QUANTITATIVE MONITORING OF COMPLETE RICE GROWING SEASONS USING SENTINEL 2 TIME SERIES IMAGES

The payload Multispectral Instrument (MSI) on the satellite Sentinel-2A provides data with strong spectral information, reasonable spatial resolution and good revisit time, which make them suitable for crop monitoring. With the availability of the image data over the complete rice growing season over two consecutive years, spectral time series analysis of rice crops is conducted in this study for the Riverina region of Coleambally, New South Wales, Australia. Vegetation and water indices are adopated to compare the growing patterns of rice over the 2015/2016 and 2016/2017 growing seasons. Rice crops of different varieties are identified and examined. Different seed sowing methods are also compared in terms of their effect on the latter season. The results show that the growth pattern of rice follows a particular trend that can be distinguished from other types of vegetation. This is facilitated by a property unique to rice where water sensitive indices produce a higher reading than vegetation indices during the initial flooding period of the season, after which, the crop growth reverses this and the biomass sensitive index becomes larger. Spectral analysis of rice crops planted via various methods reveals that the drill sowing method did not produce this unique characteristic as the late flooding time results in a very short submersion period for the rice seedlings, which is a valuable finding.