Types of ground objects had been selected from 157-63, 157-66 and 84-65, a total of 12 sample boxes were chosen, and each box consists of 20 pixels 20 pixels. Figure 3 shows the distribution diagram in the chosen four sorts of landcovers. The Flavonol Biological Activity average of 400 sample points in every single box was calculated to receive the average on the time series curve of the 4 forms of landcovers, as shown in Figure 4. Among the 4 types of ground objects, the typical backscattering coefficient of buildings was the highest, and that of water was the lowest. The average backscattering coefficient of non-rice vegetation was greater than that of rice. Furthermore, because there was no flooding period for non-rice vegetation, the minimum value of its time series curve was higher than that of rice.Agriculture 2021, 11,6 ofFigure 3. Distribution diagram of sample locations for statistical characteristic analysis.Figure four. The typical backscattering coefficient curves of 4 forms of sample points in VH polarization.Distinctive from other dryland crops and vegetation, there was an agricultural flooding period within the development approach of rice, at which the backscattering coefficient of rice was close to that of water. The transplanting time of early rice was roughly April, as well as the harvesting time was around in the finish of July for the starting of August. The transplanting time of late rice was roughly in the end of July to the starting of August, along with the harvesting time was approximately December. The rice inside the 3 D-Galacturonic acid (hydrate) Autophagy frames was rice-1, rice-2 and rice-3. They started transplanting at the corresponding 1st time, when the rice was inside the flooding period. Using the growth of rice, the backscattering coefficient reached the maximum at pretty much the eighth time. When the rice entered the mature stage, the backscattering coefficient began to reduce, plus the harvest was completed at the starting of August and entered the following development cycle of late rice. The results showed that the development cycle of rice inside the 3 frames had a certainAgriculture 2021, 11,7 ofsynchronization. Although the information from the 3 frames at the corresponding time were not totally consistent, the maximum time distinction was only 6 days, which was not enough to affect the phenological analysis of rice. The backscatter curves of 3 rice samples had some fluctuations, and also a feasible explanation was distinct soil situations. 2.2.three. Rice Sample Production According to Optimal Time Series Statistical Parameters In order to calculate the efficiency, 4 very simple time series statistical parameters have been selected for comparative evaluation of 4 ground objects, like maximum, minimum, average and variance. The typical represents the somewhat concentrated position in the time series information, the maximum worth plus the time series minimum value reflect the array of data modify, and the variance reflects the dispersion of time series information. The results were shown in Figure five.Figure 5. Time series statistical parameter diagram. (a) Maximum; (b) minimum; (c) average; (d) variance.According to Figure 5, the maximum worth of rice was close for the vegetation, the minimum value of rice was close towards the water physique, the variance of rice was big, along with the average was reduced than that of vegetation. The maximum, minimum, and average valuesAgriculture 2021, 11,8 ofof buildings were the highest. The maximum, minimum, plus the typical from the water body had been the lowest. Then, the three parameters had been arbitra.