyed rapidly and accurately, which is of great significance for soil pollution control. heavy metal pollution on farmland results in phenological changes, and we can use remote sensing technology to observe these changes. In the paper, Normalized Difference Vegetation Index (NDVI) time-series is built based on multi-source remote sensing images. Savitzky-Golay filter (S-G filter) was applied for denoising and reconstructing the time series. NDVI time series were used to calculate phenological indicators. Five phenological indicators were selected, which include seasonal amplitude, growth rate, seasonal length, seasonal integral and base level, to study on effect of heavy metal stress on rice phenology. The results showed that differences in phenological indexes at different levels of heavy metal stress as well as the phenological indicators under the stressed condition were generally lower than those under mild and moderate stress. From the findings, it can be concluded that the superiority of remote sensing phenological information in the monitoring of heavy metal stress in rice, and a new method for distinguishing heavy metal stress in rice will be provided.