Estimation of rice key phenology date using Chinese HJ-1 vegetation index time-series images

Accurate estimation of rice phenology is of critical importance for agricultural practices and studies. However, the accuracy of key phenological parameters extracted by remote sensing data cannot be guaranteed because of the influence of climate, e.g. the monsoon season, and limited available remote sensing data. With China Remote Sensing career advancement, a large number of independent researches and development satellites have launched. Among a new generation of middle to high resolution satellites, HJ-1 stands out. It sets fine spatial resolution (30 m), multi-spectral and high temporal resolution (2-day for constellation) with 360 km swath in a fusion technology with strategic significance. The time-series vegetation indices (VIs), such as the Normalized Difference Vegetation Index (NDVI) and the 2-band Enhanced Vege-tation Index (EVI2) are widely used in the studies of crop land classification, plant productivity, phenology, and crop growth monitoring. It has been shown that VIs values are relatively insensitive to the differences in angular viewing factors and atmospheric disturbances and thereby can be used as a benchmark for direct comparison between sensors. In order to explore the adaptability of Chinese HJ-1 images in rice phenological parameters extraction, two widely used VIs, NDVI and EVI2, were adopted to minimize the influence of environmental factors and the intrinsic difference among the sensor. Savitzky-Golay (S-G) filters were applied to construct continuous VI profiles per pixel. Before phenological parameters extraction, the planting area of single-cropped rice was estimated using a stepwise classification strategy. Divided by the heading date, the growth phases of single-cropped rice can be classified into vegetative growth and reproductive growth. Because the maximum VI usually appears around the heading date, we defined the heading date as the date of the maximum VI on the VI profile. In general, the rice fields are flooded before transplanting and the VI of rice fields decreases during this period and then increases after rice planting. Therefore, we defined the transplanting date of rice as the minimal point along the VI profile. Due to the etiolation and senescence of the rice leaves, the VI decreases after the heading, and the maturation date of rice is identified by the maximum slope method. The results were validated with the field survey data collected by the local agro-meteorological station. The results showed that, compared with NDVI, EVI2 was more stable. Compared with the observed phenological data of the single-cropped rice, the VI time-series had a low root mean square error (RMSE), and EVI2 showed higher accuracy compared with NDVI. We also demonstrate the application of phenology extraction of the single-cropped rice in a spatial scale in the study area. While the work is of general value, it can also be extrapolated to other regions where qualified remote sensing data are the bottleneck but where complementary data are occasionally available.